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Archive for the ‘Mutant Gene Expression’ Category

Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle


Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Reporter: Stephen S Williams, PhD

 

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series D:

Metabolic Genomics & Pharmaceutics, Vol. I

SACHS FLYER 2014 Metabolomics SeriesDindividualred-page2

which is now available on Amazon Kindle at

http://www.amazon.com/dp/B012BB0ZF0.

This e-Book is a comprehensive review of recent Original Research on  METABOLOMICS and related opportunities for Targeted Therapy written by Experts, Authors, Writers. This is the first volume of the Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases.  It is written for comprehension at the third year medical student level, or as a reference for licensing board exams, but it is also written for the education of a first time baccalaureate degree reader in the biological sciences.  Hopefully, it can be read with great interest by the undergraduate student who is undecided in the choice of a career. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon.

All forthcoming BioMed e-Book Titles can be viewed at:

https://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

  • delivering curation and summary interpretations of latest findings and innovations on an open-access, Web 2.0 platform with future goals of providing primarily concept-driven search in the near future
  • providing a social platform for scientists and clinicians to enter into discussion using social media
  • compiling recent discoveries and issues in yearly-updated Medical E-book Series on Amazon’s mobile Kindle platform

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Metabolic Genomics & Pharmaceutics, Vol. I

Chapter 1: Metabolic Pathways

Chapter 2: Lipid Metabolism

Chapter 3: Cell Signaling

Chapter 4: Protein Synthesis and Degradation

Chapter 5: Sub-cellular Structure

Chapter 6: Proteomics

Chapter 7: Metabolomics

Chapter 8:  Impairments in Pathological States: Endocrine Disorders; Stress

                   Hypermetabolism and Cancer

Chapter 9: Genomic Expression in Health and Disease 

 

Summary 

Epilogue

 

 

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Treatment for Chronic Leukemias [2.4.4B]

Larry H. Bernstein, MD, FCAP, Author, Curator, Editor

https://pharmaceuticalintelligence.com/2015/8/11/larryhbern/Treatment-for-Chronic-Leukemias-[2.4.4B]

2.4.4B1 Treatment for CML

Chronic Myelogenous Leukemia Treatment (PDQ®)

http://www.cancer.gov/cancertopics/pdq/treatment/CML/Patient/page4

Treatment Option Overview

Key Points for This Section

There are different types of treatment for patients with chronic myelogenous leukemia.

Six types of standard treatment are used:

  1. Targeted therapy
  2. Chemotherapy
  3. Biologic therapy
  4. High-dose chemotherapy with stem cell transplant
  5. Donor lymphocyte infusion (DLI)
  6. Surgery

New types of treatment are being tested in clinical trials.

Patients may want to think about taking part in a clinical trial.

Patients can enter clinical trials before, during, or after starting their cancer treatment.

Follow-up tests may be needed.

There are different types of treatment for patients with chronic myelogenous leukemia.

Different types of treatment are available for patients with chronic myelogenous leukemia (CML). Some treatments are standard (the currently used treatment), and some are being tested in clinical trials. A treatment clinical trial is a research study meant to help improve current treatments or obtain information about new treatments for patients with cancer. When clinical trials show that a new treatment is better than the standard treatment, the new treatment may become the standard treatment. Patients may want to think about taking part in a clinical trial. Some clinical trials are open only to patients who have not started treatment.

Six types of standard treatment are used:

Targeted therapy

Targeted therapy is a type of treatment that uses drugs or other substances to identify and attack specific cancer cells without harming normal cells. Tyrosine kinase inhibitors are targeted therapy drugs used to treat chronic myelogenous leukemia.

Imatinib mesylate, nilotinib, dasatinib, and ponatinib are tyrosine kinase inhibitors that are used to treat CML.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Chemotherapy

Chemotherapy is a cancer treatment that uses drugs to stop the growth of cancer cells, either by killing the cells or by stopping them from dividing. When chemotherapy is taken by mouth or injected into a vein or muscle, the drugs enter the bloodstream and can reach cancer cells throughout the body (systemic chemotherapy). When chemotherapy is placed directly into the cerebrospinal fluid, an organ, or a body cavity such as the abdomen, the drugs mainly affect cancer cells in those areas (regional chemotherapy). The way the chemotherapy is given depends on the type and stage of the cancer being treated.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Biologic therapy

Biologic therapy is a treatment that uses the patient’s immune system to fight cancer. Substances made by the body or made in a laboratory are used to boost, direct, or restore the body’s natural defenses against cancer. This type of cancer treatment is also called biotherapy or immunotherapy.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

High-dose chemotherapy with stem cell transplant

High-dose chemotherapy with stem cell transplant is a method of giving high doses of chemotherapy and replacing blood-forming cells destroyed by the cancer treatment. Stem cells (immature blood cells) are removed from the blood or bone marrow of the patient or a donor and are frozen and stored. After the chemotherapy is completed, the stored stem cells are thawed and given back to the patient through an infusion. These reinfused stem cells grow into (and restore) the body’s blood cells.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Donor lymphocyte infusion (DLI)

Donor lymphocyte infusion (DLI) is a cancer treatment that may be used after stem cell transplant.Lymphocytes (a type of white blood cell) from the stem cell transplant donor are removed from the donor’s blood and may be frozen for storage. The donor’s lymphocytes are thawed if they were frozen and then given to the patient through one or more infusions. The lymphocytes see the patient’s cancer cells as not belonging to the body and attack them.

Surgery

Splenectomy

What`s new in chronic myeloid leukemia research and treatment?

http://www.cancer.org/cancer/leukemia-chronicmyeloidcml/detailedguide/leukemia-chronic-myeloid-myelogenous-new-research

Combining the targeted drugs with other treatments

Imatinib and other drugs that target the BCR-ABL protein have proven to be very effective, but by themselves these drugs don’t help everyone. Studies are now in progress to see if combining these drugs with other treatments, such as chemotherapy, interferon, or cancer vaccines (see below) might be better than either one alone. One study showed that giving interferon with imatinib worked better than giving imatinib alone. The 2 drugs together had more side effects, though. It is also not clear if this combination is better than treatment with other tyrosine kinase inhibitors (TKIs), such as dasatinib and nilotinib. A study going on now is looking at combing interferon with nilotinib.

Other studies are looking at combining other drugs, such as cyclosporine or hydroxychloroquine, with a TKI.

New drugs for CML

Because researchers now know the main cause of CML (the BCR-ABL gene and its protein), they have been able to develop many new drugs that might work against it.

In some cases, CML cells develop a change in the BCR-ABL oncogene known as a T315I mutation, which makes them resistant to many of the current targeted therapies (imatinib, dasatinib, and nilotinib). Ponatinib is the only TKI that can work against T315I mutant cells. More drugs aimed at this mutation are now being tested.

Other drugs called farnesyl transferase inhibitors, such as lonafarnib and tipifarnib, seem to have some activity against CML and patients may respond when these drugs are combined with imatinib. These drugs are being studied further.

Other drugs being studied in CML include the histone deacetylase inhibitor panobinostat and the proteasome inhibitor bortezomib (Velcade).

Several vaccines are now being studied for use against CML.

2.4.4.B2 Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia Treatment (PDQ®)

General Information About Chronic Lymphocytic Leukemia

Key Points for This Section

  1. Chronic lymphocytic leukemia is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell).
  2. Leukemia may affect red blood cells, white blood cells, and platelets.
  3. Older age can affect the risk of developing chronic lymphocytic leukemia.
  4. Signs and symptoms of chronic lymphocytic leukemia include swollen lymph nodes and tiredness.
  5. Tests that examine the blood, bone marrow, and lymph nodes are used to detect (find) and diagnose chronic lymphocytic leukemia.
  6. Certain factors affect treatment options and prognosis (chance of recovery).
  7. Chronic lymphocytic leukemia is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell).

Chronic lymphocytic leukemia (also called CLL) is a blood and bone marrow disease that usually gets worse slowly. CLL is one of the most common types of leukemia in adults. It often occurs during or after middle age; it rarely occurs in children.

http://www.cancer.gov/images/cdr/live/CDR755927-750.jpg

Anatomy of the bone; drawing shows spongy bone, red marrow, and yellow marrow. A cross section of the bone shows compact bone and blood vessels in the bone marrow. Also shown are red blood cells, white blood cells, platelets, and a blood stem cell.

Anatomy of the bone. The bone is made up of compact bone, spongy bone, and bone marrow. Compact bone makes up the outer layer of the bone. Spongy bone is found mostly at the ends of bones and contains red marrow. Bone marrow is found in the center of most bones and has many blood vessels. There are two types of bone marrow: red and yellow. Red marrow contains blood stem cells that can become red blood cells, white blood cells, or platelets. Yellow marrow is made mostly of fat.

Leukemia may affect red blood cells, white blood cells, and platelets.

Normally, the body makes blood stem cells (immature cells) that become mature blood cells over time. A blood stem cell may become a myeloid stem cell or a lymphoid stem cell.

A myeloid stem cell becomes one of three types of mature blood cells:

  1. Red blood cells that carry oxygen and other substances to all tissues of the body.
  2. White blood cells that fight infection and disease.
  3. Platelets that form blood clots to stop bleeding.

A lymphoid stem cell becomes a lymphoblast cell and then one of three types of lymphocytes (white blood cells):

  1. B lymphocytes that make antibodies to help fight infection.
  2. T lymphocytes that help B lymphocytes make antibodies to fight infection.
  3. Natural killer cells that attack cancer cells and viruses.
Blood cell development. CDR526538-750

Blood cell development. CDR526538-750

http://www.cancer.gov/images/cdr/live/CDR526538-750.jpg

Blood cell development; drawing shows the steps a blood stem cell goes through to become a red blood cell, platelet, or white blood cell. A myeloid stem cell becomes a red blood cell, a platelet, or a myeloblast, which then becomes a granulocyte (the types of granulocytes are eosinophils, basophils, and neutrophils). A lymphoid stem cell becomes a lymphoblast and then becomes a B-lymphocyte, T-lymphocyte, or natural killer cell.

Blood cell development. A blood stem cell goes through several steps to become a red blood cell, platelet, or white blood cell.

In CLL, too many blood stem cells become abnormal lymphocytes and do not become healthy white blood cells. The abnormal lymphocytes may also be called leukemia cells. The lymphocytes are not able to fight infection very well. Also, as the number of lymphocytes increases in the blood and bone marrow, there is less room for healthy white blood cells, red blood cells, and platelets. This may cause infection, anemia, and easy bleeding.

This summary is about chronic lymphocytic leukemia. See the following PDQ summaries for more information about leukemia:

  • Adult Acute Lymphoblastic Leukemia Treatment.
  • Childhood Acute Lymphoblastic Leukemia Treatment.
  • Adult Acute Myeloid Leukemia Treatment.
  • Childhood Acute Myeloid Leukemia/Other Myeloid Malignancies Treatment.
  • Chronic Myelogenous Leukemia Treatment.
  • Hairy Cell Leukemia Treatment

Older age can affect the risk of developing chronic lymphocytic leukemia.

Anything that increases your risk of getting a disease is called a risk factor. Having a risk factor does not mean that you will get cancer; not having risk factors doesn’t mean that you will not get cancer. Talk with your doctor if you think you may be at risk. Risk factors for CLL include the following:

  • Being middle-aged or older, male, or white.
  • A family history of CLL or cancer of the lymph system.
  • Having relatives who are Russian Jews or Eastern European Jews.

Signs and symptoms of chronic lymphocytic leukemia include swollen lymph nodes and tiredness.

Usually CLL does not cause any signs or symptoms and is found during a routine blood test. Signs and symptoms may be caused by CLL or by other conditions. Check with your doctor if you have any of the following:

  • Painless swelling of the lymph nodes in the neck, underarm, stomach, or groin.
  • Feeling very tired.
  • Pain or fullness below the ribs.
  • Fever and infection.
  • Weight loss for no known reason.

Tests that examine the blood, bone marrow, and lymph nodes are used to detect (find) and diagnose chronic lymphocytic leukemia.

The following tests and procedures may be used:

Physical exam and history : An exam of the body to check general signs of health, including checking for signs of disease, such as lumps or anything else that seems unusual. A history of the patient’s health habits and past illnesses and treatments will also be taken.

Complete blood count (CBC) with differential : A procedure in which a sample of blood is drawn and checked for the following:

The number of red blood cells and platelets.

The number and type of white blood cells.

The amount of hemoglobin (the protein that carries oxygen) in the red blood cells.

The portion of the blood sample made up of red blood cells.

Results from the Phase 3 Resonate™ Trial

Significantly improved progression free survival (PFS) vs ofatumumab in patients with previously treated CLL

  • Patients taking IMBRUVICA® had a 78% statistically significant reduction in the risk of disease progression or death compared with patients who received ofatumumab1
  • In patients with previously treated del 17p CLL, median PFS was not yet reached with IMBRUVICA® vs 5.8 months with ofatumumab (HR 0.25; 95% CI: 0.14, 0.45)1

Significantly prolonged overall survival (OS) with IMBRUVICA® vs ofatumumab in patients with previously treated CLL

  • In patients with previously treated CLL, those taking IMBRUVICA® had a 57% statistically significant reduction in the risk of death compared with those who received ofatumumab (HR 0.43; 95% CI: 0.24, 0.79; P<0.05)1

Typical treatment of chronic lymphocytic leukemia

http://www.cancer.org/cancer/leukemia-chroniclymphocyticcll/detailedguide/leukemia-chronic-lymphocytic-treating-treatment-by-risk-group

Treatment options for chronic lymphocytic leukemia (CLL) vary greatly, depending on the person’s age, the disease risk group, and the reason for treating (for example, which symptoms it is causing). Many people live a long time with CLL, but in general it is very difficult to cure, and early treatment hasn’t been shown to help people live longer. Because of this and because treatment can cause side effects, doctors often advise waiting until the disease is progressing or bothersome symptoms appear, before starting treatment.

If treatment is needed, factors that should be taken into account include the patient’s age, general health, and prognostic factors such as the presence of chromosome 17 or chromosome 11 deletions or high levels of ZAP-70 and CD38.

Initial treatment

Patients who might not be able to tolerate the side effects of strong chemotherapy (chemo), are often treated with chlorambucil alone or with a monoclonal antibody targeting CD20 like rituximab (Rituxan) or obinutuzumab (Gazyva). Other options include rituximab alone or a corticosteroid like prednisione.

In stronger and healthier patients, there are many options for treatment. Commonly used treatments include:

  • FCR: fludarabine (Fludara), cyclophosphamide (Cytoxan), and rituximab
  • Bendamustine (sometimes with rituximab)
  • FR: fludarabine and rituximab
  • CVP: cyclophosphamide, vincristine, and prednisone (sometimes with rituximab)
  • CHOP: cyclophosphamide, doxorubicin, vincristine (Oncovin), and prednisone
  • Chlorambucil combined with prednisone, rituximab, obinutuzumab, or ofatumumab
  • PCR: pentostatin (Nipent), cyclophosphamide, and rituximab
  • Alemtuzumab (Campath)
  • Fludarabine (alone)

Other drugs or combinations of drugs may also be also used.

If the only problem is an enlarged spleen or swollen lymph nodes in one region of the body, localized treatment with low-dose radiation therapy may be used. Splenectomy (surgery to remove the spleen) is another option if the enlarged spleen is causing symptoms.

Sometimes very high numbers of leukemia cells in the blood cause problems with normal circulation. This is calledleukostasis. Chemo may not lower the number of cells until a few days after the first dose, so before the chemo is given, some of the cells may be removed from the blood with a procedure called leukapheresis. This treatment lowers blood counts right away. The effect lasts only for a short time, but it may help until the chemo has a chance to work. Leukapheresis is also sometimes used before chemo if there are very high numbers of leukemia cells (even when they aren’t causing problems) to prevent tumor lysis syndrome (this was discussed in the chemotherapy section).

Some people who have very high-risk disease (based on prognostic factors) may be referred for possible stem cell transplant (SCT) early in treatment.

Second-line treatment of CLL

If the initial treatment is no longer working or the disease comes back, another type of treatment may help. If the initial response to the treatment lasted a long time (usually at least a few years), the same treatment can often be used again. If the initial response wasn’t long-lasting, using the same treatment again isn’t as likely to be helpful. The options will depend on what the first-line treatment was and how well it worked, as well as the person’s health.

Many of the drugs and combinations listed above may be options as second-line treatments. For many people who have already had fludarabine, alemtuzumab seems to be helpful as second-line treatment, but it carries an increased risk of infections. Other purine analog drugs, such as pentostatin or cladribine (2-CdA), may also be tried. Newer drugs such as ofatumumab, ibrutinib (Imbruvica), and idelalisib (Zydelig) may be other options.

If the leukemia responds, stem cell transplant may be an option for some patients.

Some people may have a good response to first-line treatment (such as fludarabine) but may still have some evidence of a small number of leukemia cells in the blood, bone marrow, or lymph nodes. This is known as minimal residual disease. CLL can’t be cured, so doctors aren’t sure if further treatment right away will be helpful. Some small studies have shown that alemtuzumab can sometimes help get rid of these remaining cells, but it’s not yet clear if this improves survival.

Treating complications of CLL

One of the most serious complications of CLL is a change (transformation) of the leukemia to a high-grade or aggressive type of non-Hodgkin lymphoma called diffuse large cell lymphoma. This happens in about 5% of CLL cases, and is known as Richter syndrome. Treatment is often the same as it would be for lymphoma (see our document called Non-Hodgkin Lymphoma for more information), and may include stem cell transplant, as these cases are often hard to treat.

Less often, CLL may transform to prolymphocytic leukemia. As with Richter syndrome, these cases can be hard to treat. Some studies have suggested that certain drugs such as cladribine (2-CdA) and alemtuzumab may be helpful.

In rare cases, patients with CLL may have their leukemia transform into acute lymphocytic leukemia (ALL). If this happens, treatment is likely to be similar to that used for patients with ALL (see our document called Leukemia: Acute Lymphocytic).

Acute myeloid leukemia (AML) is another rare complication in patients who have been treated for CLL. Drugs such as chlorambucil and cyclophosphamide can damage the DNA of blood-forming cells. These damaged cells may go on to become cancerous, leading to AML, which is very aggressive and often hard to treat (see our document calledLeukemia: Acute Myeloid).

CLL can cause problems with low blood counts and infections. Treatment of these problems were discussed in the section “Supportive care in chronic lymphocytic leukemia.”

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Nonhematologic Cancer Stem Cells [11.2.3]

Writer and Curator: Larry H. Bernstein, MD, FCAP 

Nonhematologic Stem Cells

11.2.3.1 C8orf4 negatively regulates self-renewal of liver cancer stem cells via suppression of NOTCH2 signalling

Pingping Zhu, Yanying Wang, Ying Du, Lei He, Guanling Huang, et al.
Nature Communications May 2015; 6(7122). http://dx.doi.org:/10.1038/ncomms8122

Liver cancer stem cells (CSCs) harbor self-renewal and differentiation properties, accounting for chemotherapy resistance and recurrence. However, the molecular mechanisms to sustain liver CSCs remain largely unknown. In this study, based on analysis of several hepatocellular carcinoma (HCC) transcriptome datasets and our experimental data, we find that C8orf4 is weakly expressed in HCC tumors and liver CSCs. C8orf4 attenuates the self-renewal capacity of liver CSCs and tumor propagation. We show that NOTCH2 is activated in liver CSCs. C8orf4 is located in the cytoplasm of HCC tumor cells and associates with the NOTCH2 intracellular domain, which impedes the nuclear translocation of N2ICD. C8orf4 deletion causes the nuclear translocation of N2ICD that triggers the NOTCH2 signaling, which sustains the stemness of liver CSCs. Finally, NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Altogether, C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.

Like stem cells, CSCs are characterized by self-renewal and differentiation simultaneously9. Not surprisingly, CSCs share core regulatory genes and developmental pathways with normal tissue stem cells. Accumulating evidence shows that NOTCH, Hedgehog and Wnt signaling pathways are implicated in the regulation of CSC self-renewal4. NOTCH signaling modulates many aspects of metazoan development and tissue stemness1011. NOTCH receptors contain four members (NOTCH1–4) in mammals, which are activated by engagement with various ligands. The aberrant NOTCH signaling was first reported to be involved in the tumorigenesis of human T-cell leukaemia1213. Recently, a number of studies have reported that the NOTCH signaling pathway is implicated in regulating self-renewal of breast stem cells and mammary CSCs1415. However, how the NOTCH signaling regulates the liver CSC self-renewal remains largely unknown.

C8orf4, also called thyroid cancer 1 (TC1), was originally cloned from a papillary thyroid carcinoma and its surrounding normal thyroid tissue16. C8orf4 is ubiquitously expressed across a wide range of vertebrates with the sequence conservation across species. A number of studies have reported that C8orf4 is highly expressed in several tumors and implicated in tumorigenesis171819. In addition, C8orf4 augments Wnt/β-catenin signaling in some cancer cells2021, suggesting it may be involved in the regulation of self-renewal of CSCs. However, the biological function of C8orf4 in the modulation of liver CSC self-renewal is still unknown. Here we show that C8orf4 is weakly expressed in HCC and liver CSCs. NOTCH2 signaling is highly activated in HCC tumors and liver CSCs. C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.

C8orf4 is weakly expressed in HCC tissues and liver CSCs

To search for driver genes in the oncogenesis of HCC, we performed genome-wide analyses using several online-available HCC transcriptome datasets by R language and Bioconductor approaches. After analysing gene expression profiles of HCC tumor and peri-tumor tissues, we identified >360 differentially expressed genes from both Park’s cohort (GSE36376; ref. 22) and Wang’s cohort (GSE14520; refs 2324). Of these changed genes, we focused on C8orf4, which was weakly expressed in HCC tumors derived from both Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) (Fig. 1a). Lower expression of C8orf4 was further confirmed in HCC samples by quantitative reverse transcription–PCR (qRT–PCR) and immunoblotting (Fig. 1b,c). In this study, HCC patient samples we used included all subtypes of HCC. In addition, these observations were further validated by immunohistochemical (IHC) staining (Fig. 1d). These data indicate that C8orf4 is weakly expressed in HCC tumor tissues.

C8orf4 is weakly expressed in HCC tumours and liver CSCs

C8orf4 is weakly expressed in HCC tumours and liver CSCs

Figure 1. C8orf4 is weakly expressed in HCC tumours and liver CSCs

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f1.jpg

(a)C8orf4 is weakly expressed in HCC patients. Using R language and Bioconductor methods, we analyzed C8orf4 expression in HCC tumor and peri-tumor tissues provided by Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) datasets. (b,c) C8orf4 expression levels were verified in HCC patient samples by quantitative RT–PCR (qRT–PCR) (b) and immunoblotting (c). β-actin served as a loading control. 18S: 18S rRNA. (d) HCC samples were assayed by immunohistochemical staining. Scale bar—left: 50 μm; right: 20 μm. (eC8orf4 is weakly expressed in CD13+CD133+ cells sorted from Huh7 cells and primary HCC samples. C8orf4 messenger RNA (mRNA) was measured by qRT–PCR. Six HCC samples got similar results. (fC8orf4 is much more weakly expressed in oncospheres than non-sphere tumor cells. Non-sphere: Huh7 or HCC primary cells that failed to form spheres. (g) HCC sample tissues were co-stained with anti-C8orf4 and anti-CD13 or anti-CD133 antibodies, then counterstained with DAPI for confocal microscopy. White arrows indicate CD13+ or CD133+ cells. Scale bars: 20 μm. For a,b, data are shown as box and whisker plot. Boxes represent interquartile range (IQR); upper and lower edge corresponds to the 75th and 25th percentiles, respectively. Horizontal lines within boxes represent median levels of gene intensity. Whiskers below and above boxes extend to the 5th and 95th percentiles, respectively. For e and f, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. P, peri-tumor; T, tumor.

 

Notably, C8orf4 was also weakly expressed in embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) by analysis of its expression profiles derived from online datasets (GSE14897; ref. 25 and GSE25417; ref. 26) (Supplementary Fig. 1a,b). C8orf4 was also lowly expressed in normal liver stem cells (Supplementary Fig. 1c,d), suggesting that C8orf4 may be involved in the regulation of self-renewal of liver stem cells. Thus, we propose that C8orf4 might play a role in the maintenance of liver CSCs. Since CD13 and CD133 were widely used as liver CSC surface markers, we sorted CD13+CD133+ cells from Huh7 and Hep3B HCC cell lines as well as HCC samples, serving as liver CSCs. We observed that C8orf4 was weakly expressed in liver CSCs enriched from both HCC cell lines and patient samples (Fig. 1e). Six HCC samples were analyzed for these experiments. Similar results were obtained in CD13+CD133+ cells from Hep3B cells. Furthermore, we performed sphere formation experiments using Huh7 cells and HCC primary sample cells, and detected expression levels of C8orf4. We observed that C8orf4 was dramatically reduced in the oncospheres generated by both HCC cell lines and patient samples (Fig. 1f). In addition, we noticed that C8orf4 expression was negatively correlated with liver CSC markers such as CD13 and CD133 in HCC samples (Fig. 1g), suggesting lower expression of C8orf4 in liver CSCs. Moreover, C8orf4 was mainly located in the cytoplasm of tumour cells. Altogether, C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs.

C8orf4 negatively regulates self-renewal of liver CSCs

We then wanted to look at whether C8orf4 plays a critical role in the self-renewal maintenance of liver CSCs. C8orf4 was knocked out in Huh7 cells through a CRISPR/Cas9 system (Fig. 2a). TwoC8orf4-knockout (KO) cell strains were established and C8orf4 was completely deleted in these two strains. C8orf4 deletion dramatically enhanced oncosphere formation (Fig. 2b). We co-stained SOX9, a widely used progenitor marker, and Ki67, a well-known proliferation marker, in C8orf4 KO sphere cells. We found that SOX9 was strongly stained in C8orf4 KO sphere cells (Supplementary Fig. 2a). In contrast, Ki67 staining was not significantly altered in C8orf4 KO sphere cells versus WT sphere cells. We also digested sphere cells and examined the SOX9 and Ki67 expression by flow cytometry. Similar results were achieved (Supplementary Fig. 2b). Importantly, through serial passage of CSC sphere cells, similar observations were obtained in the fourth generation oncosphere assay (Supplementary Fig. 2c,d). These data suggest that C8orf4 is involved in the regulation of liver CSC self-renewal.

(not shown)

Figure 2: C8orf4 knockout enhances self-renewal of liver CSCs.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f2.jpg

  • C8orf4-deficient Huh7 cells were established using a CRISPR/Cas9 system. T7 endonuclease I cleavage confirmed the efficiency of sgRNA (left panel, white arrowheads), and C8orf4-knockout efficiency was confirmed by western blot (right panel). Two knockout cell lines were used.  C8KO#1:C8orf4KO#1;  C8KO#2C8orf4KO#2. (bC8orf4-deficient cells enhanced sphere formation activity. Calculated ratios are shown in the right panel. (cC8orf4-deficient or WT Huh7 cells (1 × 106) were injected into BALB/c nude mice. Tumor sizes were observed every 5 days. (dC8orf4 deficiency enhances tumor-initiating capacity. Diluted cell numbers of Huh7 cells were implanted into BALB/c nude mice for tumor initiation. Percentages of tumor-formation mice were calculated (left panel), and frequency of tumor-initiating cells was calculated using extreme limiting dilution analysis (right panel). Error bars represent the 95% confidence intervals of the estimation. (e) Expression levels of CD13 andCD133 were analyzed in C8orf4-knockout Huh7 cells. (f) C8orf4 was silenced in HCC primary cells and C8orf4 depletion enhanced sphere formation activity. Calculated ratios are shown at the right panel. Three HCC specimens obtained similar results. (g) C8orf4-overexpressing Huh7 cells were established (left panel). C8orf4-overexpressing Huh7 cells and control Huh7 cells were cultured for sphere formation. (h,i) Xenograft tumor growth (h) and frequency of tumor-initiating cells (i) for C8orf4-overexpressing Huh7 cells were analyzed as c,d. (j) C8orf4 overexpression reduces expression of CD133 and CD13 in Huh7 cells. (k) C8orf4 was transfected in HCC primary cells and cultured for sphere formation. Three HCC patient samples obtained similar results. Scale bars: b,f,g,k, 500 μm. Student’s t-test was used for statistical analysis,    *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data represent at least three independent experiments. oeC8orf4, overexpression of C8orf4; oeVec, overexpression vector.

In addition, C8orf4-deficient Huh7 cells overtly increased xenograft tumour growth (Fig. 2c). We then performed sphere formation and digested oncospheres formed by C8orf4-deficient or WT cells into single-cell suspension, then subcutaneously implanted 1 × 104, 1 × 103, 1 × 102 and 10 cells into BALB/c nude mice. Tumour formation was examined for tumour-initiating capacity at the third month. C8orf4 deficiency remarkably enhanced tumour-initiating capacity and liver CSC ratios (Fig. 2d). In addition, C8orf4 deletion significantly enhanced expression levels of the liver CSC markers such as CD13 and CD133 (Fig. 2e). We also silenced C8orf4 in HCC primary cells using a lentivirus infection system and established C8orf4-silenced cells. Two pairs of short hairpin RNA (shRNA) sequences obtained similar knockdown efficiency. C8orf4 knockdown remarkably promoted sphere formation and xenograft tumour growth (Fig. 2f and Supplementary Fig. 2e). These data indicate that C8orf4 deletion potentiates the self-renewal of liver CSCs.
We next overexpressed C8orf4 in Huh7 cells and HCC primary cells using lentivirus infection. We observed that C8orf4 overexpression in Huh7 cells remarkably reduced sphere formation and xenograft tumour growth (Fig. 2g,h). In addition, C8orf4 overexpression remarkably reduced tumour-initiating capacity and expression of liver CSC markers (Fig. 2i,j). Similar results were observed by C8orf4 overexpression in HCC primary cells (Fig. 2k). We tested three HCC samples with similar results. Overall, C8orf4 negatively regulates the maintenance of liver CSC self-renewal and tumour propagation.

C8orf4 suppresses NOTCH2 signaling in liver CSCs

To further determine the underlying mechanism of C8orf4 in the regulation of liver CSCs, we analyzed three major self-renewal signaling pathways, including Wnt/β-catenin, Hedgehog and NOTCH pathways, in C8orf4-deleted Huh7 cells and HCC primary cells. We found that only NOTCH target genes were remarkably upregulated in C8orf4-deficient cells (Fig. 3a), whereasC8orf4 deficiency did not significantly affect the Wnt/β-catenin or the Hedgehog pathway. Given that the NOTCH family receptors have four members, we wanted to determine which NOTCH member was involved in the C8orf4-mediated suppression of liver CSC stemness. We noticed that only NOTCH2 was highly expressed in both Huh7 cells and HCC samples (Fig. 3b). In addition, this result was also confirmed by analysis of NOTCH expression levels derived from Wang’s cohort (GSE14520) and Petel’s cohort (E-TABM-36; ref. 27) (Fig. 3c). Moreover, we analysed expression profiles of C8orf4 and NOTCH target genes using Park’s cohort (GSE36376) and Wurmbach’s cohort (GSE6764; ref. 28). These cohort datasets provided several Notch signaling and its target genes. HEY1NRARP and HES6 genes were highly expressed in HCC tumour tissues (GSE6764; ref. 28), which were further confirmed in HCC samples by real-time PCR (Supplementary Fig. 3a,b). Furthermore, HEY1NRARP and HES6 genes have been reported to be relatively specific NOTCH target genes. We then examined these three genes as the NOTCH2 target genes throughout this study. We found that the C8orf4 expression level was negatively correlated with the expression levels of HEY1 and HES6, suggesting that C8orf4 inhibited NOTCH signaling in HCC patients (Fig. 3d). Finally these results were further confirmed in HCC samples by qRT-PCR (Fig. 3e). To further explore the activation status of NOTCH2 signaling in liver CSCs, we examined the expression levels of NOTCH downstream target genes in oncospheres and CD13+CD133+ cells derived from both Huh7 cells and HCC cells. We observed that NOTCH target genes were highly expressed in liver CSCs (Fig. 3f,g). These observations were verified by immunoblotting (Fig. 3h). In addition, the expression levels of NRARPHES6 and HEY1 were positively related to the expression levels of EpCAM and CD133 derived from Zhang’s cohort (GSE25097; ref. 29) and Wang’s cohort (GSE14520; Supplementary Fig. 3c,d). These data suggest that the NOTCH2 signaling plays a critical role in the maintenance of self-renewal of liver CSCs.

(not shown)

Figure 3: C8orf4 suppresses NOTCH2 signaling in liver CSCs.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f3.jpg

(aC8orf4 deficiency or depletion activates NOTCH signaling. The indicated major stemness signalling pathways were analysed in C8orf4-knockout Huh7 cells (left panel) and C8orf4-silenced primary cells of HCC samples (right panel). (b) Four receptor members of NOTCH family were examined in both Huh7 cells (left panel) and 29 pairs of HCC samples (right panel). (cNOTCH receptors were analyzed from Wang’s cohort (left panel) and Petel’s cohort (right panel) datasets. (dHEY1 and HES6 were highly expressed in C8orf4low samples by analysis of Park’s cohort (upper panel) and Wurmbach’s cohort (lower panel). (e) Expression levels of HEY1 and HES6 along with C8orf4 were analysed in HCC samples by qRT–PCR. (f,g) Expression levels of NRARPHEY1 and HES6 in spheres generated by Huh7 cells and HCC primary cells (f) and in CD13+CD133+ cells sorted from Huh7 cells and HCC primary cells (g). Non-sphere: Huh7 cells or HCC cells that failed to form spheres. (h) HEY1, HES6 and NRARP expression in sphere and non-sphere cells was detected by immunoblotting. β-actin was used as a loading control. For c,d, data are shown as box and whisker plot. Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For a,b,f,g, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.

C8orf4 interacts with NOTCH2 that is critical for liver CSCs

On ligand–receptor binding, the NOTCH receptor experiences a proteolytic cleavage by metalloprotease and γ-secretase, releasing a NOTCH extracellular domain (NECD) and a NOTCH intracellular domain (NICD), respectively30. Then the active NICD undergoes nuclear translocation and activates the expression of NOTCH downstream target genes31.Then we constructed the NOTCH2 extracellular domain (N2ECD) and intracellular domain (N2ICD) and examined the interaction with C8orf4 via a yeast two-hybrid approach. Interestingly, we found that C8orf4 interacted with N2ICD, but not N2ECD (Fig. 4a). The interaction was validated by co-immunoprecipitation (Fig. 4b). Through domain mapping, the ankyrin repeat domain of NOTCH2 was essential and sufficient for its association with C8orf4 (Fig. 4c). Taken together, C8orf4 interacts with the N2ICD domain of NOTCH2.

Figure 4: C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs.

C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs

C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f4.jpg

(a) C8orf4 interacts with N2ICD. Yeast strain AH109 was co-transfected with Gal4 DNA-binding domain (BD) fused C8orf4 and Gal4-activating domain (AD) fused N2ICD. p53 and large T antigen were used as a positive control. (b) Recombinant Flag-N2ICD and GFP–C8orf4 were incubated for co-immunoprecipitation. (c) The ankyrin repeat AR domain is essential and sufficient for the interaction of C8orf4 with N2ICD. Various N2ICD truncation constructs were co-transfected with GFP–C8orf4 for domain mapping. NLS: nuclear location signal. (d) NOTCH2 was knocked down in Huh7 cells and detected by qRT–PCR and immunoblotting. (e) NOTCH2-silenced Huh7 cells were cultured for sphere formation assays. Two pairs of shRNAs against NOTCH2 obtained similar results. (f,g) Xenograft tumor growth (f) and frequency of tumor-initiating cells (g) for NOTCH2-silenced Huh7 cells were analyzed. (h) NOTCH2 was silenced in HCC primary cells and NOTCH2 depletion declined sphere formation activity. Three HCC specimens obtained similar results. (i) Sphere formation capacity was examined in differently treated HCC primary cells. (j) HCC primary cells were treated with indicated lentivirus and implanted into BALB/c nude mice for xenograft tumor growth assays. Scale bars: e,h,i, 500 μm, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. IB, immunoblotting; IP, immunoprecipitation; NS, not significant.

To further verify the role of NOTCH2 in the maintenance of liver CSC self-renewal, we knocked down NOTCH2 in Huh7 cells and established stably depleted cell lines by two pairs of NOTCH2 shRNAs (Fig. 4d). NOTCH2 knockdown dramatically reduced sphere formation (Fig. 4e), as well as attenuated xenograft tumor growth and tumor-initiating capacity (Fig. 4f,g). Similar observations were achieved in NOTCH2-depleted HCC primary cells (Fig. 4h). In addition, we found that simultaneous knockdown of NOTCH2 and overexpression of C8orf4 failed to reduce sphere formation capacity compared with individual knockdown of NOTCH2 (Fig. 4i), suggesting that NOTCH2 and C8orf4 affected sphere formation through the same pathway. Meanwhile, C8orf4 knockdown failed to rescue the sphere formation ability of NOTCH2-depleted HCC primary cells (Fig. 4i). Similar observations were obtained in Huh7 cells (Supplementary Fig. 4). Finally, NOTCH2 depletion in C8orf4-silenced Huh7 cells or HCC primary cells also abrogated the C8orf4 depletion-mediated enhancement of xenograft tumor growth (Fig. 4j), suggesting that C8orf4 acted as upstream of NOTCH2 signaling. These data suggest that C8orf4 suppresses the liver CSC stemness through inhibiting the NOTCH2 signaling pathway.

C8orf4 blocks nuclear translocation of N2ICD

As shown in Fig. 1g, C8orf4 was mainly localized in the cytoplasm in tumor cells of HCC samples. To confirm these observations, we stained C8orf4 in several HCC cell lines and noticed that C8orf4 also resided in the cytoplasm of Huh7 cells and Hep3B cells (Fig. 5a and Supplementary Fig. 5a). These results were further validated by cellular fractionation (Fig. 5b). Importantly, C8orf4 KO led to nuclear translocation of N2ICD (Fig. 5c). In addition, we also examined the intracellular location of N2ICD in Huh7 spheres. We found that C8orf4 deletion caused complete nuclear translocation of N2ICD in oncosphere cells (Fig. 5d,e), while N2ICD was mainly located in the cytoplasm of WT oncosphere cells. However, we found that C8orf4 KO did not affect subcellular localization of β-catenin (Supplementary Fig. 5b,c). Through luciferase assays, C8orf4 transfection did not significantly influence promoter transcription activity of Wnt target genes such as TCF1, LEF and SOX4 (Supplementary Fig. 5d). These data indicate that C8orf4 resides in the cytoplasm of HCC cells and inhibits nuclear translocation of N2ICD.

C8orf4 deletion causes the nuclear translocation of N2ICD

C8orf4 deletion causes the nuclear translocation of N2ICD

Figure 5: C8orf4 deletion causes the nuclear translocation of N2ICD.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f5.jpg

(a) C8orf4 resides in the cytoplasm of Huh7 cells. Huh7 cells were permeabilized and stained with anti-C8orf4 antibody, then counterstained with PI for confocal microscopy. (b) Cellular fractionation was performed and detected by immunoblotting. (c,d) C8orf4 knockout causes the nuclear translocation of N2ICD. C8orf4-deficient Huh7 cells (c) and sphere cells (d) were permeabilized and stained with anti-C8orf4 and anti-N2ICD antibodies, then counterstained with DAPI followed by confocal microscopy. (e) Cellular fractionation was performed in C8orf4-deficient sphere and WT sphere cells followed by immunoblotting. (f) C8orf4-deficient Huh7 cells were implanted into BALB/c nude mice. Xenograft tumors were analyzed by immunohistochemical staining. Red arrowheads denote nuclear translocation of N2ICD. (g) C8orf4-overexpressing Huh7 cells were permeabilized for immunofluorescence staining. (h) Cellular fractionation was performed in C8orf4-overexpressing Huh7 cells for immunoblotting. (i,j) C8orf4 was overexpressed in N2ICD-overexpressing Huh7 cells followed by immunofluorescence staining (i) and immunoblotting (j). (k) NOTCH target genes were measured in cells treated as in i by real-time PCR. Scale bars: a,c,d,g,i, 10 μm; f, 40 μm. Student’s t-test was used for statistical analysis, **P<0.01;***P<0.001, data are shown as mean±s.d.. Data represent at least three independent experiments.

To further determine whether C8orf4 inhibits the NOTCH2 signaling in the propagation of xenograft tumors, we examined the distribution of N2ICD and NOTCH2 target gene activation inC8orf4-deficient xenograft tumor tissues. We found that C8orf4-deficient tumors displayed much more nuclear translocation of N2ICD compared with WT tumors (Fig. 5f). Expectedly, C8orf4-deficient tumors showed elevated expression levels of NOTCH2 target genes such as HEY1, HES6 and NRARP (Supplementary Fig. 5e). Furthermore, C8orf4 overexpression blocked the nuclear translocation of N2ICD (Fig. 5g,h). Consequently, C8orf4-overexpressing tumors showed much less N2ICD nuclear translocation and reduced expression levels of NOTCH2 target genes compared with control tumors (Supplementary Fig. 5f,g). Of note, C8orf4 overexpression in N2ICD-overexpressing Huh7 cells still blocked nuclear translocation of N2ICD (Fig. 5i,j). Consequently, C8orf4 overexpression abolished the activation of Notch2 signaling (Fig. 5k). These results suggest that C8orf4 deletion causes the nuclear translocation of N2ICD leading to activation of NOTCH2 signaling.

NOTCH2 signalling is required for the stemness of liver CSCs

To further verify the role of NRARP and HEY1 in the maintenance of liver CSC self-renewal, we knocked down these two genes in Huh7 cells and established stably depleted cell lines by two pairs of shRNAs. As expected, NRARP knockdown dramatically reduced sphere formation (Fig. 6a,b). NRARP knockdown also attenuated tumor-initiating capacity and liver CSC ratios (Fig. 6c). Similar results were achieved in NRARP-silenced HCC primary cells (Fig. 6d,e). Similarly, HEY1 silencing remarkably reduced sphere formation derived from Huh7 and HCC primary cells (Fig. 6f–i), as well as declined xenograft tumor growth and tumor-initiating capacity (Supplementary Fig. 6a,b). In sum, NOTCH2 signaling is required for the maintenance of liver CSC self-renewal.

(not shown)

Figure 6: Depletion of NRARP and HEY1 impairs stemness of liver CSCs.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f6.jpg

(a,b) NRARP-silenced Huh7 cells were established (a) and showed reduced sphere formation capacity (b). Two pairs of shRNAs against NRARP obtained similar results. (c) NRARP-silenced Huh7 cells decline tumour-initiating capacity (left panel) and reduce liver CSC frequency (right panel). Error bars represent the 95% confidence intervals of the estimation. (d,e) NRARP was knocked down in HCC primary cells (d) and sphere formation was detected (e). Three HCC samples were tested with similar results. (f,g) HEY1-silenced Huh7 cells were established (f) and sphere formation was assayed (g). Two pairs of shRNAs against HEY1 obtained similar results. (h,i) HEY1 was knocked down in HCC primary cells (h) and HEY1 depletion impaired sphere formation capacity (i). Three HCC samples were tested with similar results. Scale bars: b,e,g,i, 500 μm. For a,b,di, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01;  ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.

NOTCH2 signaling is correlated with HCC severity

As shown above, the NOTCH2 signaling was highly activated in liver CSCs and involved in the regulation of liver CSC stemness. We further examined the relationship of NOTCH2 signaling with the progression of HCC. First, we analyzed NOTCH2 activation levels in HCC tumor tissues and peri-tumor tissues derived from Park’s cohort (GSE36376). We observed that HEY1HES6 and NRARP were highly expressed in the tumor tissues of HCC patients (Fig. 7a). Consistently, high expression levels of HEY1HES6 and NRARP in HCC tumors were validated by Zhang’s cohort (GSE25097) (Fig. 7b). Importantly, high expression of these three genes was confirmed in HCC samples through quantitative RT–PCR (Fig. 7c), as well as immunoblotting (Fig. 7d). To confirm a causative link between low C8orf4 expression level and nuclear N2ICD, we examined 93 HCC samples (31 peri-tumor, 37 early stage of HCC patients and 25 advanced stage of HCC patients) with immunohistochemistry staining. We observed that nuclear staining of N2ICD appeared in ~10% tumor cells in the majority of early HCC patients we tested (Fig. 7e,f). In advanced HCC patients, nuclear staining of N2ICD in tumor cells increased to ~30% in almost all the advanced HCC patients we examined. Consequently, HEY1 staining existed in ~10% tumor cells with scattered distribution and increased to 30% tumor cells in the advanced HCC patients (Fig. 7e). Consistently, low expression of C8orf4 was well correlated with activation of NOTCH2 signaling (Fig. 7e,f).

NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients

NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients

Figure 7: NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f7.jpg

(a,b) NOTCH target genes were highly expressed in HCC tumour tissues derived from Park’s cohort (a) and Zhang’s cohort (b). (c) High expression levels of NOTCH target genes in HCC tumor tissues were verified by qRT–PCR. (d) HEY1 expression in HCC tumor tissues was detected by western blot. (e) IHC staining for N2ICD, C8orf4 and HEY1. These images represent 93 HCC samples. Scale bars, 50 μm. (f) IHC images were calculated using Image-Pro Plus 6. (g) Expression levels of NOTCH target genes were elevated in HCC tumors and advanced HCC patients derived from Wang’s cohort. (hHEY1 expression level was positively correlated with prognosis prediction of HCC patients analyzed by Petel’s cohort and Wang’s cohort. HCC samples were divided into two groups according to HEY1 expression levels followed by Kaplan–Meier survival analysis. For ac, data are shown as box and whisker plot, Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For f,g, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001; data are shown as mean ± standard deviation. Experiments were repeated at least three times. aHCC, advanced HCC; CL, cirrhosis liver; eHCC, early HCC; IL, inflammatory liver; NL, normal liver; NS, not significant.

Serial passages of colonies or sphere formation in vitro, as well as transplantation of tumor cells, are frequently used to assess the long-term self-renewal capacities of CSCs32. We used HCC primary cells for serial passage growth in vitro and tested the expression levels of C8orf4HEY1 and SOX9. We found that C8orf4 expression was gradually reduced over serial passages in oncosphere cells (Supplementary Fig. 7a). Consequently, the expression of NOTCH2 targets such as HEY1 and SOX9 was gradually increased in oncosphere cells during serial passages (Supplementary Fig. 7b). In addition, N2ICD nuclear translocation appeared in oncosphere cells with high expression of HEY1 plus low expression of C8orf4 (termed as C8orf4/N2ICDnuc/HEY1+cells) (Supplementary Fig. 7c). These data suggest that the C8orf4/N2ICDnuc/HEY1+ fraction cells represent a subset of liver CSCs.

Through analyzing Wang’s cohort (GSE54238), we noticed that the NOTCH2 activation levels were positively correlated with the development and progression of HCC (Fig. 7g). By contrast, the NOTCH2 pathway was not activated in inflammation liver, cirrhosis liver and normal liver (Fig. 7f). Consistently, similar observations were achieved by analysis of Zhang’s cohort (GSE25097) (Supplementary Fig. 7d). In addition, the NOTCH2 activation levels were consistent with clinicopathological stages of HCC patients derived from Wang’s cohort (GSE14520) (Supplementary Fig. 7e). Finally, HCC patients with higher expression of HEY1 displayed worse prognosis derived from Petel’s cohort (E-TABM-36) and Wang’s cohort (GSE14520) (Fig. 7h). These two cohorts (E-TABM-36 and GSE14520) have survival information of HCC patients. Taken together, the NOTCH2 activation levels in tumor tissues are consistent with clinical severity and prognosis of HCC patients.

Discussion

CSC have been identified in many solid tumors, including breast, lung, brain, liver, colon, prostate and bladder cancers4633. CSCs have similar characteristics associated with normal tissue stem cells, including self-renewal, differentiation and the ability to form new tumors. CSCs may be responsible for cancer relapse and metastasis due to their invasive and drug-resistant capacities34. Thus, targeting CSCs may become a promising therapeutic strategy to deadly malignancies3536. However, it remains largely unknown about hepatic CSC biology. In this study, we used CD13 and CD133 to enrich CD13+CD133+
subpopulation cells as liver CSCs. Based on analysis of several online-available HCC transcriptome datasets, we found that C8orf4 is weakly expressed in HCC tumors as well as in CD13+CD133+ liver CSCs. NOTCH2 signaling is required for the maintenance of liver CSC self-renewal. C8orf4 resides in the cytoplasm of tumor cells and interacts with N2ICD, blocking the nuclear translocation of N2ICD. Lower expression of C8orf4 causes nuclear translocation of N2ICD that activates NOTCH2 signaling in liver CSCs. NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Therefore, C8orf4 negatively regulates self-renewal of liver CSCs via suppression of NOTCH2 signaling.

Elucidating signaling pathways that maintains self-renewal of liver CSCs is pivotal for the understanding of hepatic CSC biology and the development of novel therapies against HCC. Several signaling pathways, such as Wnt/β-catenin, transforming growth factor-beta, AKT and STAT3 pathways, have been defined to be implicated in the regulation of liver CSCs37. Not surprisingly, some liver CSC subsets and normal tissue stem cells may share core regulatory genes and common signaling pathways. The NOTCH signaling pathway plays an important role in development via cell-fate determination, proliferation and cell survival3839. The NOTCH family receptors contain four members in mammals (NOTCH1–4), which are activated by binding to their corresponding ligands. A large body of evidence provides that NOTCH signaling is implicated in carcinogenesis40. However, the role of NOTCH signaling in liver cancer is controversial. A previous study reported that NOTCH1 signaling suppresses tumor growth of HCC41. Recently, several reports showed that NOTCH signaling enhances liver tumor initiation424344. Importantly, a recent study showed that various NOTCH receptors have differential functions in the development of liver cancer45. Here we demonstrate that NOTCH2 signaling is activated in HCC tumor tissues and liver CSCs, which is required for the maintenance of liver CSC self-renewal.

C8orf4, also known as TC1, was originally cloned from a papillary thyroid cancer16, 46. The copy number variations of C8orf4 are associated with acute myeloid leukemia and other hematological malignancies19, 47. C8orf4 has been reported to be implicated in various cancers. C8orf4 was highly expressed in thyroid cancer, gastric cancer and breast cancer16, 20, 46. C8orf4 has been reported to enhance Wnt/β-catenin signaling in cancer cells that is associated with poor prognosis20, 21. However, C8orf4 is downregulated in colon cancer48. In this study, we show that C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs. Our observations were confirmed by two HCC cohort datasets. Importantly, C8orf4 negatively regulates the NOTCH2 signaling to suppress the self-renewal of liver CSCs. Therefore, C8orf4 may exert distinct functions in the regulation of various malignancies.

NOTCH receptors consist of noncovalently bound extracellular and transmembrane domains. Once binding with membrane-bound Delta or Jagged ligands, the NOTCH receptors undergoes a proteolytic step by metalloprotease and γ-secretase, generating NECD and NICD fragments11, 31. The NICD, a soluble fragment, is released in the cytoplasm on proteolysis. Then the NICD translocates to the nucleus and binds to the transcription initiation complex, leading to activation of NOTCH-associated target genes49. However, it is largely unclear how the NICD is regulated during NOTCH signaling activation. Here we show that N2ICD binds to C8orf4 in the cytoplasm of liver non-CSC tumor cells, which impedes the nuclear translocation of N2ICD. By contrast, in liver CSCs, lower expression of C8orf4 causes the nuclear translocation of N2ICD, leading to activation of NOTCH signaling.

CSCs or tumour-initiating cells, behave like tissue stem cells in that they are capable of self-renewal and of giving rise to hierarchical organization of heterogeneous cancer cells4. Thus, CSCs harbour the stem cell properties of self-renewal and differentiation. Actually, the CSC model cannot account for tumorigenesis in all tumours. CSCs could undergo genetic evolution, and the non-CSCs might switch to CSC-like cells4. These results highlight the dynamic nature of CSCs, suggesting that the clonal evolution and CSC models can act in concert for tumorigenesis. Furthermore, low C8orf4 expression in tumor cells results in overall Notch2 activation, which then may have more of a progenitor signature and be more aggressive. These cells would likely have a growth advantage in non-adherent conditions and express many of the stemness markers. The dynamic nature of CSCs or persistent NOTCH2 activation may contribute to the high number of C8orf4/N2ICDnuc/HEY1+ cells in advanced HCC tumors and correlation in the patient cohort.

A recent study showed that NOTCH2 and its ligand Jag1 are highly expressed in human HCC tumors, suggesting activation of NOTCH2 signaling in HCC45. In addition, inhibiting NOTCH2 or Jag1 dramatically reduces tumor burden and growth. However, suppression of NOTCH3 has no effect on tumor growth. Dill et al.43 reported that Notch2 is an oncogene in HCC. Notch2-driven HCC are poorly differentiated with a high expression level of the progenitor marker Sox9, indicating a critical role of Notch2 signaling in liver CSCs. Here we found that NOTCH2 and its target genes such as NRARP, HEY1 and HES6 are highly expressed in HCC samples. In addition, depletion of NRARP and HEY1 impairs the stemness maintenance of liver CSCs and tumor propagation. Moreover, the expression levels of NRARP, HEY1 and HES6 in tumors are positively correlated with clinical severity and prognosis of HCC patients. Finally, the NOTCH2 activation status is positively related to the clinicopathological stages of HCC patients. Altogether, C8orf4 and NOTCH2 signaling can be detected for the diagnosis and prognosis prediction of HCC patients, as well as used as targets for eradicating liver CSCs for future therapy.

11.2.3.2 Quantifying the Landscape for Development and Cancer from a Core Cancer Stem Cell Circuit

The authors developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. The landscape exhibits four basins of attraction, representing cancer stem cell, stem cell, cancer and normal cell states. They also uncovered certain key genes and regulations responsible for determining the switching between different states. [Cancer Res]

Chunhe Li and Jin Wang
Cancer Res May 13, 2015; 75(10).
http://dx.doi.org:/10.1158/0008-5472.CAN-15-0079

Cancer presents a serious threat to human health. The understanding of the cell fate determination during development and tumor genesis remains challenging in current cancer biology. It was suggested that cancer stem cell (CSC) may arise from normal stem cells, or be transformed from normal differentiated cells. This gives hints on the connection between cancer and development. However, the molecular mechanisms of these cell type transitions and the CSC formation remain elusive. We quantified landscape, dominant paths and switching rates between cell types from a core gene regulatory network for cancer and development. Stem cell, CSC, cancer, and normal cell types emerge as basins of attraction on associated landscape. The dominant paths quantify the transition processes among CSC, stem cell, normal cell and cancer cell attractors. Transition actions of the dominant paths are shown to be closely related to switching rates between cell types, but not always to the barriers in between, due to the presence of the curl flux. During the process of P53 gene activation, landscape topography changes gradually from a CSC attractor to a normal cell attractor. This confirms the roles of P53 of preventing the formation of CSC, through suppressing self-renewal and inducing differentiation. By global sensitivity analysis according to landscape topography and action, we identified key regulations determining cell type switchings and suggested testable predictions. From landscape view, the emergence of the CSCs and the associated switching to other cell types are the results of underlying interactions among cancer and developmental marker genes. This indicates that the cancer and development are intimately connected. This landscape and flux theoretical framework provides a quantitative way to understand the underlying mechanisms of CSC formation and interplay between cancer and development. Major Findings: We developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. Landscape exhibits four basins of attraction, representing CSC, stem cell, cancer and normal cell states. We quantified the kinetic rate and paths between different attractor states. We uncovered certain key genes and regulations responsible for determining the switching between different states.

11.2.3.3 IMP3 Promotes Stem-Like Properties in Triple-Negative Breast Cancer by Regulating SLUG

Scientists observed that insulin-like growth factor-2 mRNA binding protein 3 (IMP3) expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and demonstrated that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells. [Oncogene]

S Samanta, H Sun, H L Goel, B Pursell, C Chang, A Khan, et al.
Oncogene
 , (18 May 2015) |
http://dx.doi.org:/10.1038/onc.2015.164

IMP3 (insulin-like growth factor-2 mRNA binding protein 3) is an oncofetal protein whose expression is prognostic for poor outcome in several cancers. Although IMP3 is expressed preferentially in triple-negative breast cancer (TNBC), its function is poorly understood. We observed that IMP3 expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and we demonstrate that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells (CSCs). The mechanism by which IMP3 contributes to this phenotype involves its ability to induce the stem cell factor SOX2. IMP3 does not interact with SOX2 mRNA significantly or regulate SOX2 expression directly. We discovered that IMP3 binds avidly to SNAI2 (SLUG) mRNA and regulates its expression by binding to the 5′ UTR. This finding is significant because SLUG has been implicated in breast CSCs and TNBC. Moreover, we show that SOX2 is a transcriptional target of SLUG. These data establish a novel mechanism of breast tumor initiation involving IMP3 and they provide a rationale for its association with aggressive disease and poor outcome.

11.2.3.4 Type II Transglutaminase Stimulates Epidermal Cancer Stem Cell Epithelial-Mesenchymal Transition

Researchers investigated the role of type II transglutaminase (TG2) in regulating epithelial mesenchymal transition (EMT) in epidermal cancer stem cells. They showed that TG2 knockdown or treatment with TG2 inhibitor, resulted in a reduced EMT marker expression, and reduced cell migration and invasion. [Oncotarget]

ML Fisher, G Adhikary, W Xu, C Kerr, JW Keillor, RL Ecker
Oncotarget May 08, 2015;

Type II transglutaminase (TG2) is a multifunctional protein that has recently been implicated as having a role in ECS cell survival. In the present study we investigate the role of TG2 in regulating epithelial mesenchymal transition (EMT) in ECS cells. Our studies show that TG2 knockdown or treatment with TG2 inhibitor, results in a reduced EMT marker expression, and reduced cell migration and invasion. TG2 has several activities, but the most prominent are its transamidase and GTP binding activity. Analysis of a series of TG2 mutants reveals that TG2 GTP binding activity, but not the transamidase activity, is required for expression of EMT markers (Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α), and increased ECS cell invasion and migration. This coupled with reduced expression of E-cadherin. Additional studies indicate that NFϰB signaling, which has been implicated as mediating TG2 impact on EMT in breast cancer cells, is not involved in TG2 regulation of EMT in skin cancer. These studies suggest that TG2 is required for maintenance of ECS cell EMT, invasion and migration, and suggests that inhibiting TG2 GTP binding/G-protein related activity may reduce skin cancer tumor survival.

Epidermal squamous cell carcinoma (SCC) is among the most common cancers and the frequency is increasing at a rapid rate [1,2]. SCC is treated by surgical excision, but the rate of recurrence approaches 10% and the recurrent tumors are aggressive and difficult to treat [2]. We propose that human epidermal cancer stem (ECS) cells survive at the site of tumor excision, that these cells give rise to tumor regrowth, and that therapies targeted to kill ECS cells constitute a viable anti-cancer strategy. An important goal in this context is identifying and inhibiting activity of key proteins that are essential for ECS cell survival. Working towards this goal, we have developed systems for propagation of human ECS cells [3]. These cells display properties of cancer stem cells including self-renew and high level expression of stem cell marker proteins [3].

In the present study we demonstrate that ECS cells express proteins characteristic of cells undergoing EMT (epithelial-mesenchymal transition). EMT is a morphogenetic process whereby epithelial cells lose epithelial properties and assume mesenchymal characteristics [4]. The epithelial cells lose cell-cell contact and polarity, and assume a mesenchymal migratory phenotype. There are three types of EMT. This first is an embryonic process, during gastrulation, when the epithelial sheet gives rise to the mesoderm [5]. The second is a growth factor and cytokine-stimulated EMT that occurs at sites of tissue injury to facilitate wound repair [6]. The third is associated with epithelial cancer cell acquisition of a mesenchymal migratory/invasive phenotype. This process mimics normal EMT, but is not as well controlled and coordinated [478]. A number of transcription factors (ZEB1, ZEB2, snail, slug, and twist) that are expressed during EMT suppress expression of epithelial makers, including E-cadherin, desmoplakin and claudins [4]. Snail proteins also activate expression of vimentin, fibronectin and metalloproteinases [4]. Snail factors are not present in normal epithelial cells, but are present in the tumor cells and are prognostic factors for poor survival [4].

An important goal is identifying factors that provide overarching control of EMT in cancer stem cells. In this context, several recent papers implicate type II transglutaminase (TG2) as a regulator of EMT [912]. TG2, the best studied transglutaminase, was isolated in 1957 from guinea pig liver extract as an enzyme involved in the covalent crosslinks proteins via formation of isopeptide bonds [13]. However, subsequent studies reveal that TG2 also serves as a scaffolding protein, regulates cell adhesion, and modulates signal transduction as a GTP binding protein that participates in G protein signaling [14]. TG2 is markedly overexpressed in cancer cells, is involved in cancer development [1518], and has been implicated in maintaining and enhancing EMT in breast and ovarian cancer [10121920]. The G protein function may have an important role in these processes [102123].

In the present manuscript we study the role of TG2 in regulating EMT in human ECS cells. Our studies show that TG2 is highly enriched in ECS cells. We further show that these cells express EMT markers and that TG2 is required to maintain EMT protein expression. TG2 knockdown, or treatment with TG2 inhibitor, reduces EMT marker expression and ECS cell survival, invasion and migration. TG2 GTP binding activity is absolutely required for maintenance of EMT protein expression and EMT-related responses. However, in contrast to breast cancer [910], we show that TG2 regulation of EMT is not mediated via NFκB signaling.

TG2 is required for expression of EMT markers

EMT is a property of tumor stem cells that confers an ability to migrate and invade surrounding tissue [2426]. We first examined whether ECS cells express EMT markers. Non-stem cancer cells and ECS cells, derived from the SCC-13 cancer cell line, were analyzed for expression of EMT markers. Fig. 1A shows that a host of EMT transcriptional regulators, including Twist, Snail and Slug, are increased in ECS cells (spheroid) as compared to non-stem cancer cells (monolayer). This is associated with increased levels of vimentin, fibronectin and N-cadherin, which are mesenchymal proteins, and reduced expression of E-cadherin, an epithelial marker. HIF-1α, an additional marker frequently associated with EMT, is also elevated. We next examined whether TG2 is required to maintain EMT marker expression. SCC-13 cell-derived ECS cells were grown in the presence of control- or TG2-siRNA, to reduce TG2, and the impact on EMT marker level was measured. Fig. 1B shows that loss of TG2 is associated with reduced expression of Twist, Snail, vimentin and HIF-1α. To further assess the role of TG2, we utilized SCC13-Control-shRNA and SCC13-TG2-shRNA2 cell lines. These lines were produced by infection of SCC-13 cells with lentiviruses encoding control- or TG2-specific shRNA. Fig. 1C shows that SCC13-TG2-shRNA2 cells express markedly reduced levels of TG2 and that this is associated with reduced expression of EMT associated transcription factors and target proteins, and increased expression of E-cadherin. To confirm this, we grew SCC13-Control-shRNA and SCC13-TG2-shRNA2 cells as monolayer cultures for immunostain detection of EMT markers. As shown in Fig. 2A, TG2 levels are reduced in TG2-shRNA expressing cells, and this is associated with the anticipated changes in epithelial and mesenchymal marker expression.

Tumor cells that express EMT markers display enhanced migration and invasion ability [2426]. We therefore examined the impact of TG2 reduction on these responses. To measure invasion, control-shRNA and TG2-shRNA cells were monitored for ability to move through matrigel. Fig. 2B shows that loss of TG2 reduces movement through matrigel by 50%. We further show that this is associated with a reduction in cell migration using a monolayer culture wound closure assay. The control cells close the wound completely within 14 h, while TG2 knockdown reduces closure rate (Fig. 2C).

TG2 inhibitor reduces EMT marker expression and EMT functional responses

NC9 is a recently developed TG2-specific inhibitor [2728]. We therefore asked whether pharmacologic inhibition of TG2 suppresses EMT. SCC-13 cells were treated with 0 or 20 μM NC9. Fig. 3A shows that NC9 treatment reduces EMT transcription factor (Twist, Snail, Slug) and EMT marker (vimentin, fibronectin, N-cadherin, HIF-1α) levels. Consistent with these changes, the level of the epithelial marker, E-cadherin, is elevated. Fig. 3B and 3C show that pharmacologic inhibition of TG2 activity also reduces EMT biological response. Invasion (Fig. 3B) and cell migration (Fig. 3C) are also reduced.

Identification of TG2 functional domain required for EMT

We next performed studies to identify the functional domains and activities required for TG2 regulation of EMT. TG2 is a multifunctional enzyme that serves as a scaffolding protein, as a transamidase, as a kinase, and as a GTP binding protein [21]. The two best studied functions are the transamidase and GTP binding/G-protein related activities [21]. Transamidase activity is observed in the presence of elevated intracellular calcium, while GTP binding-related signaling is favored by low calcium conditions (reviewed in [21]). To identify the TG2 activity required for EMT, we measured the ability of wild-type and mutant TG2 to restore EMT in SCC13-TG2-shRNA2 cells, which have reduced TG2 expression (Fig. 4A). SCC13-TG2-shRNA2 cells display reduced expression of EMT markers including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α, and increased expression of the epithelial maker, E-cadherin, as compared to SCC13-Control-shRNA cells. Expression of wild-type TG2, or the TG2-C277S or TG2-W241A mutants, restores marker expression in SCC13-TG2-shRNA2 cells (Fig. 4A). TG2-C277S and TG2-W241A lack transamidase activity [10,2931]. In contrast, TG2-R580A, which lacks G-protein activity [2931], and TG2-Y516F, which retains only partial G-protein activity [30], do not efficiently restore marker expression. These findings suggest that the TG2 GTP binding function is required for EMT.

We next assayed the ability of the TG2 mutants to restore EMT functional responses-invasion and migration. Fig. 4B4C shows that wild-type TG2, TG2-C277S and TG2-W241A restore the ability of SCC13-TG2-shRNA2 cells to invade matrigel, but TG2-R580A and Y516F are less active. Fig. 4D shows a similar finding for cell migration, in that the TG2-R580A and Y517F mutant are only partially able to restore SCC13-TG2-shRNA2 cell migration. These findings suggest that TG2 GTP binding/G-protein related activity is required for EMT-related migration and invasion by skin cancer cells.

Role of TG2 in regulating EMT in A431 cells

The number of available epidermis-derived squamous cell carcinoma cell lines is limited, and so we compared our findings with A431 cells. A431 cells are squamous cell carcinoma cells established from human vulvar skin. A431 cells were grown as monolayer (non-stem cancer cells) and spheroids (ECS cells) and after 10 d the cells were harvested and assayed for expression of TG2 and EMT makers. Fig. 5A shows that TG2 levels are elevated in ECS cells and that this is associated with increased levels of mesenchymal markers, including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α. In contrast, E-cadherin levels are reduced. We next examined the impact of TG2 knockdown on EMT marker expression. Fig. 5B shows that mesenchymal markers are globally reduced and E-cadherin level is increased. As a biological endpoint of EMT, we examine the impact of TG2 knockdown on spheroid formation and found that TG2 loss leads to reduced spheroid formation (Fig. 5C). We next examined the impact of NC9 treatment on EMT and found a reduction in EMT markers expression associated with an increase in epithelial (E-cadherin) marker level (Fig. 5D). This loss of EMT marker expression is associated with reduced matrigel invasion (Fig. 5E), reduced spheroid formation (Fig. 5F) and reduced cell migration (Fig. 5G).

Role of NFκB

Previous studies in breast [183236], ovarian cancer [123738], and epidermoid carcinoma [11] indicate that NFκB signaling mediates TG2 impact on EMT. We therefore assessed the role of NFκB in skin cancer cells. As shown in Fig. 6A, the increase in TG2 level observed in ECS cells (spheroids) is associated with reduced NFκB level. In addition, NFκB level is increased in TG2 knockdown cells (Fig. 6B). Thus, increased NFκB is not associated with increased TG2. We next assessed the impact of NFκB knockdown on TG2 control of EMT marker expression. Fig. 6C shows that TG2 is required for increased expression of EMT markers (HIF-1α, snail, twist, N-cadherin, vimentin and fibronectin) and reduced expression of the E-cadherin epithelial marker; however, knockdown of NFκB expression does not interfere with TG2 regulation of these endpoints. We next examined the effect of TG2 knockdown on NFκB and IκBα localization. The fluorescence images in Fig. 6D suggest that TG2 knockdown with TG2-siRNA does not alter the intracellular localization of NFκB or IκBα. This is confirmed by subcellular fractionation assay (Fig. 6E) which compares NFκB level in SCC13-TG2-Control and SCC13-TG2-shRNA2 (TG2 knockdown) cells. We also monitored NFκB subcellular distribution following treatment with NC9, the TG2 inhibitor. Fig. 6F shows that cytoplasmic/nuclear distribution of NFκB is not altered by NC9. Finally, we monitored the impact of TG2 expression on NFκB binding to a canonical NFκB-response element. Increased NFκB binding to the response element is a direct measure of NFκB activity [10]. Fig. 6G shows that overall binding is reduced in nuclear (N) extract prepared from ECS cells (spheroids) as compared to non-stem cancer cells (monolayer), and that NFkB binding, as indicated by gel supershift assay, is also slightly reduced in ECS cell extracts. These findings indicate that NFkB binding is slightly reduced in ECS cells, which are TG2-enriched (Fig. 1A).

We next monitored the role of NFκB on biological endpoints of EMT. Fig. 7A and 7B show that TG2 knockdown reduces migration through matrigel, but NFκB knockdown has no impact. Likewise, TG2 knockdown reduces wound closure, but NFκB knockdown does not. These findings suggest that NFκB does not mediate the pro-EMT actions of TG2 in epidermal squamous cell carcinoma.

The metastatic cascade, from primary tumor to metastasis, is a complex process involving multiple pathways and signaling cascades [3941]. Cells that complete the metastatic cascade migrate away from the primary tumor through the blood to a distant site and there form a secondary tumor. Identifying the mechanisms that allow cells to survive this journey and form secondary tumors is an important goal. The processes involved in epithelial-mesenchymal transition (EMT) are important cancer therapy targets, as EMT is associated with enhanced cancer cell migration and stem cell self-renewal. EMT regulators, including Snail, Twist, Slug, are increased in expression in EMT and control expression of genes associated with the EMT phenotype [42].

TG2 is required for EMT

We have characterized a population of ECS cells derived from epidermal squamous cell carcinoma [3]. The present studies show that these cells, which display enhanced migration and invasion, possess elevated levels of TG2. Moreover, these cells are enriched in expression of transcription factors associated with EMT (Snail, Slug, and Twist, HIF-1α) as well as mesenchymal structural proteins including vimentin, fibronectin and N-cadherin. Consistent with a shift to mesenchymal phenotype, E-cadherin, an epithelial marker, is reduced in level. Additional studies show that TG2 knockdown results in a marked reduction in EMT marker expression and that this is associated with reduced ability of the cells to migrate to close a scratch wound and reduced movement in matrigel invasion assays. We also examined the impact of treatment with a TG2 inhibitor. NC9 is an irreversible active site inhibitor of TG2, that locks the enzyme in an open conformation [284345]. NC9 treatment of ECS cells results in decreased levels of Snail, Slug and Twist. These transcription factors suppress E-cadherin expression [46] and their decline in level is associated with increased levels of E-cadherin. NC9 inhibition of TG2 also reduces expression of vimentin, fibronectin and N-cadherin, and these changes are associated with reduced cell migration and reduced invasion through matrigel.

(Figures are not shown)

We also examined the role of TG2 in A431 squamous cell carcinoma cells derived from the vulva epithelium. TG2 is elevated in A431-derived ECS cells, as are EMT markers, and knockdown of TG2, with TG2-siRNA, reduces EMT marker expression and spheroid formation. Studies with NC9 indicate that NC9 inhibits A431 spheroid formation, EMT, migration and invasion. These studies indicate that TG2 is also required for EMT and migration and invasion in A431 cells. Based on these findings we conclude that TG2 is essential for EMT, migration and invasion, and is likely to contribute to metastasis in squamous cell carcinoma.

TG2 GTP binding activity is required for EMT

TG2 is a multifunctional enzyme that can act as a transamidase, GTP binding protein, protein disulfide isomerase, protein kinase, protein scaffold, and DNA hydrolase [21294447]. The two most studied functions are the transamidase and GTP binding functions [294447]. To identify the TG2 activity responsible for induction of EMT, we studied the ability of TG2 mutants to restore EMT in SCC13-TG2-shRNA2 cells, which express low levels of TG2 and do not express elevated levels of EMT markers or display EMT-related biological responses. These studies show that wild-type TG2 restores EMT marker expression and the ability of the cells to migrate on plastic and invade matrigel. TG2 mutants that retain GTP binding activity (TG2-C277S and TG2-W241A) also restore EMT. In contrast, TG2-R580A, which lacks GTP binding function, does not restore EMT. This evidence suggests that the GTP binding function is essential for TG2 induction of the EMT phenotype in ECS cells. Recent reports suggest that the TG2 is important for maintenance of stem cell survival in breast [91017] and ovarian [123848] cancer cells. Moreover, our findings are in agreement of those of Mehta and colleagues who reported that the TG2 GTP binding function, but not the crosslinking function, is required for TG2 induction of EMT in breast cancer cells [10].

TG2, NFκB signaling and EMT

To gain further insight into the mechanism of TG2 mediated EMT, we examined the role of NFκB. NFκB has been implicated as mediating EMT in breast, ovarian, and pancreatic cancer; however, NFκB may have a unique role in epidermal squamous cell carcinoma. In keratinocytes, NFκB has been implicated in keratinocyte dysplasia and hyperproliferation [49]. However, inhibition of NFκB function has also been shown to predispose murine epidermis to cancer [50]. Here we show that TG2 levels are elevated and NFκB levels are reduced in ECS cells as compared to non-stem cancer cells, and that TG2 knockdown is associated with increased NFκB level. In addition, TG2 knockdown, or inhibition of TG2 by treatment with NC9, does not altered the nuclear/cytoplasmic distribution of NFκB. We further show that elevated levels of TG2 in spheroid culture results in a slight reduction in NFκB binding to the NFκB response element, as measured by gel mobility supershift assay. These molecular assays strongly suggest that NFκB does not mediate the action of TG2 in epidermal cancer stem cells. Moreover, knockdown of NFκB-p65 in TG2 positive cells does not result in a reduction in Snail, Slug and Twist, or mesenchymal marker proteins expression, and concurrent knockdown of TG2 and NFκB does not reduce EMT marker protein levels beyond that of TG2 knockdown alone. These findings suggest that NFκB is not an intermediary in TG2-stimulated EMT in ECS cells. This is in contrast to the required role of NFκB in mediating TG2 induction of cell survival and EMT in breast cancer cells [183233] and ovarian cancer [123738] and epidermoid carcinoma [11].

11.2.3.5 CD24+ Ovarian Cancer Cells are Enriched for Cancer Initiating Cells and Dependent on JAK2 Signaling for Growth and Metastasis

Investigators showed that CD24+ and CD133+ cells have increased tumorsphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24– cells, had significantly greater tumor initiation and tumor growth capacity. [Mol Cancer Ther]

D Burgos-OjedaR Wu, K McLean, Yu-Chih Chen, M Talpaz, et al.
Molec Cancer Ther May 12, 2015; 14(5)
http://dx.doi.org:/10.1158/1535-7163.MCT-14-0607

Ovarian cancer is known to be composed of distinct populations of cancer cells, some of which demonstrate increased capacity for cancer initiation and/or metastasis. The study of human cancer cell populations is difficult due to long requirements for tumor growth, inter-patient variability and the need for tumor growth in immune-deficient mice. We therefore characterized the cancer initiation capacity of distinct cancer cell populations in a transgenic murine model of ovarian cancer. In this model, conditional deletion of Apc, Pten, and Trp53 in the ovarian surface epithelium (OSE) results in the generation of high grade metastatic ovarian carcinomas. Cell lines derived from these murine tumors express numerous putative stem cell markers including CD24, CD44, CD90, CD117, CD133 and ALDH. We show that CD24+ and CD133+ cells have increased tumor sphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24- cells, had significantly greater tumor initiation and tumor growth capacity. No preferential tumor initiating or growth capacity was observed for CD44+, CD90+, CD117+, or ALDH+ versus their negative counterparts. We have found that CD24+ cells, compared to CD24- cells, have increased phosphorylation of STAT3 and increased expression of STAT3 target Nanog and c-myc. JAK2 inhibition of STAT3 phosphorylation preferentially induced cytotoxicity in CD24+ cells. In vivo JAK2 inhibitor therapy dramatically reduced tumor metastases, and prolonged overall survival. These findings indicate that CD24+ cells play a role in tumor migration and metastasis and support JAK2 as a therapeutic target in ovarian cancer.

11.2.3.6 EpCAM-Antibody-Labeled Noncytotoxic Polymer Vesicles for Cancer Stem Cells-Targeted Delivery of Anticancer Drug and siRNA

Researchers designed and synthesized a novel anti-epithelial cell adhesion molecule (EpCAM)-monoclonal-antibody-labeled cancer stem cells (CSCs)-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA. [Biomacromolecules]

Jing Chen , Qiuming Liu , Jiangang Xiao , and Jianzhong Du
Biomacromolecules May 19, 2015. (just published)
http://dx.doi.org:/10.1021/acs.biomac.5b00551

Cancer stem cells (CSCs) have the capability to initiate tumor, to sustain tumor growth, to maintain the heterogeneity of tumor, and are closely linked to the failure of chemotherapy due to their self-renewal and multilineage differentiation capability with an innate resistance to cytotoxic agents. Herein, we designed and synthesized a novel anti-EpCAM (epithelial cell adhesion molecule)-monoclonal-antibody-labeled CSCs-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA (to overcome CSCs drug resistance by silencing the expression of oncogenes). This vesicle shows high delivery efficacy of both anticancer drug doxorubicin hydrochloride (DOX∙HCl) and siRNA to the CSCs because it is labeled by the monoclonal antibodies to the CSCs-surface-specific marker. Compared to non-CSCs-targeting vesicles, the DOX∙HCl or siRNA loaded CSCs-targeting vesicles exhibited much better CSCs killing and tumor growth inhibition capabilities with lower toxicity to normal cells (IC50,DOX decreased by 80%), demonstrating promising potential applications in nanomedicine.

11.2.3.7 Survival of Skin Cancer Stem Cells Requires the Ezh2 Polycomb Group Protein

Investigators showed that Ezh2 is required for epidermal cancer stem (ECS) cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. They also showed that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduced Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. [Carcinogenesis]

G Adhikary, D Grun, S Balasubramanian, C Kerr, J Huang and RL Eckert
Carcinogenesis (2015)
http://dx.doi.org:/10.1093/carcin/bgv064

Polycomb group (PcG) proteins, including Ezh2, are important candidate stem cell maintenance proteins in epidermal squamous cell carcinoma. We previously showed that epidermal cancer stem cells (ECS cells) represent a minority of cells in tumors, are highly enriched in Ezh2 and drive aggressive tumor formation. We now show that Ezh2 is required for ECS cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. We also show that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduces Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. These studies indicate that epidermal squamous cell carcinoma cells contain a subpopulation of cancer stem (tumor-initiating) cells that are enriched in Ezh2, that Ezh2 is required for optimal ECS cell survival and tumor formation, and that treatment with Ezh2 inhibitors may be a strategy for reducing epidermal cancer stem cell survival and suppressing tumor formation.

11.2.3.8 Inhibition of STAT3, FAK and Src mediated signaling reduces cancer stem cell load, tumorigenic potential and metastasis in breast cancer

R Thakur, R Trivedi, N Rastogi, M Singh & DP Mishra
Scientific Reports May 14, 2015; 5(10194)
http://dx.doi.org:/10.1038/srep10194

Cancer stem cells (CSCs) are responsible for aggressive tumor growth, metastasis and therapy resistance. In this study, we evaluated the effects of Shikonin (Shk) on breast cancer and found its anti-CSC potential. Shk treatment decreased the expression of various epithelial to mesenchymal transition (EMT) and CSC associated markers. Kinase profiling array and western blot analysis indicated that Shk inhibits STAT3, FAK and Src activation. Inhibition of these signaling proteins using standard inhibitors revealed that STAT3 inhibition affected CSCs properties more significantly than FAK or Src inhibition. We observed a significant decrease in cell migration upon FAK and Src inhibition and decrease in invasion upon inhibition of STAT3, FAK and Src. Combined inhibition of STAT3 with Src or FAK reduced the mammosphere formation, migration and invasion more significantly than the individual inhibitions. These observations indicated that the anti-breast cancer properties of Shk are due to its potential to inhibit multiple signaling proteins. Shk also reduced the activation and expression of STAT3, FAK and Src in vivo and reduced tumorigenicity, growth and metastasis of 4T1 cells. Collectively, this study underscores the translational relevance of using a single inhibitor (Shk) for compromising multiple tumor-associated signaling pathways to check cancer metastasis and stem cell load.

Breast cancer is the most common endocrine cancer and the second leading cause of cancer-related deaths in women. In spite of the diverse therapeutic regimens available for breast cancer treatment, development of chemo-resistance and disease relapse is constantly on the rise. The most common cause of disease relapse and chemo-resistance is attributed to the presence of stem cell like cells (or CSCs) in tumor tissues12. CSCs represent a small population within the tumor mass, capable of inducing independent tumors in vivo and are hard to eradicate2. Multiple signaling pathways including Receptor Tyrosine Kinase (RTKs), Wnt/β-catenin, TGF-β, STAT3, Integrin/FAK, Notch and Hedgehog signaling pathway helps in maintaining the stem cell programs in normal as well as in cancer cells3456. These pathways also support the epithelial-mesenchymal transition (EMT) and expression of various drug transporters in cancer cells. Cells undergoing EMT are known to acquire stem cell and chemo-resistant traits7. Thus, the induction of EMT programs, drug resistance and stem cell like properties are interlinked7. Commonly used anti-cancer drugs eradicate most of the tumor cells, but CSCs due to their robust survival mechanisms remain viable and lead to disease relapse8. Studies carried out on patient derived tumor samples and in vivo mouse models have demonstrated that the CSCs metastasize very efficiently than non-CSCs91011. Therefore, drugs capable of compromising CSCs proliferation and self-renewal are urgently required as the inhibition of CSC will induce the inhibition of tumor growth, chemo-resistance, metastasis and metastatic colonization in breast cancer.

Shikonin, a natural dietary component is a potent anti-cancer compound1213. Previous studies have shown that Shk inhibits the cancer cell growth, migration, invasion and tumorigenic potential12. Shk has good bioavailability, less toxicity and favorable pharmacokinetic and pharmacodynamic profiles in vivo12. In a recent report, it was shown that the prolonged exposure of Shk to cancer cells does not cause chemo-resistance13.Other studies have shown that it inhibits the expression of various key inflammatory cytokines and associated signaling pathways1214. It decreases the expression of TNFα, IL12, IL6, IL1β, IL2, IFNγ, inhibits ERK1/2 and JNK signaling and reduces the expression of NFκB and STAT3 transcription factors1415. It inhibits proteasome and also modulates the cancer cell metabolism by inhibiting tumor specific pyurvate kinase-M214,1516. Skh causes cell cycle arrest and induces necroptosis in various cancer types14. Shk also inhibits the expression of MMP9, integrin β1 and decreases invasive potential of cancer cells1417. Collectively, Shk modulates various signaling pathways and elicits anti-cancer responses in a variety of cancer types.

In breast cancer, Shk has been reported to induce the cell death and inhibit cell migration, but the mechanisms responsible for its effect are not well studied1819. Signaling pathways modulated by Shk in cancerous and non-cancerous models have previously been shown important for breast cancer growth, metastasis and tumorigenicity20. Therefore in the current study, we investigated the effect of Shk on various hallmark associated properties of breast cancer cells, including migration, invasion, clonogenicity, cancer stem cell load and in vivo tumor growth and metastasis.

Shk inhibits cancer hallmarks in breast cancer cell lines and primary cells

We first examined the effect of Shk on various cancer hallmark capabilities (proliferation, invasion, migration, colony and mammosphere forming potential) in breast cancer cells. MTT assay was used to find out effect of Shk on viability of breast cancer cells. Semi-confluent cultures were exposed to various concentrations of Shk for 24 h. Shk showed specific anti-breast cancer activity with IC50 values ranging from 1.38 μM to 8.3 μM in MDA-MB 231, MDA-MB 468, BT-20, MCF7, T47D, SK-BR-3 and 4T1 cells (Fig. 1A). Whereas the IC50 values in non-cancerous HEK-293 and human PBMCs were significantly higher indicating that it is relatively safe for normal cells (Fig. S1A). Shk was found to induce necroptotic cell death consistent with previous reports (Fig. S1B). Treatment of breast cancer cells for 24 h with 1.25 μM, 2.5 μM and 5.0 μM of Shk significantly reduced their colony forming potential (Fig. 1B). To check the effect of Shk on the heterogeneous cancer cell population, we tested it on patient derived primary breast cancer cells. Shk reduced the viability and colony forming potential of primary breast cancer cells in dose dependent manner (Fig. 1C,D). Further we checked its effects on migration and invasion of breast cancer cells. Shk (2.5 μM) significantly inhibited the migration of MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cells (Fig. 1E). It also inhibited the cell invasion in dose dependent manner (Fig. 1F and S1CS1DS1E,S1F). We further examined its effect on mammosphere formation. MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cell mammosphere cultures were grown in presence or absence of 1.25 μM, 2.5 μM and 5.0 μM Shk for 24 h. After 8 days of culture, a dose dependent decrease in the mammosphere forming potential of these cells was observed (Figs. 1G,H). Collectively, these results indicated that Shk effectively inhibits the various hallmarks associated with aggressive breast cancer.

(not shown)

Figure 1: Shk inhibits multiple cancer hallmarks

Shk reduces cancer stem cell load in breast cancer

As Shk exhibited strong anti-mammosphere forming potential; therefore it was further examined for its anti-cancer stem cell (CSC) properties. Cancer stem cell loads in breast cancer cells were assessed using Aldefluor assay which measures ALDH1 expression. MDA-MB 231 cells with the highest number of ALDH1+ cells were selected for further studies (Fig. S2A). We also checked the correlation between ALDH1 expression and mammosphere formation. Sorted ALDH1+ cells were subjected to mammosphere cultures. ALDH1+ cells formed highest number of mammospheres compared to ALDH1-/low and parent cell population, indicating that ALDH1+ cells are enriched in CSCs (Fig. S2B). Shk reduced the Aldefluor positive cells in MDA-MB 231 cells after 24 h of treatment (Fig. 2A,B). Next, we examined the effect of Shk on the expression of stem cell (Sox2, Oct3/4, Nanog, AldhA1 and c-Myc) and EMT (Snail, Slug, ZEB1, Twist, β-Catenin) markers, associated with the sustenance of breast CSCs. Shk (2.5 μM) treatment for 24 h reduced the expression of these markers (Fig. 2C and S2D). Shk also reduced protein expression of these markers in dose dependent manner (Fig. 2D,E and S2C).

(not shown)

Figure 2: Shk decreases stem cell load in breast cancer cells and enriched CD44+,CD24−/low breast cancer stem cells.

To further confirm anti-CSC properties of Shk, we checked the effect of shikonin on the load of CD44+ CD24− breast CSCs in MCF7 cells grown on matrigel. Shikonin reduced CD44+ CD24− cell load in dose dependent manner after 24 h of treatment (Fig S2E). We also tested its effects on the enriched CSC population. CD44+ CD24− cells were enriched from MCF7 cells using MagCellect CD24− CD44+ Breast CSC Isolation Kit (Fig. S2F). Enriched CSCs formed highest number of mammosphere in comparison to parent MCF7 cell population or negatively selected CD24+ cells (Fig. S2G). Enriched CSCs were treated with indicated doses of Shk (0.625 μM, 1.25 μM and 2.5 μM) for 24 h and were either analyzed for ALDH1 positivity or subjected to colony or mammosphere formation. 2.5 μM dose of Shk reduced ALDH1+ cells by 50% and inhibited colony and mammosphere formation (Fig. S2H2F2G and 2H). Shk also reduced the mRNA expression of CSC markers in CD44+ CD24− cells and patient derived primary cancer cells (Fig. 2I,J). These results collectively indicated that Shk inhibits CSC load and associated programs in breast cancer.

Shk is a potent inhibitor of STAT3 and poorly inhibits FAK and Src

To identify the molecular mechanism responsible for anti-cancer properties of Shk, we used a human phospho-kinase antibody array to study a subset of phosphorylation events in MDA-MB 231 cells after 6h of treatment with 2.5 μM Shk. Amongst the 46 phospho-antibodies spotted on the array, the relative extent of phosphorylation of three proteins decreased to about ≳ 2 fold (STAT3, 3.3 fold; FAK, 2.5 fold and Src, 1.8 fold) upon Shk treatment (Fig. 3A,B). These proteins (STAT3, FAK and Src) are known to regulate CSC proliferation and self renewal212223. Therefore, we focused on these proteins and the result of kinase-array was confirmed by western blotting. Shk effectively inhibits STAT3 at early time point (1 h) while activation of FAK and Src decreased on or after 3 h (Fig. 3C) confirming Shk as a potent inhibitor of STAT3. Shk also reduced the protein expression of STAT3, FAK and Src at 24 h (Fig. 3C).

(not shown)

Figure 3. Shk inhibits STAT3, FAK and Src signaling pathways.

We also observed that Shk does not inhibit JAK2 at initial time-points (Fig. 3C). This raised a possibility that Shk either regulates STAT3 independent of JAK2 or it binds directly to STAT3. To check the first probability, we activated STAT3 by treating the cells with IL6 (100 ng ml−1) for 1 h followed by treatment with Shk (2.5 μM) for 1 h. Both immunofluorescence and western-blotting results showed that Shk inhibited activated STAT3 without inhibiting JAK2 (Fig. S3AS3B) confirming that Shk inhibits JAK2 mediated activation of STAT3 possibly by binding directly to STAT3. For further confirmation, we performed an in silico molecular docking analysis to examine binding of Shk with the STAT3 SH2 domain. In a major conformational cluster, Shk occupied Lys-707, Lys-709 and Phe-710 binding sites in the STAT3 SH2 domain similar to the STAT3 standard inhibitor S3I-201 (Fig. S3C and S3D). The binding energy of Shk to STAT3 was −4.20 kcal mol−1. Collectively, these results showed that Shk potently inhibits STAT3 activation and also attenuates FAK and Src activation.

STAT3, Src and FAK are differentially expressed and activated in breast CSCs (BCSCs)

STAT3 and FAK are known to play an important role in proliferation and self-renewal of CSCs in various cancer types including breast cancer212224. Src also support CSC phenotype in some cancer types, but there are limited reports of its involvement in breast cancer25. Therefore, we checked the expression and activation of STAT3, FAK and Src in CSCs and non-CSCs. Here we used two methods to enrich the CSCs and non-CSCs. In the first method, the MDA-MB 231 cells were subjected to mammosphere formation for 96 h. After 96 h, mammosphere and non-mammosphere forming cells were clearly visible (Fig. 4A). These mammosphere and non-mammosphere forming cells were separated by using a 70 micron cell strainer. Mammospheres were subjected to two subculture cycles to enrich CSCs. With each passage, the viable single cells (non-mammosphere forming cells) and mammospheres were collected in RIPA lysis buffer and western blotting was done (Fig. 4B). We found that the activation and expression of the STAT3, FAK and Src is higher in enriched mammosphere cultures (Fig. 4C). In the second method, CD44+ CD24− cells were isolated from MCF7 cultures using MagCellect Breast CSC Isolation Kit. STAT3, FAK and Src activation and their mRNA and protein expression were assessed in enriched CSCs and were compared to parent MCF7 cell population. STAT3, FAK and Src all were differentially activated in CSCs (Fig. 4E). High mRNA as well as protein expressions of all the three genes was also observed in CSCs (Fig. 4D,E). Collectively, these results indicate that STAT3, FAK and Src are over expressed and activated in BCSCs.

Figure 4: STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

  • Representative picture indicating mammosphere and single suspended cells. (B) Schematic outline of mammosphere enrichment. (C) Protein expression and activation of STAT3, FAK and Src was determined in single suspended cells (non-mammosphere forming cells) and mammospheres by western blot. The full size blots corresponding to the cropped blot images are given in  S10. (D) Gene expression of STAT3, FAK and Src was determined in MCF7 parent population and CD44+ CD24−/low MCF7 cells using PCR. The full agarose gel images corresponding to the cropped images are given in Fig. S10. (E) Protein expression and activation of STAT3, FAK and Src was in CD44+ 24− cells and parent population.
STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f4.jpg

STAT3 is important for mammosphere formation and CSC programs in breast cancer

As our results indicated that the expression and activation of STAT3, FAK and Src is high in BCSCs and Shk is capable of inhibiting these signaling proteins; therefore to find out functional relevance of each protein and associated effects on their pharmacological inhibition by Shk, we used specific inhibitors against these three. Effect of these inhibitors was first tested on the mammosphere forming potential of MDA-MB 231, MDA-MB 468 and MCF7 cells. A drastic reduction in the mammosphere formation was observed upon STAT3 inhibition. FAK and Src inhibition also reduced the primary and secondary mammosphere formation but STAT3 inhibition showed most potent effect (Fig. 5A and S4). Further, we also checked the effect of these inhibitors on the expression of various CSC and EMT related markers in MDA-MB 231 cells. STAT3 inhibition decreased the expression of most of the CSC and EMT markers (Fig. 5B). These two findings indicated that STAT3 inhibition is more effective in reducing mammosphere forming potential and weakens major CSC programs and the anti-CSC potential of Shk is possibly due to its strong STAT3 inhibitory effect.
(not shown)

STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer

STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer

Figure 5: STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer.

http://www.nature.com/srep/2015/150514/srep10194/carousel/srep10194-f5.jpg

(A) Bar graph represents number of mammospheres formed from 2500 cells in presence and absence of indicated treatments. MDA-MB 231, MDA-MB 468 and MCF7 24 h mammosphere cultures were treated with Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). After 24 h, treatments were removed and cells were allowed to grow in fresh mammosphere culture media for 8 days. (B) Expression of various stem cell and EMT related transcription factors and markers were detected using western blotting in MDA-MB 231 cells with or without indicated treatments. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) MDA-MB 231, MDA-MB 468 and MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. Bar graph represents average of three independent experiments. (D) MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. After 24 h, cells were treated with DMSO (untreated) or Shk (treated) as indicated in the bar graph. Data are shown as the mean ±SD. (*) p < 0.05 and (**) p < 0.01.

To further check the involvement of these pathways in CSCs, we cultured MDA-MB 231, MDA-MB 468 and MCF7 cells in the presence of either IL6 (100ng ml−1), EGF (25 ng ml−1) or Fibronectin (1 μg ml−1) coated surface for two population doublings. Cells were then subjected to mammosphere formation. In IL6 pre-treated cultures, there was a sharp rise in mammosphere formation, indicating that the STAT3 activation shifts CSC and non-CSC dynamics towards CSCs (Fig. 5C). IL6 is previously known to induce the conversion of non-CSC to CSC via STAT3 activation26. In MCF7 cells, mammosphere forming potential after IL6 pre-treatment increased nearly by three fold. Therefore, we further checked the effectiveness of Shk on mammosphere forming potential in pre-treated MCF7 cells. It was found that Shk inhibits mammosphere formation most effectively in IL6 pre-treated cultures (Fig. 5D). However, in EGF and Fibronectin pre-treated cultures, Shk was relatively less effective. This was possibly due to its weak FAK and Src inhibitory potential. Collectively, these results illustrated that STAT3 activation is significantly correlated with the mammosphere forming potential of breast cancer cells and its inhibition by a standard inhibitor or Shk potently reduce the mammosphere formation.

Shk inhibit CSCs load by disrupting the STAT3-Oct3/4 axis

In breast cancer, STAT3 mediated expression of Oct3/4 is a major regulator of CSC self-renewal2627. As we observed that both Shk and STAT3 inhibitors decreased the Oct3/4 expression (Figs. 2C and 5B), we further checked the effect of STAT3 activation on ALDH1+ CSCs and Oct3/4 expression. On IL6 pre-treatment, number of ALDH1+ cells increased in all three (MDA-MB 231, MDA-MB 468 and MCF7) cancer cells (Fig. 6A). MCF7 cells showed highest increase. Therefore, to check the effect of STAT3 inhibition on CSC load, we incubated IL6 pre-treated MCF7 cells with Shk and STAT3 inhibitor for 24 h and analyzed for ALDH1 positivity. It was observed that both Shk and STAT3 inhibitor reduced the IL6 induced ALDH1 positivity from 10% to < 2% (Fig. 6B). These results suggested that Shk induced inhibition of STAT3 and decrease in BCSC load is interlinked. We further checked the effect of STAT3 activation status on Oct3/4 expression in MDA-MB 231, MDA-MB 468 and MCF7 cells. We observed that expression of Oct3/4 increases with the increase in STAT3 activation (Fig. 6C–E).

(not shown)

Figure 6: STAT3 activation status and its effect on cancer stem cell load

STAT3 transcriptional activity is important in maintaining CSC programs2829. Therefore, we also examined the effect of Shk on STAT3 promoter activity. STAT3 reporter assay was performed in presence of IL6 and Shk; it was found that Shk reduced the promoter activity of STAT3 in a dose dependent manner (Fig. S5). Collectively, these results showed that Shk mediated STAT3 inhibition are responsible for decrease in CSC load and Oct3/4 associated stem cell programs.

Shk inhibits mammosphere formation, migration and invasion through inhibition of STAT3, FAK and Src in breast cancer cells

As the earlier results (Fig. 1) showed that Shk inhibits cell migration and invasion in breast cancer cells, we further examined the effect of STAT3, FAK and Src inhibitors on cell migration and invasion in MDA-MB 231 cells. It was found that STAT3 inhibitor poorly inhibits cell migration while both Src and FAK inhibitors were effective in reducing cell migration (Fig. 7A). All the three inhibitors decreased the cell invasion and MMP9 expression significantly (Fig. 7B and S6). It was also observed that effect of all these inhibitors, except STAT3 inhibitor on mammosphere formation and FAK inhibitor on cell migration, were not comparable to that of Shk. Shk inhibited all these properties more effectively than individual inhibition of STAT3, FAK and Src. This made us to assume that the ability of Shk to inhibit multiple signaling molecules simultaneously is the reason behind its potent anti-cancer effect. To check this notion, we combined STAT3, FAK and Src inhibitors with each other and examined the effect of combinations on invasion, migration and mammosphere forming potential in MDA-MB 231 cells. We observed further decrease in cell migration and invasion on combining STAT3 and FAK, STAT3 and Src, or FAK and Src (Figs. 7A,B). Combination of FAK and Src was not very effective in inhibiting mammosphere formation in MDA-MB 231 cells and CD44+ CD24− MCF7 CSCs. However, their combination with STAT3 decreased the mammosphere forming potential equivalent to that of Shk (Fig. 7C,D). We also compared the mammosphere forming potential of Shk with Salinomycin (another anti-CSC agent) and found that at 2.5 μM dose of Shk was almost two times more potent than Salinomycin (Fig. S7). Collectively, these results indicated that Shk inhibits multiple signaling proteins (STAT3, FAK and Src) to compromise various aggressive breast cancer hallmarks.

Figure 7: Combination of FAK, Src and STAT3 inhibitors is more potent than individual inhibition against various cancer hallmarks.

combination-of-fak-src-and-stat3-inhibitors-is-more-potent-than-individual-inhibition-against-various-cancer-hallmarks

combination-of-fak-src-and-stat3-inhibitors-is-more-potent-than-individual-inhibition-against-various-cancer-hallmarks

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f7.jpg

  • Cell migration and (B) cell invasion potential of MDA-MB 231 cells was assessed in the presence of Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). Various combinations of these inhibitors were also used STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM + AZM 475271; 10 μM) and FAK+Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cell migration and cell invasion was assessed through scratch cell migration assay and transwell invasion after 24 h of treatments. (C,D) Mammosphere forming potential of MDA-MB 231 cells and CD44+ CD24−/low enriched MCF7 cells was assessed in presence of similar combination of STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM+ AZM 475271; 10 μM) and FAK + Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cells were subjected to mammosphere cultures for 24 h and treated with the indicated inhibitors for next 24 h, followed by media change and growth of mammospheres were monitored for next 8 days. Data are shown as the mean ±SD. (**) p < 0.01.

Shk inhibits breast cancer growth, metastasis and decreases tumorigenicity

To explore whether Shk may have therapeutic potential for breast cancer treatment in vivo, we tested Shk against 4T1-induced breast cancer syngenic mouse model. 4T1 cells (mouse breast cancer cells) are capable of growing fast and metastasize efficiently in vivo30. Prior to the in vivo experiments, we checked the effect of Shk on ALDH1 positivity and on activation of STAT3, FAK and Src in 4T1 cells in vitro. Shk effectively decreased the ALDH1+ cells and inhibited STAT3, FAK and Src in 4T1 cells in vitro (Fig. S8A and S8B). For in vivo tumor generation, 1 × 106 cells were injected subcutaneously in the fourth nipple mammary fat pad of BALB/c mice. When the average size of tumors reached around 50 mm3, mice were divided into three groups, vehicle and two Shk treated groups each received either 2.5 mg Kg−1 or 5.0 mg Kg−1 Shk. Shk was administered via the intraperitoneal injection on every alternate day. It significantly suppressed the tumor growth in 4T1 induced syngenic mouse model (Fig. 8A). The average reduction in 4T1 tumor growth was 49.78% and 89.73% in 2.5 mg Kg−1 and 5.0 mg Kg−1 groups respectively compared with the vehicle treated group (Fig. 8A). No considerable change in body weight of the treated group animals was observed (Fig. S9A). We further examined the effect of Shk on the tumor initiating potential of breast cancer cells. 4T1 induced tumors were excised from the control and treatment groups on the second day after 4th dose of Shk was administered. Tumors were dissociated; cells were allowed to adhere and then re-injected into new animals for secondary tumor formation. Growth of secondary tumors was monitored till day 15 post-reinjection. Shk treated groups showed a marked decrease in secondary tumor formation (Fig. 8D). We also observed a drastic reduction in the number of metastatic nodules in the lungs of treatment group animals (Fig. 8F). The reduction in the metastatic load was not proportional to the decrease in tumor sizes; however within the treatment group, some animals with small tumors were carrying higher number of metastatic nodules. As FAK is an important mediator of cancer metastasis and metastatic colonization, we further examined the effects of Shk on metastatic colonization. For this, 1 × 105 4T1 cells were injected to BALB/c mice through tail vein. Animals were divided into three groups, as indicated above. Shk and vehicle were administered through intraperitoneal injections at alternate days starting from the 2nd day post tail vein injections till 33rd day. The average reduction in total number of metastatic nodules was 88.6% – 90.5% in Shk treated mice compared to vehicle control (Fig. 8F). An inset picture (Fig. 8A lower panel) represents lung morphology of vehicle control and treated groups. We further examined the activation and expression status of STAT3, FAK and Src between vehicle control and treated group tumors. There were low expression and activation of STAT3, FAK and Src in treated tumors as compared to the vehicle control (Fig. 8B,C). Similar trend was observed in ALDH1 expressions (Fig. 8B). Further, the mice tumor sections were subjected to immunohistochemistry, immunofluorescence and hematoxylin and eosin (H&E) staining to study histology and expression of key proteins being examined in this study. Fig. 8G shows representative images of H&E staining, proliferating cell nuclear antigen (PCNA), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), STAT3 and Oct3/4 immunostaining. PCNA expression was low while TUNEL positive cells were high in tumor tissues of Shk treated groups. STAT3 and Oct3/4 expression was low in Shk treated groups. These results collectively demonstrated that Shk modulates the expression and activation of STAT3, FAK and Src in vivo and is effective in suppressing tumorigenic potential and metastasis in syngenic mouse model.

Figure 8: Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo.

Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo

Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f8.jpg

  • Shk inhibited 4T1 tumor growth. Bar graph represents the average tumor volumes in vehicle control and Shk treated tumor bearing mice (n = 6). (*) p < 0.05 and (**) p < 0.01. Inset picture of upper panel represents tumor sizes and lower pane represents lung morphology in vehicle control and Shk treatment groups. (B) Western blot examination of indicated proteins for their expression and activation in vehicle control and treated tumor groups. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) Gene expression of stem cell and EMT markers in tumor tissues excised from the vehicle control and Shk treated groups (n = 3). (D) Number of secondary tumors formed after injecting indicated cell dilutions from Vehicle treated and Shk treated 4T1 tumors. (E) Number of lung nodules formed in mice injected with 4T1 mouse mammary tumor cells in the mammary fat pad and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks (n = 6). (F) Number of lung nodules in mice injected with 4T1 mouse mammary tumor cells through tail vein and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks. (n = 8) (G) Representative panel of the histological H&E staining, immunofluorescence staining for the STAT3, Oct3/4, cell proliferation marker PCNA and DNA damage indicator-TUNEL staining of tumor sections from vehicle and treatment groups.

Recent studies have shown that aggressiveness, therapy resistance and disease relapse in breast cancer is attributed to a small population of CSCs involved in continuous self-renewal and differentiation through signaling pathways similar to that of the normal stem cells31. Therapeutic targeting of CSCs therefore, has profound clinical implications for cancer treatment31. Recent studies indicated that therapies / agents targeting both differentiated cancer cells and CSCs may possibly have significant therapeutic advantages32. Therefore, it is imperative to look for novel therapeutic agents with lesser side effects urgently for effective targeting of CSCs. In search of novel, nontoxic anti-CSC agents, attention has been focused on natural agents in recent times33,34. In this study, we have used a natural napthoquinone compound, Shk with established antitumorigenic, favorable pharmacokinetic and toxicity profiles and report for the first time its potent anti-CSC properties. Shk significantly inhibits breast cancer cell proliferation in vitroex vivoand in vivo. It decreases the cell migration and invasion of breast cancer cells in vivo, as well as inhibits tumorigenicity, metastasis and metastatic colonization in a syngenic mouse model of breast cancer in vivo. These finding suggest a strong potential of Shk in breast cancer therapy.

We assessed the effect of Shk on the CSC load in breast cancer cells through various functional assays (tumorsphere in vitro and syngenic mouse model of breast cancer in vivo) and quantification of specific stem cell markers. In breast cancer, CD44+ CD24− cells and ALDH1+ cells are considered to be BCSCs2125. Shk significantly decreased the mammosphere formation (Fig. 1HS1G and 2H), ALDH1+ cell and CD44+ CD24− cell loads in vitro (Fig. 2BS2E and S2H). It also reduced the expression of CSC markers (Oct3/4, Sox2, Nanog, c-Myc and Aldh1) in vivo andin vitro (Fig. 2C,DS2C and S2D). These genes are known to regulate stem cell programs and in cancer, they are established promoters and regulators of CSC phenotype353637383940. Decrease in the expression of these genes on Shk treatment indicates its potential to suppress CSC programs. Tumor initiating potential (tumorigenicity) is the bona fide measure of CSCs. Reduction in the tumorigenic potential of cells isolated form Shk treated tumors indicates in vivoanti-CSC effects of Shk.

We further demonstrated that Shk is a potent inhibitor of STAT3 and it also inhibits FAK and Src (Fig. 3A–C). Its STAT3 inhibitory property was found to be responsible for its anti-CSC effects (Figs. 6B and 7B). STAT3 and FAK inhibitors are previously known to compromise CSC growth41,42. Here, we found that pharmacological inhibition of STAT3 was more effective in compromising CSC load than FAK and Src inhibitions (Fig. 5A). STAT3 activation through IL6 increases mammosphere formation more significantly than Src and FAK activation through EGF and Fibronectin (Fig. 5C). This indicates that IL6-STAT3 axis is a key regulator of BCSC dynamics.

11.2.3.9 Ovatodiolide Sensitizes Aggressive Breast Cancer Cells to Doxorubicin Anticancer Activity, Eliminates Their Cancer Stem Cell-Like Phenotype, and Reduces Doxorubicin-Associated Toxicity

Investigators evaluated the usability of ovatodiolide (Ova) in sensitizing triple negative breast cancer (TNBC) cells to doxorubicin (Doxo), cytotoxicity, so as to reduce Doxo effective dose and consequently its adverse effects. Ova-sensitized TNBC cells also lost their cancer stem cell-like phenotype evidenced by significant dissolution and necrosis of formed mammospheres, as well as their terminal differentiation. [Cancer Lett]

11.2.3.10 Glabridin Inhibits Cancer Stem Cell-Like Properties of Human Breast Cancer Cells: An Epigenetic Regulation of miR-148a/SMAd2 Signaling

The authors report that glabridin (GLA) attenuated the cancer stem cell (CSC)-like properties through microRNA-148a (miR-148a)/transforming growth factor beta-SMAD2 signal pathway in vitro and in vivo. In MDA-MB-231 and Hs-578T breast cancer cell lines, GLA enhanced the expression of miR-148a through DNA demethylation. [Mol Carcinog]

11.2.3.11 Ginsenoside Rh2 Inhibits Cancer Stem-Like Cells in Skin Squamous Cell Carcinoma

The effects of ginsenoside Rh2 (GRh2) on Lgr5-positive cancer stem cells (CSCs) were determined by flow cytometry and by tumor sphere formation. Scientists found that GRh2 dose-dependently reduced skin squamous cell carcinoma viability, possibly through reduced the number of Lgr5-positive CSCs. [Cell Physiol Biochem]

Liu S. Chen M. Li P. Wu Y. Chang C. Qiu Y. Cao L. Liu Z. Jia C.
Cell Physiol Biochem 2015;36:499-508
http://dx.doi.org:/10.1159/000430115

Background/Aims: Treatments targeting cancer stem cells (CSCs) are most effective cancer therapy, whereas determination of CSCs is challenging. We have recently reported that Lgr5-positive cells are cancer stem cells (CSCs) in human skin squamous cell carcinoma (SCC). Ginsenoside Rh2 (GRh2) has been shown to significantly inhibit growth of some types of cancers, whereas its effects on the SCC have not been examined. Methods: Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by fow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for Atg7 and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Results: We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability. Conclusion: Taken together, our data suggest that GRh2 inhibited SCC growth, possibly through reduced the number of Lgr5-positive CSCs. This may be conducted through an interaction Carcinoma account for more than 80% of all types of cancer worldwide, and squamous cell carcinoma (SCC) is the most frequent carcinoma. Skin SCC causes a lot of mortality yearly, which requires a better understanding of the molecular carcinogesis of skin SCC for developing efficient therapy [1,2]. Ginsenoside Rh2 (GRh2) is a characterized component in red ginseng, and has proven therapeutic effects on inflammation [3] and a number of cancers [4,5,6,7,8,9,10,11,12,13,14], whereas its effects on the skin SCC have not been examined.

Cancer stem cells (CSCs) are cancer cells with great similarity to normal stem cells, e.g., the ability to give rise to various cell types in a particular cancer [15,16]. CSCs are highly tumorigenic, compared to other non-CSCs. CSCs appear to persist in tumors as a distinct population and CSCs are believed to be responsible for cancer relapse and metastasis after primary tumor resection [15,16,17,18]. Recently, the appreciation of the critical roles of CSCs in cancer therapy have been continuously increasing, although the identification of CSCs in a particular cancer is still challenging.

To date, different cell surface proteins have been used to isolate CSCs from a variety of cancers by flow cytometry. Among these markers for identification of CSCs, the most popular ones are prominin-1 (CD133), side population (SP) and increased activity of aldehyde dehydrogenase (ALDH). CD133 is originally detected in hematopoietic stem cells, endothelial progenitor cells and neuronal and glial stem cells. Later on, CD133 has been shown to be expressed in the CSCs from some tumors [19,20,21,22,23], but with exceptions [24]. SP is a sub-population of cells that efflux chemotherapy drugs, which accounts for the resistance of cancer to chemotherapy. Hoechst (HO) has been experimentally used for isolation of SP cells, while the enrichment of CSCs by SP appears to be limited [25]. Increased activity of ALDH, a detoxifying enzyme responsible for the oxidation of intracellular aldehydes [26,27], has also been used to identify CSCs, using aldefluor assay [28,29]. However, ALDH has also been detected in other cell types, which creates doubts on the purity of CSCs using ALDH method [30,31]. Moreover, all these methods appear to be lack of cancer specificity.

The Wnt target gene Lgr5 has been recently identified as a stem cell marker of the intestinal epithelium, and of the hair follicle [32,33]. Recently, we reported that Lgr5 may be a potential CSC marker for skin SCC [34]. We detected extremely high Lgr5 levels in the resected skin SCC specimen from the patients. In vitro, Lgr5-positive SCC cells grew significantly faster than Lgr5-negative cells, and the fold increase in growth of Lgr5-positive vs Lgr5-negative cells is significantly higher than SP vs non-SP, or ALDH-high vs ALDH-low, or CD133-positive vs CD133-negative cells. Elimination of Lgr5-positive SCC cells completely inhibited cancer cell growth in vitro.

Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by flow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for autophagy-related protein 7 (Atg7) and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Atg7 was identified based on homology to Pichia pastoris GSA7 and Saccharomyces cerevisiae APG7. In the yeast, the protein appears to be required for fusion of peroxisomal and vacuolar membranes. The protein shows homology to the ATP-binding and catalytic sites of the E1 ubiquitin activating enzymes. Atg7 is a mediator of autophagosomal biogenesis, and is a putative regulator of autophagic function [35,36,37,38]. We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability.

Transduction of SCC cells with GFP under Lgr5 promoter

We have recently shown that Lgr5 is CSC marker for skin SCC [34]. In order to examine the role of GRh2 on SCC cells, as well as a possible effect on CSCs, we transduced human skin SCC cells A431 [34] with a lentivirus carrying GFP reporter under Lgr5 promoter (Fig. 1A). The Lgr5-positive cells were green fluorescent in culture (Fig. 1B), and could be analyzed or isolated by flow cytometry, based on GFP (Fig. 1C).

(not shown)

Fig. 1. Transduction of SCC cells with GFP under Lgr5 promoter. (A) The structure of lentivirus carrying GFP reporter under Lgr5 promoter. (B) The pLgr5-GFP-transduced A431 cells in culture. Lgr5-positive cells were green fluorescent. Nuclear staining was done by DAPI. (C) Representative flow chart for analyzing pLgr5-GFP-transduced A431 cells by flow cytometry based on GFP. Gated cells were Lgr5-positive cells. Scar bar is 20µm.

GRh2 dose-dependently inhibits SCC cell growth

Then, we examined the effect of GRh2 on the viability of SCC cells. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. We found that from 0.01mg/ml to 1mg/ml, GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (Fig. 2A), or a MTT assay (Fig. 2B). Next, we questioned whether GRh2 may have a specific effect on CSCs in SCC cells. Thus, we analyzed GFP+ cells, which represent Lgr5-positive CSCs in pLgr5-GFP-transduced A431 cells after GRh2 treatment. We found that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (Fig. 2C), and by quantification (Fig. 2D). We also examined the capability of the GRh2-treated cells in the formation of tumor sphere. We found that GRh2 dose-dependently deceased the formation of tumor sphere-like structure, by quantification (Fig. 2E), and by representative images (Fig. 2F). Together, these data suggest that GRh2 dose-dependently inhibited SCC cell growth, possibly through inhibition of CSCs.

Fig. 2. GRh2 dose-dependently inhibits SCC cell growth. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. (A-B) GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (A), or a MTT assay (B). (C-D) GFP+ cells after GRh2 treatment were analyzed by flow cytometry, showing that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (C), and by quantification (D). The capability of the GRh2-treated cells to form tumor sphere-like structures was examined, shown by quantification (E), and by representative images (F). *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f02.JPG

GRh2 treatment decreases β-catenin and increases autophagy in SCC cells

We analyzed the molecular mechanisms underlying the cancer inhibitory effects of GRh2 on SCC cells. We thus examined the growth-regulatory proteins in SCC. From a variety of proteins, we found that GRh2 treatment dose-dependently decreases β-catenin, and dose-dependently upregulated autophagy-related proteins Beclin, Atg7 and increased the ratio of LC3 II to LC3 I, by quantification (Fig. 3A), and by representative Western blots (Fig.3B). Since β-catenin signaling is a strong cell-growth stimulator and autophagy can usually lead to stop of cell-growth and cell death, we feel that the alteration in these pathways may be responsible for the GRh2-mediated suppression of SCC growth.

(not shown)

Figure 3. GRh2 treatment decreases β-catenin and increases autophagy in SCC cells.

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Inhibition of autophagy abolishes the effects of GRh2 on β-catenin

In order to find out the relationship between β-catenin and autophagy in this model, we inhibited autophagy using a shRNA for Atg7, and examined its effect on the changes of β-catenin by GRh2. First, the inhibition of Atg7 in A431 cells by shAtg7 was confirmed by RT-qPCR (Fig. 4A), and by Western blot (Fig. 4B). Inhibition of Atg7 resulted in abolishment of the effects of GRh2 on other autophagy-associated proteins (Fig. 4B), and resulted in abolishment of the inhibitory effect of GRh2 on β-catenin (Fig. 4B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 4C). Together, inhibition of autophagy abolishes the effects of GRh2 on β-catenin. Thus, the regulation of GRh2 on β-catenin needs autophagy-associated proteins.

Fig. 4. Inhibition of autophagy abolishes the effects of GRh2 on β-catenin.

A431 cells were transfected with shRNA for Atg7, or scrambled sequence (scr) as a control. (A) RT-qPCR for Atg7. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f04.JPG

Overexpression of β-catenin abolishes the effects of GRh2 on autophagy

Next, we inhibited the effects of GRh2 on β-catenin by overexpression of β-catenin in A431 cells. First, the overexpression of β-catenin in A431 cells was confirmed by RT-qPCR (Fig. 5A), and by Western blot (Fig. 5B). Overexpression of β-catenin resulted in abolishment of the effects of GRh2 on autophagy-associated proteins (Fig. 5B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 5C). Together, inhibition of β-catenin signaling abolishes the effects of GRh2 on autophagy. Thus, the regulation of GRh2 on autophagy needs β-catenin signaling. This model is thus summarized in a schematic (Fig. 6), suggesting that GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.

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Fig. 5. Overexpression of β-catenin abolishes the effects of GRh2 on autophagy. A431 cells were transfected with β-catenin, or scrambled sequence (scr) as a control. (A) RT-qPCR for β-catenin. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f06.JPG

Fig. 6. Schematic of the model. GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.

Understanding the cancer molecular biology of skin SCC and identification of an effective treatment are both critical for improving the current therapy [1]. Lgr5 has been recently identified as a novel stem cell marker of the intestinal epithelium and the hair follicle, in which Lgr5 is expressed in actively cycling cells [32,33]. Moreover, we recently showed that Lgr5-positive are CSCs in skin SCC [34]. Thus, specific targeting Lgr5-positive cells may be a promising therapy for skin SCC.

In the current study, we analyzed the effects of GRh2 on the viability of SCC. Importantly, we not only found that GRh2 dose-dependently decreases SCC cell viability, but also dose-dependently decreased the number of Lgr5-positive CSCs in SCC cells. These data suggest that the CSCs in SCC may be more susceptible for the GRh2 treatment, and the decreases in CSCs may result in the decreased viability in total SCC cells. This point was supported by following mechanism studies. Activated β-catenin signaling by WNT/GSK3β prevents degradation of β-catenin and induces its nuclear translocation [39]. Nuclear β-catenin thus activates c-myc, cyclinD1 and c-jun to promote cell proliferation, and activates Bcl-2 to inhibit apoptosis [39]. High β-catenin levels thus are a signature of CSCs. Therefore, it is not surprising that CSCs are more affected than other cells when GRh2 targets β-catenin signaling.

In addition, GRh2 appears to target autophagy. Although altered metabolism may be beneficial to the cancer cells, it can create an increased demand for nutrients to support cell growth and proliferation, which creates metabolic stress and subsequently induces autophagy, a catabolic process leading to degradation of cellular components through the lysosomal system [40]. Cancer cells use autophagy as a survival strategy to provide essential biomolecules that are required for cell viability under metabolic stress [40]. However, autophagy not only results in a staring in cell growth, but also may result in cell death [40]. Increases in autophagy may substantially decrease cancer cell growth. Thus, GRh2 has its inhibitory effect on skin SCC cells through a combined effect on cell proliferation (by decreasing β-catenin) and autophagy [40].

Interestingly, our data suggest an interaction between β-catenin and autophagy. This finding is consistent with previous reports showing that autophagy negatively modulates Wnt/β-catenin signaling by promoting Dvl instability [41,42], and with other studies showing that β-catenin regulates autophagy [38,43,44].

Of note, we have checked other SCC lines and essentially got same results. Together with our previous reports showing that Lgr5-positive cells are CSCs in skin SCC [34], these findings thus highlight a future engagement of Lgr5-directed GRh2 therapy, which could be performed in a sufficiently frequent manner, to substantially improve the current treatment for skin SCC.

Normal vs Cancer Thyroid Stem Cells: The Road to Transformation
The authors discuss new insights into thyroid stem cells as a potential source of cancer formation in light of the available information on the oncogenic role of genetic modifications that occur during thyroid cancer development. Understanding the fine mechanisms that regulate tumor transformation may provide new ground for clinical intervention in terms of prevention, diagnosis and therapy. [Oncogene] Abstract
Cancer Stem Cells: A Potential Target for Cancer Therapy
The identification of cancer stem cells (CSCs) and a better understanding of the complex characteristics of CSCs will provide invaluable diagnostic, therapeutic and prognostic targets for clinical application. The authors introduce the dysregulated properties of CSCs in cancers and discuss the possible challenges in targeting CSCs for cancer treatment. [Cell Mol Life Sci] Abstract
Targeting Cancer Stem Cells Using Immunologic Approaches
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Hypoxia Inducible Factor 1 (HIF-1)

Writer and Curator: Larry H Bernstein, MD, FCAP

7.9  Hypoxia Inducible Factor 1 (HIF-1)

7.9.1 Hypoxia and mitochondrial oxidative metabolism

7.9.2 Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability

7.9.3 Hypoxia-Inducible Factors in Physiology and Medicine

7.9.4 Hypoxia-inducible factor 1. Regulator of mitochondrial metabolism and mediator of ischemic preconditioning

7.9.5 Regulation of cancer cell metabolism by hypoxia-inducible factor 1

7.9.6 Coming up for air. HIF-1 and mitochondrial oxygen consumption

7.9.7 HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption

7.9.8 HIF-1. upstream and downstream of cancer metabolism

7.9.9 In Vivo HIF-Mediated Reductive Carboxylation

7.9.10 Evaluation of HIF-1 inhibitors as anticancer agents

 

 

7.9.1 Hypoxia and mitochondrial oxidative metabolism

Solaini G1Baracca ALenaz GSgarbi G.
Biochim Biophys Acta. 2010 Jun-Jul; 1797(6-7):1171-7
http://dx.doi.org/10.1016/j.bbabio.2010.02.011

It is now clear that mitochondrial defects are associated with a large variety of clinical phenotypes. This is the result of the mitochondria’s central role in energy production, reactive oxygen species homeostasis, and cell death. These processes are interdependent and may occur under various stressing conditions, among which low oxygen levels (hypoxia) are certainly prominent. Cells exposed to hypoxia respond acutely with endogenous metabolites and proteins promptly regulating metabolic pathways, but if low oxygen levels are prolonged, cells activate adapting mechanisms, the master switch being the hypoxia-inducible factor 1 (HIF-1). Activation of this factor is strictly bound to the mitochondrial function, which in turn is related with the oxygen level. Therefore in hypoxia, mitochondria act as [O2] sensors, convey signals to HIF-1directly or indirectly, and contribute to the cell redox potential, ion homeostasis, and energy production. Although over the last two decades cellular responses to low oxygen tension have been studied extensively, mechanisms underlying these functions are still indefinite. Here we review current knowledge of the mitochondrial role in hypoxia, focusing mainly on their role in cellular energy and reactive oxygen species homeostasis in relation with HIF-1 stabilization. In addition, we address the involvement of HIF-1 and the inhibitor protein of F1F0 ATPase in the hypoxia-induced mitochondrial autophagy.

Over the last two decades a defective mitochondrial function associated with hypoxia has been invoked in many diverse complex disorders, such as type 2 diabetes [1] and [2], Alzheimer’s disease [3] and [4], cardiac ischemia/reperfusion injury [5] and [6], tissue inflammation [7], and cancer [8][9][10],[11] and [12].

The [O2] in air-saturated aqueous buffer at 37 °C is approx. 200 μM [13]; however, mitochondria in vivo are exposed to a considerably lower [O2] that varies with tissue and physiological state. Under physiological conditions, most human resting cells experience some 5% oxygen tension, however the [O2] gradient occurring between the extracellular environment and mitochondria, where oxygen is consumed by cytochrome c oxidase, results in a significantly lower [O2] exposition of mitochondria. Below this oxygen level, most mammalian tissues are exposed to hypoxic conditions  [14]. These may arise in normal development, or as a consequence of pathophysiological conditions where there is a reduced oxygen supply due to a respiratory insufficiency or to a defective vasculature. Such conditions include inflammatory diseases, diabetes, ischemic disorders (cerebral or cardiovascular), and solid tumors. Mitochondria consume the greatest amount (some 85–90%) of oxygen in cells to allow oxidative phosphorylation (OXPHOS), which is the primary metabolic pathway for ATP production. Therefore hypoxia will hamper this metabolic pathway, and if the oxygen level is very low, insufficient ATP availability might result in cell death [15].

When cells are exposed to an atmosphere with reduced oxygen concentration, cells readily “respond” by inducing adaptive reactions for their survival through the AMP-activated protein kinase (AMPK) pathway (see for a recent review [16]) which inter alia increases glycolysis driven by enhanced catalytic efficiency of some enzymes, including phosphofructokinase-1 and pyruvate kinase (of note, this oxidative flux is thermodynamically allowed due to both reduced phosphorylation potential [ATP]/([ADP][Pi]) and the physiological redox state of the cell). However, this is particularly efficient only in the short term, therefore cells respond to prolonged hypoxia also by stimulation of hypoxia-inducible factors (HIFs: HIF-1 being the mostly studied), which are heterodimeric transcription factors composed of α and β subunits, first described by Semenza and Wang [17]. These HIFs in the presence of hypoxic oxygen levels are activated through a complex mechanism in which the oxygen tension is critical (see below). Afterwards HIFs bind to hypoxia-responsive elements, activating the transcription of more than two hundred genes that allow cells to adapt to the hypoxic environment [18] and [19].

Several excellent reviews appeared in the last few years describing the array of changes induced by oxygen deficiency in both isolated cells and animal tissues. In in vivo models, a coordinated regulation of tissue perfusion through vasoactive molecules such as nitric oxide and the action of carotid bodies rapidly respond to changes in oxygen demand [20][21][22][23] and [24]. Within isolated cells, hypoxia induces significant metabolic changes due to both variation of metabolites level and activation/inhibition of enzymes and transporters; the most important intracellular effects induced by different pathways are expertly described elsewhere (for recent reviews, see [25][26] and [27]). It is reasonable to suppose that the type of cells and both the severity and duration of hypoxia may determine which pathways are activated/depressed and their timing of onset [3][6][10][12][23] and [28]. These pathways will eventually lead to preferential translation of key proteins required for adaptation and survival to hypoxic stress. Although in the past two decades, the discovery of HIF-1 by Gregg Semenza et al. provided a molecular platform to investigate the mechanism underlying responses to oxygen deprivation, the molecular and cellular biology of hypoxia has still to be completely elucidated. This review summarizes recent experimental data concerned with mitochondrial structure and function adaptation to hypoxia and evaluates it in light of the main structural and functional parameters defining the mitochondrial bioenergetics. Since mitochondria contain an inhibitor protein, IF1, whose action on the F1F0 ATPase has been considered for decades of critical importance in hypoxia/ischemia, particular notice will be dedicated to analyze molecular aspects of IF1 regulation of the enzyme and its possible role in the metabolic changes induced by low oxygen levels in cells.

Mechanism(s) of HIF-1 activation

HIF-1 consists of an oxygen-sensitive HIF-1α subunit that heterodimerizes with the HIF-1β subunit to bind DNA. In high O2 tension, HIF-1α is oxidized (hydroxylated) by prolyl hydroxylases (PHDs) using α-ketoglutarate derived from the tricarboxylic acid (TCA) cycle. The hydroxylated HIF-1α subunit interacts with the von Hippel–Lindau protein, a critical member of an E3 ubiquitin ligase complex that polyubiquitylates HIF. This is then catabolized by proteasomes, such that HIF-1α is continuously synthesized and degraded under normoxic conditions [18]. Under hypoxia, HIF-1α hydroxylation does not occur, thereby stabilizing HIF-1 (Fig. 1). The active HIF-1 complex in turn binds to a core hypoxia response element in a wide array of genes involved in a diversity of biological processes, and directly transactivates glycolytic enzyme genes [29]. Notably, O2 concentration, multiple mitochondrial products, including the TCA cycle intermediates and reactive oxygen species, can coordinate PHD activity, HIF stabilization, hence the cellular responses to O2 depletion [30] and [31]. Incidentally, impaired TCA cycle flux, particularly if it is caused by succinate dehydrogenase dysfunction, results in decreased or loss of energy production from both the electron-transport chain and the Krebs cycle, and also in overproduction of free radicals [32]. This leads to severe early-onset neurodegeneration or, as it occurs in individuals carrying mutations in the non-catalytic subunits of the same enzyme, to tumors such as phaeochromocytoma and paraganglioma. However, impairment of the TCA cycle may be relevant also for the metabolic changes occurring in mitochondria exposed to hypoxia, since accumulation of succinate has been reported to inhibit PHDs [33]. It has to be noticed that some authors believe reactive oxygen species (ROS) to be essential to activate HIF-1 [34], but others challenge this idea [35], therefore the role of mitochondrial ROS in the regulation of HIF-1 under hypoxia is still controversial [36]. Moreover, the contribution of functional mitochondria to HIF-1 regulation has also been questioned by others [37][38] and [39].

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Major mitochondrial changes in hypoxia

Major mitochondrial changes in hypoxia

Fig. 1. Major mitochondrial changes in hypoxia. Hypoxia could decrease electron-transport rate determining Δψm reduction, increased ROS generation, and enhanced NO synthase. One (or more) of these factors likely contributes to HIF stabilization, that in turn induces metabolic adaptation of both hypoxic cells and mitophagy. The decreased Δψm could also induce an active binding of IF1, which might change mitochondrial morphology and/or dynamics, and inhibit mitophagy. Solid lines indicate well established hypoxic changes in cells, whilst dotted lines indicate changes not yet stated. Inset, relationships between extracellular O2concentration and oxygen tension.

Oxygen is a major determinant of cell metabolism and gene expression, and as cellular O2 levels decrease, either during isolated hypoxia or ischemia-associated hypoxia, metabolism and gene expression profiles in the cells are significantly altered. Low oxygen reduces OXPHOS and Krebs cycle rates, and participates in the generation of nitric oxide (NO), which also contributes to decrease respiration rate [23] and [40]. However, oxygen is also central in the generation of reactive oxygen species, which can participate in cell signaling processes or can induce irreversible cellular damage and death [41].

As specified above, cells adapt to oxygen reduction by inducing active HIF, whose major effect on cells energy homeostasis is the inactivation of anabolism, activation of anaerobic glycolysis, and inhibition of the mitochondrial aerobic metabolism: the TCA cycle, and OXPHOS. Since OXPHOS supplies the majority of ATP required for cellular processes, low oxygen tension will severely reduce cell energy availability. This occurs through several mechanisms: first, reduced oxygen tension decreases the respiration rate, due first to nonsaturating substrate for cytochrome c oxidase (COX), secondarily, to allosteric modulation of COX[42]. As a consequence, the phosphorylation potential decreases, with enhancement of the glycolysis rate primarily due to allosteric increase of phosphofructokinase activity; glycolysis however is poorly efficient and produces lactate in proportion of 0.5 mol/mol ATP, which eventually drops cellular pH if cells are not well perfused, as it occurs under defective vasculature or ischemic conditions  [6]. Besides this “spontaneous” (thermodynamically-driven) shift from aerobic to anaerobic metabolism which is mediated by the kinetic changes of most enzymes, the HIF-1 factor activates transcription of genes encoding glucose transporters and glycolytic enzymes to further increase flux of reducing equivalents from glucose to lactate[43] and [44]. Second, HIF-1 coordinates two different actions on the mitochondrial phase of glucose oxidation: it activates transcription of the PDK1 gene encoding a kinase that phosphorylates and inactivates pyruvate dehydrogenase, thereby shunting away pyruvate from the mitochondria by preventing its oxidative decarboxylation to acetyl-CoA [45] and [46]. Moreover, HIF-1 induces a switch in the composition of cytochrome c oxidase from COX4-1 to COX4-2 isoform, which enhances the specific activity of the enzyme. As a result, both respiration rate and ATP level of hypoxic cells carrying the COX4-2 isoform of cytochrome c oxidase were found significantly increased with respect to the same cells carrying the COX4-1 isoform [47]. Incidentally, HIF-1 can also increase the expression of carbonic anhydrase 9, which catalyses the reversible hydration of CO2 to HCO3 and H+, therefore contributing to pH regulation.

Effects of hypoxia on mitochondrial structure and dynamics

Mitochondria form a highly dynamic tubular network, the morphology of which is regulated by frequent fission and fusion events. The fusion/fission machineries are modulated in response to changes in the metabolic conditions of the cell, therefore one should expect that hypoxia affect mitochondrial dynamics. Oxygen availability to cells decreases glucose oxidation, whereas oxygen shortage consumes glucose faster in an attempt to produce ATP via the less efficient anaerobic glycolysis to lactate (Pasteur effect). Under these conditions, mitochondria are not fueled with substrates (acetyl-CoA and O2), inducing major changes of structure, function, and dynamics (for a recent review see [48]). Concerning structure and dynamics, one of the first correlates that emerge is that impairment of mitochondrial fusion leads to mitochondrial depolarization, loss of mtDNA that may be accompanied by altered respiration rate, and impaired distribution of the mitochondria within cells [49][50] and [51]. Indeed, exposure of cortical neurons to moderate hypoxic conditions for several hours, significantly altered mitochondrial morphology, decreased mitochondrial size and reduced mitochondrial mean velocity. Since these effects were either prevented by exposing the neurons to inhibitors of nitric oxide synthase or mimicked by NO donors in normoxia, the involvement of an NO-mediated pathway was suggested [52]. Mitochondrial motility was also found inhibited and controlled locally by the [ADP]/[ATP] ratio [53]. Interestingly, the author used an original approach in which mitochondria were visualized using tetramethylrhodamineethylester and their movements were followed by applying single-particle tracking.

Of notice in this chapter is that enzymes controlling mitochondrial morphology regulators provide a platform through which cellular signals are transduced within the cell in order to affect mitochondrial function [54]. Accordingly, one might expect that besides other mitochondrial factors [30] and [55] playing roles in HIF stabilization, also mitochondrial morphology might reasonably be associated with HIF stabilization. In order to better define the mechanisms involved in the morphology changes of mitochondria and in their dynamics when cells experience hypoxic conditions, these pioneering studies should be corroborated by and extended to observations on other types of cells focusing also on single proteins involved in both mitochondrial fusion/fission and motion.

Effects of hypoxia on the respiratory chain complexes

O2 is the terminal acceptor of electrons from cytochrome c oxidase (Complex IV), which has a very high affinity for it, being the oxygen concentration for half-maximal respiratory rate at pH 7.4 approximately 0.7 µM [56]. Measurements of mitochondrial oxidative phosphorylation indicated that it is not dependent on oxygen concentration up to at least 20 µM at pH 7.0 and the oxygen dependence becomes markedly greater as the pH is more alkaline [56]. Similarly, Moncada et al. [57] found that the rate of O2 consumption remained constant until [O2] fell below 15 µM. Accordingly, most reports in the literature consider hypoxic conditions occurring in cells at 5–0.5% O2, a range corresponding to 46–4.6 µM O2 in the cells culture medium (see Fig. 1 inset). Since between the extracellular environment and mitochondria an oxygen pressure gradient is established [58], the O2 concentration experienced by Complex IV falls in the range affecting its kinetics, as reported above.

Under these conditions, a number of changes on the OXPHOS machinery components, mostly mediated by HIF-1 have been found. Thus, Semenza et al. [59] and others thereafter [46] reported that activation of HIF-1α induces pyruvate dehydrogenase kinase, which inhibits pyruvate dehydrogenase, suggesting that respiration is decreased by substrate limitation. Besides, other HIF-1 dependent mechanisms capable to affect respiration rate have been reported. First, the subunit composition of COX is altered in hypoxic cells by increased degradation of the COX4-1 subunit, which optimizes COX activity under aerobic conditions, and increased expression of the COX4-2 subunit, which optimizes COX activity under hypoxic conditions [29]. On the other hand, direct assay of respiration rate in cells exposed to hypoxia resulted in a significant reduction of respiration [60]. According with the evidence of Zhang et al., the respiration rate decrease has to be ascribed to mitochondrial autophagy, due to HIF-1-mediated expression of BNIP3. This interpretation is in line with preliminary results obtained in our laboratory where the assay of the citrate synthase activity of cells exposed to different oxygen tensions was performed. Fig. 2 shows the citrate synthase activity, which is taken as an index of the mitochondrial mass [11], with respect to oxygen tension: [O2] and mitochondrial mass are directly linked.

Citrate synthase activity

Citrate synthase activity

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Fig. 2. Citrate synthase activity. Human primary fibroblasts, obtained from skin biopsies of 5 healthy donors, were seeded at a density of 8,000 cells/cm2 in high glucose Dulbecco’s Modified Eagle Medium, DMEM (25 mM glucose, 110 mg/l pyruvate, and 4 mM glutamine) supplemented with 15% Foetal Bovine Serum (FBS). 18 h later, cell culture dishes were washed once with Hank’s Balanced Salt Solution (HBSS) and the medium was replaced with DMEM containing 5 mM glucose, 110 mg/l pyruvate, and 4 mM glutamine supplemented with 15% FBS. Cell culture dishes were then placed into an INVIVO2 humidified hypoxia workstation (Ruskinn Technologies, Bridgend, UK) for 72 h changing the medium at 48 h, and oxygen partial pressure (tension) conditions were: 20%, 4%, 2%, 1% and 0.5%. Cells were subsequently collected within the workstation with trypsin-EDTA (0.25%), washed with PBS and resuspended in a buffer containing 10 mM Tris/HCl, 0.1 M KCl, 5 mM KH2PO4, 1 mM EGTA, 3 mM EDTA, and 2 mM MgCl2 pH 7.4 (all the solutions were preconditioned to the appropriate oxygen tension condition). The citrate synthase activity was assayed essentially by incubating 40 µg of cells with 0.02% Triton X-100, and monitoring the reaction by measuring spectrophotometrically the rate of free coenzyme A released, as described in [90]. Enzymatic activity was expressed as nmol/min/mg of protein. Three independent experiments were carried out and assays were performed in either duplicate or triplicate.

However, the observations of Semenza et al. must be seen in relation with data reported by Moncada et al.[57] and confirmed by others [61] in which it is clearly shown that when cells (various cell lines) experience hypoxic conditions, nitric oxide synthases (NOSs) are activated, therefore NO is released. As already mentioned above, NO is a strong competitor of O2 for cytochrome c oxidase, whose apparent Km results increased, hence reduction of mitochondrial cytochromes and all the other redox centres of the respiratory chain occurs. In addition, very recent data indicate a potential de-activation of Complex I when oxygen is lacking, as it occurs in prolonged hypoxia [62]. According to Hagen et al. [63] the NO-dependent inhibition of cytochrome c oxidase should allow “saved” O2 to redistribute within the cell to be used by other enzymes, including PHDs which inactivate HIF. Therefore, unless NO inhibition of cytochrome c oxidase occurs only when [O2] is very low, inhibition of mitochondrial oxygen consumption creates the paradox of a situation in which the cell may fail to register hypoxia. It has been tempted to solve this paradox, but to date only hypotheses have been proposed [23] and [26]. Interestingly, recent observations on yeast cells exposed to hypoxia revealed abnormal protein carbonylation and protein tyrosine nitration that were ascribed to increased mitochondrially generated superoxide radicals and NO, two species typically produced at low oxygen levels, that combine to form ONOO [64]. Based on these studies a possible explanation has been proposed for the above paradox.

Finally, it has to be noticed that the mitochondrial respiratory deficiency observed in cardiomyocytes of dogs in which experimental heart failure had been induced lies in the supermolecular assembly rather than in the individual components of the electron-transport chain [65]. This observation is particularly intriguing since loss of respirasomes is thought to facilitate ROS generation in mitochondria [66], therefore supercomplexes disassembly might explain the paradox of reduced [O2] and the enhanced ROS found in hypoxic cells. Specifically, hypoxia could reduce mitochondrial fusion by impairing mitochondrial membrane potential, which in turn could induce supercomplexes disassembly, increasing ROS production[11].

Complex III and ROS production

It has been estimated that, under normoxic physiological conditions, 1–2% of electron flow through the mitochondrial respiratory chain gives rise to ROS [67] and [68]. It is now recognized that the major sites of ROS production are within Complexes I and III, being prevalent the contribution of Complex I [69] (Fig. 3). It might be expected that hypoxia would decrease ROS production, due to the low level of O2 and to the diminished mitochondrial respiration [6] and [46], but ROS level is paradoxically increased. Indeed, about a decade ago, Chandel et al. [70] provided good evidence that mitochondrial reactive oxygen species trigger hypoxia-induced transcription, and a few years later the same group [71] showed that ROS generated at Complex III of the mitochondrial respiratory chain stabilize HIF-1α during hypoxia (Fig. 1 and Fig. 3). Although others have proposed mechanisms indicating a key role of mitochondria in HIF-1α regulation during hypoxia (for reviews see [64] and [72]), the contribution of mitochondria to HIF-1 regulation has been questioned by others [35][36] and [37]. Results of Gong and Agani [35] for instance show that inhibition of electron-transport Complexes I, III, and IV, as well as inhibition of mitochondrial F0F1 ATPase, prevents HIF-1α expression and that mitochondrial reactive oxygen species are not involved in HIF-1α regulation during hypoxia. Concurrently, Tuttle et al. [73], by means of a non invasive, spectroscopic approach, could find no evidence to suggest that ROS, produced by mitochondria, are needed to stabilize HIF-1α under moderate hypoxia. The same authors found the levels of HIF-1α comparable in both normal and ρ0 cells (i.e. cells lacking mitochondrial DNA). On the contrary, experiments carried out on genetic models consisting of either cells lacking cytochrome c or ρ0 cells both could evidence the essential role of mitochondrial respiration to stabilize HIF-1α [74]. Thus, cytochrome c null cells, being incapable to respire, exposed to moderate hypoxia (1.5% O2) prevented oxidation of ubiquinol and generation of the ubisemiquinone radical, thus eliminating superoxide formation at Complex III [71]. Concurrently, ρ0 cells lacking electron transport, exposed 4 h to moderate hypoxia failed to stabilize HIF-1α, suggesting the essential role of the respiratory chain for the cellular sensing of low O2 levels. In addition, recent evidence obtained on genetic manipulated cells (i.e. cytochrome b deficient cybrids) showed increased ROS levels and stabilized HIF-1α protein during hypoxia [75]. Moreover, RNA interference of the Complex III subunit Rieske iron sulfur protein in the cytochrome b deficient cells, abolished ROS generation at the Qo site of Complex III, preventing HIF-1α stabilization. These observations, substantiated by experiments with MitoQ, an efficient mitochondria-targeted antioxidant, strongly support the involvement of mitochondrial ROS in regulating HIF-1α. Nonetheless, collectively, the available data do not allow to definitely state the precise role of mitochondrial ROS in regulating HIF-1α, but the pathway stabilizing HIF-1α appears undoubtedly mitochondria-dependent [30].

Overview of mitochondrial electron and proton flux in hypoxia

Overview of mitochondrial electron and proton flux in hypoxia

Overview of mitochondrial electron and proton flux in hypoxia

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Fig. 3. Overview of mitochondrial electron and proton flux in hypoxia. Electrons released from reduced cofactors (NADH and FADH2) under normoxia flow through the redox centres of the respiratory chain (r.c.) to molecular oxygen (blue dotted line), to which a proton flux from the mitochondrial matrix to the intermembrane space is coupled (blue arrows). Protons then flow back to the matrix through the F0 sector of the ATP synthase complex, driving ATP synthesis. ATP is carried to the cell cytosol by the adenine nucleotide translocator (blue arrows). Under moderate to severe hypoxia, electrons escape the r.c. redox centres and reduce molecular oxygen to the superoxide anion radical before reaching the cytochrome c (red arrow). Under these conditions, to maintain an appropriate Δψm, ATP produced by cytosolic glycolysis enters the mitochondria where it is hydrolyzed by the F1F0ATPase with extrusion of protons from the mitochondrial matrix (red arrows).

Hypoxia and ATP synthase

The F1F0 ATPase (ATP synthase) is the enzyme responsible of catalysing ADP phosphorylation as the last step of OXPHOS. It is a rotary motor using the proton motive force across the mitochondrial inner membrane to drive the synthesis of ATP [76]. It is a reversible enzyme with ATP synthesis or hydrolysis taking place in the F1 sector at the matrix side of the membrane, chemical catalysis being coupled to H+transport through the transmembrane F0 sector.

Under normoxia the enzyme synthesizes ATP, but when mitochondria experience hypoxic conditions the mitochondrial membrane potential (Δψm) decreases below its endogenous steady-state level (some 140 mV, negative inside the matrix [77]) and the F1F0 ATPase may work in the reversal mode: it hydrolyses ATP (produced by anaerobic glycolysis) and uses the energy released to pump protons from the mitochondrial matrix to the intermembrane space, concurring with the adenine nucleotide translocator (i.e. in hypoxia it exchanges cytosolic ATP4− for matrix ADP3−) to maintain the physiological Δψm ( Fig. 3). Since under conditions of limited oxygen availability the decline in cytoplasmic high energy phosphates is mainly due to hydrolysis by the ATP synthase working in reverse [6] and [78], the enzyme must be strictly regulated in order to avoid ATP dissipation. This is achieved by a natural protein, the H+ψm-dependent IF1, that binds to the catalytic F1 sector at low pH and low Δψm (such as it occurs in hypoxia/ischemia) [79]. IF1 binding to the ATP synthase results in a rapid and reversible inhibition of the enzyme [80], which could reach about 50% of maximal activity (for recent reviews see [6] and [81]).

Besides this widely studied effect, IF1 appears to be associated with ROS production and mitochondrial autophagy (mitophagy). This is a mechanism involving the catabolic degradation of macromolecules and organelles via the lysosomal pathway that contributes to housekeeping and regenerate metabolites. Autophagic degradation is involved in the regulation of the ageing process and in several human diseases, such as myocardial ischemia/reperfusion [82], Alzheimer’s Disease, Huntington diseases, and inflammatory diseases (for recent reviews see [83] and [84], and, as mentioned above, it promotes cell survival by reducing ROS and mtDNA damage under hypoxic conditions.

Campanella et al. [81] reported that, in HeLa cells under normoxic conditions, basal autophagic activity varies in relation to the expression levels of IF1. Accordingly, cells overexpressing IF1 result in ROS production similar to controls, conversely cells in which IF1 expression is suppressed show an enhanced ROS production. In parallel, the latter cells show activation of the mitophagy pathway (Fig. 1), therefore suggesting that variations in IF1 expression level may play a significant role in defining two particularly important parameters in the context of the current review: rates of ROS generation and mitophagy. Thus, the hypoxia-induced enhanced expression level of IF1[81] should be associated with a decrease of both ROS production and autophagy, which is in apparent conflict with the hypoxia-induced ROS increase and with the HIF-1-dependent mitochondrial autophagy shown by Zhang et al. [60] as an adaptive metabolic response to hypoxia. However, in the experiments of Zhang et al. the cells were exposed to hypoxia for 48 h, whereas the F1F0-ATPase inhibitor exerts a prompt action on the enzyme and to our knowledge, it has never been reported whether its action persists during prolonged hypoxic expositions. Pertinent with this problem is the very recent observation that IEX-1 (immediate early response gene X-1), a stress-inducible gene that suppresses production of ROS and protects cells from apoptosis [85], targets the mitochondrial F1F0-ATPase inhibitor for degradation, reducing ROS by decreasing Δψm. It has to be noticed that the experiments described were carried out under normal oxygen availability, but it does not seem reasonable to rule out IEX-1 from playing a role under stress conditions as those induced by hypoxia in cells, therefore this issue might deserve an investigation also at low oxygen levels.

In conclusion, data are still emerging regarding the regulation of mitochondrial function by the F1F0 ATPase within hypoxic responses in different cellular and physiological contexts. Given the broad pathophysiological role of hypoxic cellular modulation, an understanding of the subtle tuning among different effectors of the ATP synthase is desirable to eventually target future therapeutics most effectively. Our laboratory is actually involved in carrying out investigations to clarify this context.

Conclusions and perspectives

The mitochondria are important cellular platforms that both propagate and initiate intracellular signals that lead to overall cellular and metabolic responses. During the last decades, a significant amount of relevant data has been obtained on the identification of mechanisms of cellular adaptation to hypoxia. In hypoxic cells there is an enhanced transcription and synthesis of several glycolytic pathway enzymes/transporters and reduction of synthesis of proteins involved in mitochondrial catabolism. Although well defined kinetic parameters of reactions in hypoxia are lacking, it is usually assumed that these transcriptional changes lead to metabolic flux modification. The required biochemical experimentation has been scarcely addressed until now and only in few of the molecular and cellular biology studies the transporter and enzyme kinetic parameters and flux rate have been determined, leaving some uncertainties.

Central to mitochondrial function and ROS generation is an electrochemical proton gradient across the mitochondrial inner membrane that is established by the proton pumping activity of the respiratory chain, and that is strictly linked to the F1F0-ATPase function. Evaluation of the mitochondrial membrane potential in hypoxia has only been studied using semiquantitative methods based on measurements of the fluorescence intensity of probes taken up by cells experiencing normal or hypoxic conditions. However, this approach is intrinsically incorrect due to the different capability that molecular oxygen has to quench fluorescence [86] and [87] and to the uncertain concentration the probe attains within mitochondria, whose mass may be reduced by a half in hypoxia [60]. In addition, the uncertainty about measurement of mitochondrial superoxide radical and H2O2 formation in vivo [88] hampers studies on the role of mitochondrial ROS in hypoxic oxidative damage, redox signaling, and HIF-1 stabilization.

The duration and severity of hypoxic stress differentially activate the responses discussed throughout and lead to substantial phenotypic variations amongst tissues and cell models, which are not consistently and definitely known. Certainly, understanding whether a hierarchy among hypoxia response mechanisms exists and which are the precise timing and conditions of each mechanism to activate, will improve our knowledge of the biochemical mechanisms underlying hypoxia in cells, which eventually may contribute to define therapeutic targets in hypoxia-associated diseases. To this aim it might be worth investigating the hypoxia-induced structural organization of both the respiratory chain enzymes in supramolecular complexes and the assembly of the ATP synthase to form oligomers affecting ROS production [65] and inner mitochondrial membrane structure [89], respectively.

7.9.2 Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability

DR WisePS WardJES ShayJR CrossJJ Gruber, UM Sachdeva, et al.
Proc Nat Acad Sci Oct 27, 2011; 108(49):19611–19616
http://dx.doi.org:/10.1073/pnas.1117773108

Citrate is a critical metabolite required to support both mitochondrial bioenergetics and cytosolic macromolecular synthesis. When cells proliferate under normoxic conditions, glucose provides the acetyl-CoA that condenses with oxaloacetate to support citrate production. Tricarboxylic acid (TCA) cycle anaplerosis is maintained primarily by glutamine. Here we report that some hypoxic cells are able to maintain cell proliferation despite a profound reduction in glucose-dependent citrate production. In these hypoxic cells, glutamine becomes a major source of citrate. Glutamine-derived α-ketoglutarate is reductively carboxylated by the NADPH-linked mitochondrial isocitrate dehydrogenase (IDH2) to form isocitrate, which can then be isomerized to citrate. The increased IDH2-dependent carboxylation of glutamine-derived α-ketoglutarate in hypoxia is associated with a concomitant increased synthesis of 2-hydroxyglutarate (2HG) in cells with wild-type IDH1 and IDH2. When either starved of glutamine or rendered IDH2-deficient by RNAi, hypoxic cells are unable to proliferate. The reductive carboxylation of glutamine is part of the metabolic reprogramming associated with hypoxia-inducible factor 1 (HIF1), as constitutive activation of HIF1 recapitulates the preferential reductive metabolism of glutamine-derived α-ketoglutarate even in normoxic conditions. These data support a role for glutamine carboxylation in maintaining citrate synthesis and cell growth under hypoxic conditions.

Citrate plays a critical role at the center of cancer cell metabolism. It provides the cell with a source of carbon for fatty acid and cholesterol synthesis (1). The breakdown of citrate by ATP-citrate lyase is a primary source of acetyl-CoA for protein acetylation (2). Metabolism of cytosolic citrate by aconitase and IDH1 can also provide the cell with a source of NADPH for redox regulation and anabolic synthesis. Mammalian cells depend on the catabolism of glucose and glutamine to fuel proliferation (3). In cancer cells cultured at atmospheric oxygen tension (21% O2), glucose and glutamine have both been shown to contribute to the cellular citrate pool, with glutamine providing the major source of the four-carbon molecule oxaloacetate and glucose providing the major source of the two-carbon molecule acetyl-CoA (45). The condensation of oxaloacetate and acetyl-CoA via citrate synthase generates the 6 carbon citrate molecule. However, both the conversion of glucose-derived pyruvate to acetyl-CoA by pyruvate dehydrogenase (PDH) and the conversion of glutamine to oxaloacetate through the TCA cycle depend on NAD+, which can be compromised under hypoxic conditions. This raises the question of how cells that can proliferate in hypoxia continue to synthesize the citrate required for macromolecular synthesis.

This question is particularly important given that many cancers and stem/progenitor cells can continue proliferating in the setting of limited oxygen availability (67). Louis Pasteur first highlighted the impact of hypoxia on nutrient metabolism based on his observation that hypoxic yeast cells preferred to convert glucose into lactic acid rather than burning it in an oxidative fashion. The molecular basis for this shift in mammalian cells has been linked to the activity of the transcription factor HIF1 (810). Stabilization of the labile HIF1α subunit occurs in hypoxia. It can also occur in normoxia through several mechanisms including loss of the von Hippel-Lindau tumor suppressor (VHL), a common occurrence in renal carcinoma (11). Although hypoxia and/or HIF1α stabilization is a common feature of multiple cancers, to date the source of citrate in the setting of hypoxia or HIF activation has not been determined.

Here, we study the sources of hypoxic citrate synthesis in a glioblastoma cell line that proliferates in profound hypoxia (0.5% O2). Glucose uptake and conversion to lactic acid increased in hypoxia. However, glucose conversion into citrate dramatically declined. Glutamine consumption remained constant in hypoxia, and hypoxic cells were addicted to the use of glutamine in hypoxia as a source of α-ketoglutarate. Glutamine provided the major carbon source for citrate synthesis during hypoxia. However, the TCA cycle-dependent conversion of glutamine into citric acid was significantly suppressed. In contrast, there was a relative increase in glutamine-dependent citrate production in hypoxia that resulted from carboxylation of α-ketoglutarate. This reductive synthesis required the presence of mitochondrial isocitrate dehydrogenase 2 (IDH2). In confirmation of the reverse flux through IDH2, the increased reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia was associated with increased synthesis of 2HG. Finally, constitutive HIF1α-expressing cells also demonstrated significant reductive-carboxylation-dependent synthesis of citrate in normoxia and a relative defect in the oxidative conversion of glutamine into citrate. Collectively, the data demonstrate that mitochondrial glutamine metabolism can be rerouted through IDH2-dependent citrate synthesis in support of hypoxic cell growth.

Some Cancer Cells Can Proliferate at 0.5% O2 Despite a Sharp Decline in Glucose-Dependent Citrate Synthesis.

At 21% O2, cancer cells have been shown to synthesize citrate by condensing glucose-derived acetyl-CoA with glutamine-derived oxaloacetate through the activity of the canonical TCA cycle enzyme citrate synthase (4). In contrast, less is known regarding the synthesis of citrate by cells that can continue proliferating in hypoxia. The glioblastoma cell line SF188 is able to proliferate at 0.5% O2 (Fig. 1A), a level of hypoxia that is sufficient to stabilize HIF1α (Fig. 1B) and predicted to limit respiration (1213). Consistent with previous observations in hypoxic cells, we found that SF188 cells demonstrated increased lactate production when incubated in hypoxia (Fig. 1C), and the ratio of lactate produced to glucose consumed increased demonstrating an increase in the rate of anaerobic glycolysis. When glucose-derived carbon in the form of pyruvate is converted to lactate, it is diverted away from subsequent metabolism that can contribute to citrate production. However, we observed that SF188 cells incubated in hypoxia maintain their intracellular citrate to ∼75% of the level maintained under normoxia (Fig. 1D). This prompted an investigation of how proliferating cells maintain citrate production under hypoxia.

SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis.

SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis.

http://www.pnas.org/content/108/49/19611/F1.medium.gif

Fig. 1. SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis. (A) SF188 cells were plated in complete medium equilibrated with 21% O2 (Normoxia) or 0.5% O2 (Hypoxia), total viable cells were counted 24 h and 48 h later (Day 1 and Day 2), and population doublings were calculated. Data are the mean ± SEM of four independent experiments. (B) Western blot demonstrates stabilized HIF1α protein in cells cultured in hypoxia compared with normoxia. (C) Cells were grown in normoxia or hypoxia for 24 h, after which culture medium was collected. Medium glucose and lactate levels were measured and compared with the levels in fresh medium. (D) Cells were cultured for 24 h as in C. Intracellular metabolism was then quenched with 80% MeOH prechilled to −80 °C that was spiked with a 13C-labeled citrate as an internal standard. Metabolites were then extracted, and intracellular citrate levels were analyzed with GC-MS and normalized to cell number. Data for C and D are the mean ± SEM of three independent experiments. (E) Model depicting the pathway for cit+2 production from [U-13C]glucose. Glucose uniformly 13C-labeled will generate pyruvate+3. Pyruvate+3 can be oxidatively decarboxylated by PDH to produce acetyl-CoA+2, which can condense with unlabeled oxaloacetate to produce cit+2. (F) Cells were cultured for 24 h as in C and D, followed by an additional 4 h of culture in glucose-deficient medium supplemented with 10 mM [U-13C]glucose. Intracellular metabolites were then extracted, and 13C-enrichment in cellular citrate was analyzed by GC-MS and normalized to the total citrate pool size. Data are the mean ± SD of three independent cultures from a representative of two independent experiments. *P < 0.05, ***P < 0.001.

Increased glucose uptake and glycolytic metabolism are critical elements of the metabolic response to hypoxia. To evaluate the contributions made by glucose to the citrate pool under normoxia or hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 10 mM [U-13C]glucose. Following a 4-h labeling period, cellular metabolites were extracted and analyzed for isotopic enrichment by gas chromatography-mass spectrometry (GC-MS). In normoxia, the major 13C-enriched citrate species found was citrate enriched with two 13C atoms (cit+2), which can arise from the NAD+-dependent decarboxylation of pyruvate+3 to acetyl-CoA+2 by PDH, followed by the condensation of acetyl-CoA+2 with unenriched oxaloacetate (Fig. 1 E and F). Compared with the accumulation of cit+2, we observed minimal accumulation of cit+3 and cit+5 under normoxia. Cit+3 arises from pyruvate carboxylase (PC)-dependent conversion of pyruvate+3 to oxaloacetate+3, followed by the condensation of oxaloacetate+3 with unenriched acetyl-CoA. Cit+5 arises when PC-generated oxaloacetate+3 condenses with PDH-generated acetyl-CoA+2. The lack of cit+3 and cit+5 accumulation is consistent with PC activity not playing a major role in citrate production in normoxic SF188 cells, as reported (4).

In hypoxic cells, the major citrate species observed was unenriched. Cit+2, cit+3, and cit+5 all constituted minor fractions of the total citrate pool, consistent with glucose carbon not being incorporated into citrate through either PDH or PC-mediated metabolism under hypoxic conditions (Fig. 1F). These data demonstrate that in contrast to normoxic cells, where a large percentage of citrate production depends on glucose-derived carbon, hypoxic cells significantly reduce their rate of citrate production from glucose.

Glutamine Carbon Metabolism Is Required for Viability in Hypoxia.

In addition to glucose, we have previously reported that glutamine can contribute to citrate production during cell growth under normoxic conditions (4). Surprisingly, under hypoxic conditions, we observed that SF188 cells retained their high rate of glutamine consumption (Fig. 2A). Moreover, hypoxic cells cultured in glutamine-deficient medium displayed a significant loss of viability (Fig. 2B). In normoxia, the requirement for glutamine to maintain viability of SF188 cells can be satisfied by α-ketoglutarate, the downstream metabolite of glutamine that is devoid of nitrogenous groups (14). α-ketoglutarate cannot fulfill glutamine’s roles as a nitrogen source for nonessential amino acid synthesis or as an amide donor for nucleotide or hexosamine synthesis, but can be metabolized through the oxidative TCA cycle to regenerate oxaloacetate, and subsequently condense with glucose-derived acetyl-CoA to produce citrate. To test whether the restoration of carbon from glutamine metabolism in the form of α-ketoglutarate could rescue the viability defect of glutamine-starved SF188 cells even under hypoxia, SF188 cells incubated in hypoxia were cultured in glutamine-deficient medium supplemented with a cell-penetrant form of α-ketoglutarate (dimethyl α-ketoglutarate). The addition of dimethyl α-ketoglutarate rescued the defect in cell viability observed upon glutamine withdrawal (Fig. 2B). These data demonstrate that, even under hypoxic conditions, when the ability of glutamine to replenish oxaloacetate through oxidative TCA cycle metabolism is diminished, SF188 cells retain their requirement for glutamine as the carbon backbone for α-ketoglutarate. This result raised the possibility that glutamine could be the carbon source for citrate production through an alternative, nonoxidative, pathway in hypoxia.

Glutamine carbon is required for hypoxic cell viability

Glutamine carbon is required for hypoxic cell viability

Glutamine carbon is required for hypoxic cell viability

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Fig. 2. Glutamine carbon is required for hypoxic cell viability and contributes to increased citrate production through reductive carboxylation relative to oxidative metabolism in hypoxia. (A) SF188 cells were cultured for 24 h in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2(Hypoxia). Culture medium was then removed from cells and analyzed for glutamine levels which were compared with the glutamine levels in fresh medium. Data are the mean ± SEM of three independent experiments. (B) The requirement for glutamine to maintain hypoxic cell viability can be satisfied by α-ketoglutarate. Cells were cultured in complete medium equilibrated with 0.5% O2 for 24 h, followed by an additional 48 h at 0.5% O2 in either complete medium (+Gln), glutamine-deficient medium (−Gln), or glutamine-deficient medium supplemented with 7 mM dimethyl α-ketoglutarate (−Gln +αKG). All medium was preconditioned in 0.5% O2. Cell viability was determined by trypan blue dye exclusion. Data are the mean and range from two independent experiments. (C) Model depicting the pathways for cit+4 and cit+5 production from [U-13C]glutamine (glutamine+5). Glutamine+5 is catabolized to α-ketoglutarate+5, which can then contribute to citrate production by two divergent pathways. Oxidative metabolism produces oxaloacetate+4, which can condense with unlabeled acetyl-CoA to produce cit+4. Alternatively, reductive carboxylation produces isocitrate+5, which can isomerize to cit+5. (D) Glutamine contributes to citrate production through increased reductive carboxylation relative to oxidative metabolism in hypoxic proliferating cancer cells. Cells were cultured for 24 h as in A, followed by 4 h of culture in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in cellular citrate was quantitated with GC-MS. Data are the mean ± SD of three independent cultures from a representative of three independent experiments. **P < 0.01.

Cells Proliferating in Hypoxia Maintain Levels of Additional Metabolites Through Reductive Carboxylation.

Previous work has documented that, in normoxic conditions, SF188 cells use glutamine as the primary anaplerotic substrate, maintaining the pool sizes of TCA cycle intermediates through oxidative metabolism (4). Surprisingly, we found that, when incubated in hypoxia, SF188 cells largely maintained their levels of aspartate (in equilibrium with oxaloacetate), malate, and fumarate (Fig. 3A). To distinguish how glutamine carbon contributes to these metabolites in normoxia and hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 4 mM [U-13C]glutamine. After a 4-h labeling period, metabolites were extracted and the intracellular pools of aspartate, malate, and fumarate were analyzed by GC-MS.

In normoxia, the majority of the enriched intracellular asparatate, malate, and fumarate were the +4 species, which arise through oxidative metabolism of glutamine-derived α-ketoglutarate (Fig. 3 B and C). The +3 species, which can be derived from the citrate generated by the reductive carboxylation of glutamine-derived α-ketoglutarate, constituted a significantly lower percentage of the total aspartate, malate, and fumarate pools. By contrast, in hypoxia, the +3 species constituted a larger percentage of the total aspartate, malate, and fumarate pools than they did in normoxia. These data demonstrate that, in addition to citrate, hypoxic cells preferentially synthesize oxaloacetate, malate, and fumarate through the pathway of reductive carboxylation rather than the oxidative TCA cycle.

IDH2 Is Critical in Hypoxia for Reductive Metabolism of Glutamine and for Cell Proliferation.

We hypothesized that the relative increase in reductive carboxylation we observed in hypoxia could arise from the suppression of α-ketoglutarate oxidation through the TCA cycle. Consistent with this, we found that α-ketoglutarate levels increased in SF188 cells following 24 h in hypoxia (Fig. 4A). Surprisingly, we also found that levels of the closely related metabolite 2-hydroxyglutarate (2HG) increased in hypoxia, concomitant with the increase in α-ketoglutarate under these conditions. 2HG can arise from the noncarboxylating reduction of α-ketoglutarate (Fig. 4B). Recent work has found that specific cancer-associated mutations in the active sites of either IDH1 or IDH2 lead to a 10- to 100-fold enhancement in this activity facilitating 2HG production (1517), but SF188 cells lack IDH1/2 mutations. However, 2HG levels are also substantially elevated in the inborn error of metabolism 2HG aciduria, and the majority of patients with this disease lack IDH1/2 mutations. As 2HG has been demonstrated to arise in these patients from mitochondrial α-ketoglutarate (18), we hypothesized that both the increased reductive carboxylation of glutamine-derived α-ketoglutarate to citrate and the increased 2HG accumulation we observed in hypoxia could arise from increased reductive metabolism by wild-type IDH2 in the mitochondria.

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

http://www.pnas.org/content/108/49/19611/F4.medium.gif

Fig. 4. Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2. (A) α-ketoglutarate and 2HG increase in hypoxia. SF188 cells were cultured in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia) for 24 h. Intracellular metabolites were then extracted, cell extracts spiked with a 13C-labeled citrate as an internal standard, and intracellular α-ketoglutarate and 2HG levels were analyzed with GC-MS. Data shown are the mean ± SEM of three independent experiments. (B) Model for reductive metabolism from glutamine-derived α-ketoglutarate. Glutamine+5 is catabolized to α-ketoglutarate+5. Carboxylation of α-ketoglutarate+5 followed by reduction of the carboxylated intermediate (reductive carboxylation) will produce isocitrate+5, which can then isomerize to cit+5. In contrast, reductive activity on α-ketoglutarate+5 that is uncoupled from carboxylation will produce 2HG+5. (C) IDH2 is required for reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia. SF188 cells transfected with a siRNA against IDH2 (siIDH2) or nontargeting negative control (siCTRL) were cultured for 2 d in complete medium equilibrated with 0.5% O2. (Upper) Cells were then cultured at 0.5% O2 for an additional 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in intracellular citrate and 2HG was determined and normalized to the relevant metabolite total pool size. (Lower) Cells transfected and cultured in parallel at 0.5% O2 were counted by hemacytometer (excluding nonviable cells with trypan blue staining) or harvested for protein to assess IDH2 expression by Western blot. Data shown for GC-MS and cell counts are the mean ± SD of three independent cultures from a representative experiment. **P < 0.01, ***P < 0.001.

In an experiment to test this hypothesis, SF188 cells were transfected with either siRNA directed against mitochondrial IDH2 (siIDH2) or nontargeting control, incubated in hypoxia for 2 d, and then cultured for another 4 h in hypoxia in media containing 4 mM [U-13C]glutamine. After the labeling period, metabolites were extracted and analyzed by GC-MS (Fig. 4C). Hypoxic SF188 cells transfected with siIDH2 displayed a decreased contribution of cit+5 to the total citrate pool, supporting an important role for IDH2 in the reductive carboxylation of glutamine-derived α-ketoglutarate in hypoxic conditions. The contribution of cit+4 to the total citrate pool did not decrease with siIDH2 treatment, consistent with IDH2 knockdown specifically affecting the pathway of reductive carboxylation and not other fundamental TCA cycle-regulating processes. In confirmation of reverse flux occurring through IDH2, the contribution of 2HG+5 to the total 2HG pool decreased in siIDH2-treated cells. Supporting the importance of citrate production by IDH2-mediated reductive carboxylation for hypoxic cell proliferation, siIDH2-transfected SF188 cells displayed a defect in cellular accumulation in hypoxia. Decreased expression of IDH2 protein following siIDH2 transfection was confirmed by Western blot. Collectively, these data point to the importance of mitochondrial IDH2 for the increase in reductive carboxylation flux of glutamine-derived α-ketoglutarate to maintain citrate levels in hypoxia, and to the importance of this reductive pathway for hypoxic cell proliferation.

Reprogramming of Metabolism by HIF1 in the Absence of Hypoxia Is Sufficient to Induce Increased Citrate Synthesis by Reductive Carboxylation Relative to Oxidative Metabolism.

The relative increase in the reductive metabolism of glutamine-derived α-ketoglutarate at 0.5% O2 may be explained by the decreased ability to carry out oxidative NAD+-dependent reactions as respiration is inhibited (1213). However, a shift to preferential reductive glutamine metabolism could also result from the active reprogramming of cellular metabolism by HIF1 (810), which inhibits the generation of mitochondrial acetyl-CoA necessary for the synthesis of citrate by oxidative glucose and glutamine metabolism (Fig. 5A). To better understand the role of HIF1 in reductive glutamine metabolism, we used VHL-deficient RCC4 cells, which display constitutive expression of HIF1α under normoxia (Fig. 5B). RCC4 cells expressing either a nontargeting control shRNA (shCTRL) or an shRNA directed at HIF1α (shHIF1α) were incubated in normoxia and cultured in medium with 4 mM [U-13C]glutamine. Following a 4-h labeling period, metabolites were extracted and the cellular citrate pool was analyzed by GC-MS. In shCTRL cells, which have constitutive HIF1α expression despite incubation in normoxia, the majority of the total citrate pool was constituted by the cit+5 species, with low levels of all other species including cit+4 (Fig. 5C). By contrast, in HIF1α-deficient cells the contribution of cit+5 to the total citrate pool was greatly decreased, whereas the contribution of cit+4 to the total citrate pool increased and was the most abundant citrate species. These data demonstrate that the relative enhancement of the reductive carboxylation pathway for citrate synthesis can be recapitulated by constitutive HIF1 activation in normoxia.

Reprogramming of metabolism by HIF1 in the absence of hypoxia

Reprogramming of metabolism by HIF1 in the absence of hypoxia

http://www.pnas.org/content/108/49/19611/F5.medium.gif

Reprogramming of metabolism by HIF1 in the absence of hypoxia is sufficient to induce reductive carboxylation of glutamine-derived α-ketoglutarate.

Fig. 5. Reprogramming of metabolism by HIF1 in the absence of hypoxia is sufficient to induce reductive carboxylation of glutamine-derived α-ketoglutarate. (A) Model depicting how HIF1 signaling’s inhibition of pyruvate dehydrogenase (PDH) activity and promotion of lactate dehydrogenase-A (LDH-A) activity can block the generation of mitochondrial acetyl-CoA from glucose-derived pyruvate, thereby favoring citrate synthesis from reductive carboxylation of glutamine-derived α-ketoglutarate. (B) Western blot demonstrating HIF1α protein in RCC4 VHL−/− cells in normoxia with a nontargeting shRNA (shCTRL), and the decrease in HIF1α protein in RCC4 VHL−/− cells stably expressing HIF1α shRNA (shHIF1α). (C) HIF1-induced reprogramming of glutamine metabolism. Cells from B at 21% O2 were cultured for 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. Intracellular metabolites were then extracted, and 13C enrichment in cellular citrate was determined by GC-MS. Data shown are the mean ± SD of three independent cultures from a representative of three independent experiments. ***P < 0.001.

Compared with glucose metabolism, much less is known regarding how glutamine metabolism is altered under hypoxia. It has also remained unclear how hypoxic cells can maintain the citrate production necessary for macromolecular biosynthesis. In this report, we demonstrate that in contrast to cells at 21% O2, where citrate is predominantly synthesized through oxidative metabolism of both glucose and glutamine, reductive carboxylation of glutamine carbon becomes the major pathway of citrate synthesis in cells that can effectively proliferate at 0.5% O2. Moreover, we show that in these hypoxic cells, reductive carboxylation of glutamine-derived α-ketoglutarate is dependent on mitochondrial IDH2. Although others have previously suggested the existence of reductive carboxylation in cancer cells (1920), these studies failed to demonstrate the intracellular localization or specific IDH isoform responsible for the reductive carboxylation flux. Recently, we identified IDH2 as an isoform that contributes to reductive carboxylation in cancer cells incubated at 21% O2 (16), but remaining unclear were the physiological importance and regulation of this pathway relative to oxidative metabolism, as well as the conditions where this reductive pathway might be advantageous for proliferating cells.

Here we report that IDH2-mediated reductive carboxylation of glutamine-derived α-ketoglutarate to citrate is an important feature of cells proliferating in hypoxia. Moreover, the reliance on reductive glutamine metabolism can be recapitulated in normoxia by constitutive HIF1 activation in cells with loss of VHL. The mitochondrial NADPH/NADP+ ratio required to fuel the reductive reaction through IDH2 can arise from the increased NADH/NAD+ ratio existing in the mitochondria under hypoxic conditions (2122), with the transfer of electrons from NADH to NADP+ to generate NADPH occurring through the activity of the mitochondrial transhydrogenase (23). Our data do not exclude a complementary role for cytosolic IDH1 in impacting reductive glutamine metabolism, potentially through its oxidative function in an IDH2/IDH1 shuttle that transfers high energy electrons in the form of NADPH from mitochondria to cytosol (1624).

In further support of the increased mitochondrial reductive glutamine metabolism that we observe in hypoxia, we report here that incubation in hypoxia can lead to elevated 2HG levels in cells lacking IDH1/2 mutations. 2HG production from glutamine-derived α-ketoglutarate significantly decreased with knockdown of IDH2, supporting the conclusion that 2HG is produced in hypoxia by enhanced reverse flux of α-ketoglutarate through IDH2 in a truncated, noncarboxylating reductive reaction. However, other mechanisms may also contribute to 2HG elevation in hypoxia. These include diminished oxidative activity and/or enhanced reductive activity of the 2HG dehydrogenase, a mitochondrial enzyme that normally functions to oxidize 2HG back to α-ketoglutarate (25). The level of 2HG elevation we observe in hypoxic cells is associated with a concomitant increase in α-ketoglutarate, and is modest relative to that observed in cancers with IDH1/2 gain-of-function mutations. Nonetheless, 2HG elevation resulting from hypoxia in cells with wild-type IDH1/2 may hold promise as a cellular or serum biomarker for tissues undergoing chronic hypoxia and/or excessive glutamine metabolism.

The IDH2-dependent reductive carboxylation pathway that we propose in this report allows for continued citrate production from glutamine carbon when hypoxia and/or HIF1 activation prevents glucose carbon from contributing to citrate synthesis. Moreover, as opposed to continued oxidative TCA cycle functioning in hypoxia which can increase reactive oxygen species (ROS), reductive carboxylation of α-ketoglutarate in the mitochondria may serve as an electron sink that decreases the generation of ROS. HIF1 activity is not limited to the setting of hypoxia, as a common feature of several cancers is the normoxic stabilization of HIF1α through loss of the VHL tumor suppressor or other mechanisms. We demonstrate here that altered glutamine metabolism through a mitochondrial reductive pathway is a central aspect of hypoxic proliferating cell metabolism and HIF1-induced metabolic reprogramming. These findings are relevant for the understanding of numerous constitutive HIF1-expressing malignancies, as well as for populations, such as stem progenitor cells, which frequently proliferate in hypoxic conditions.

7.9.3 Hypoxia-Inducible Factors in Physiology and Medicine

Gregg L. Semenza
Cell. 2012 Feb 3; 148(3): 399–408.
http://dx.doi.org/10.1016%2Fj.cell.2012.01.021

Oxygen homeostasis represents an organizing principle for understanding metazoan evolution, development, physiology, and pathobiology. The hypoxia-inducible factors (HIFs) are transcriptional activators that function as master regulators of oxygen homeostasis in all metazoan species. Rapid progress is being made in elucidating homeostatic roles of HIFs in many physiological systems, determining pathological consequences of HIF dysregulation in chronic diseases, and investigating potential targeting of HIFs for therapeutic purposes. Oxygen homeostasis represents an organizing principle for understanding metazoan evolution, development, physiology, and pathobiology. The hypoxia-inducible factors (HIFs) are transcriptional activators that function as master regulators of oxygen homeostasis in all metazoan species. Rapid progress is being made in elucidating homeostatic roles of HIFs in many physiological systems, determining pathological consequences of HIF dysregulation in chronic diseases, and investigating potential targeting of HIFs for therapeutic purposes.

 

Oxygen is central to biology because of its utilization in the process of respiration. O2 serves as the final electron acceptor in oxidative phosphorylation, which carries with it the risk of generating reactive oxygen species (ROS) that react with cellular macromolecules and alter their biochemical or physical properties, resulting in cell dysfunction or death. As a consequence, metazoan organisms have evolved elaborate cellular metabolic and systemic physiological systems that are designed to maintain oxygen homeostasis. This review will focus on the role of hypoxia-inducible factors (HIFs) as master regulators of oxygen homeostasis and, in particular, on recent advances in understanding their roles in physiology and medicine. Due to space limitations and the remarkably pleiotropic effects of HIFs, the description of such roles will be illustrative rather than comprehensive.

O2 and Evolution, Part 1

Accumulation of O2 in Earth’s atmosphere starting ~2.5 billion years ago led to evolution of the extraordinarily efficient system of oxidative phosphorylation that transfers chemical energy stored in carbon bonds of organic molecules to the high-energy phosphate bond in ATP, which is used to power physicochemical reactions in living cells. Energy produced by mitochondrial respiration is sufficient to power the development and maintenance of multicellular organisms, which could not be sustained by energy produced by glycolysis alone (Lane and Martin, 2010). The modest dimensions of primitive metazoan species were such that O2 could diffuse from the atmosphere to all of the organism’s thousand cells, as is the case for the worm Caenorhabditis elegans. To escape the constraints placed on organismal growth by diffusion, systems designed to conduct air to cells deep within the body evolved and were sufficient for O2delivery to organisms with hundreds of thousands of cells, such as the fly Drosophila melanogaster. The final leap in body scale occurred in vertebrates and was associated with the evolution of complex respiratory, circulatory, and nervous systems designed to efficiently capture and distribute O2 to hundreds of millions of millions of cells in the case of the adult Homo sapiens.

Hypoxia-Inducible Factors

Hypoxia-inducible factor 1 (HIF-1) is expressed by all extant metazoan species analyzed (Loenarz et al., 2011). HIF-1 consists of HIF-1α and HIF-1β subunits, which each contain basic helix-loop-helix-PAS (bHLH-PAS) domains (Wang et al., 1995) that mediate heterodimerization and DNA binding (Jiang et al., 1996a). HIF-1β heterodimerizes with other bHLH-PAS proteins and is present in excess, such that HIF-1α protein levels determine HIF-1 transcriptional activity (Semenza et al., 1996).

Under well-oxygenated conditions, HIF-1α is bound by the von Hippel-Lindau (VHL) protein, which recruits an ubiquitin ligase that targets HIF-1α for proteasomal degradation (Kaelin and Ratcliffe, 2008). VHL binding is dependent upon hydroxylation of a specific proline residue in HIF-1α by the prolyl hydroxylase PHD2, which uses O2 as a substrate such that its activity is inhibited under hypoxic conditions (Epstein et al., 2001). In the reaction, one oxygen atom is inserted into the prolyl residue and the other atom is inserted into the co-substrate α-ketoglutarate, splitting it into CO2 and succinate (Kaelin and Ratcliffe, 2008). Factor inhibiting HIF-1 (FIH-1) represses HIF-1α transactivation function (Mahon et al., 2001) by hydroxylating an asparaginyl residue, using O2 and α-ketoglutarate as substrates, thereby blocking the association of HIF-1α with the p300 coactivator protein (Lando et al., 2002). Dimethyloxalylglycine (DMOG), a competitive antagonist of α-ketoglutarate, inhibits the hydroxylases and induces HIF-1-dependent transcription (Epstein et al., 2001). HIF-1 activity is also induced by iron chelators (such as desferrioxamine) and cobalt chloride, which inhibit hydroxylases by displacing Fe(II) from the catalytic center (Epstein et al., 2001).

Studies in cultured cells (Jiang et al., 1996b) and isolated, perfused, and ventilated lung preparations (Yu et al., 1998) revealed an exponential increase in HIF-1α levels at O2 concentrations less than 6% (~40 mm Hg), which is not explained by known biochemical properties of the hydroxylases. In most adult tissues, O2concentrations are in the range of 3-5% and any decrease occurs along the steep portion of the dose-response curve, allowing a graded response to hypoxia. Analyses of cultured human cells have revealed that expression of hundreds of genes was increased in response to hypoxia in a HIF-1-dependent manner (as determined by RNA interference) with direct binding of HIF-1 to the gene (as determined by chromatin immunoprecipitation [ChIP] assays); in addition, the expression of hundreds of genes was decreased in response to hypoxia in a HIF-1-dependent manner but binding of HIF-1 to these genes was not detected (Mole et al., 2009), indicating that HIF-dependent repression occurs via indirect mechanisms, which include HIF-1-dependent expression of transcriptional repressors (Yun et al., 2002) and microRNAs (Kulshreshtha et al., 2007). ChIP-seq studies have revealed that only 40% of HIF-1 binding sites are located within 2.5 kb of the transcription start site (Schödel et al., 2011).

In vertebrates, HIF-2α is a HIF-1α paralog that is also regulated by prolyl and asparaginyl hydroxylation and dimerizes with HIF-1β, but is expressed in a cell-restricted manner and plays important roles in erythropoiesis, vascularization, and pulmonary development, as described below. In D. melanogaster, the gene encoding the HIF-1α ortholog is designated similar and its paralog is designated trachealess because inactivating mutations result in defective development of the tracheal tubes (Wilk et al., 1996). In contrast, C. elegans has only a single HIF-1α homolog (Epstein et al., 2001). Thus, in both invertebrates and vertebrates, evolution of specialized systems for O2 delivery was associated with the appearance of a HIF-1α paralog.

O2 and Metabolism

The regulation of metabolism is a principal and primordial function of HIF-1. Under hypoxic conditions, HIF-1 mediates a transition from oxidative to glycolytic metabolism through its regulation of: PDK1, encoding pyruvate dehydrogenase (PDH) kinase 1, which phosphorylates and inactivates PDH, thereby inhibiting the conversion of pyruvate to acetyl coenzyme A for entry into the tricarboxylic acid cycle (Kim et al., 2006Papandreou et al., 2006); LDHA, encoding lactate dehydrogenase A, which converts pyruvate to lactate (Semenza et al. 1996); and BNIP3 (Zhang et al. 2008) and BNIP3L (Bellot et al., 2009), which mediate selective mitochondrial autophagy (Figure 1). HIF-1 also mediates a subunit switch in cytochrome coxidase that improves the efficiency of electron transfer under hypoxic conditions (Fukuda et al., 2007). An analogous subunit switch is also observed in Saccharomyces cerevisiae, although it is mediated by a completely different mechanism (yeast lack HIF-1), suggesting that it may represent a fundamental response of eukaryotic cells to hypoxia.

Regulation of Glucose Metabolism nihms-350382-f0001

Regulation of Glucose Metabolism nihms-350382-f0001

Regulation of Glucose Metabolism

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3437543/bin/nihms-350382-f0001.gif
Figure 1
Regulation of Glucose Metabolism

It is conventional wisdom that cells switch to glycolysis when O2 becomes limiting for mitochondrial ATP production. Yet, HIF-1α-null mouse embryo fibroblasts, which do not down-regulate respiration under hypoxic conditions, have higher ATP levels at 1% O2 than wild-type cells at 20% O2, demonstrating that under these conditions O2 is not limiting for ATP production (Zhang et al., 2008). However, the HIF-1α-null cells die under prolonged hypoxic conditions due to ROS toxicity (Kim et al. 2006Zhang et al., 2008). These studies have led to a paradigm shift with regard to our understanding of the regulation of cellular metabolism (Semenza, 2011): the purpose of this switch is to prevent excess mitochondrial generation of ROS that would otherwise occur due to the reduced efficiency of electron transfer under hypoxic conditions (Chandel et al., 1998). This may be particularly important in stem cells, in which avoidance of DNA damage is critical (Suda et al., 2011).

Role of HIFs in Development

Much of mammalian embryogenesis occurs at O2 concentrations of 1-5% and O2 functions as a morphogen (through HIFs) in many developmental systems (Dunwoodie, 2009). Mice that are homozygous for a null allele at the locus encoding HIF-1α die by embryonic day 10.5 with cardiac malformations, vascular defects, and impaired erythropoiesis, indicating that all three components of the circulatory system are dependent upon HIF-1 for normal development (Iyer et al., 1998Yoon et al., 2011). Depending on the genetic background, mice lacking HIF-2α: die by embryonic day 12.5 with vascular defects (Peng et al., 2000) or bradycardia due to deficient catecholamine production (Tian et al., 1998); die as neonates due to impaired lung maturation (Compernolle et al., 2002); or die several months after birth due to ROS-mediated multi-organ failure (Scortegagna et al., 2003). Thus, while vertebrate evolution was associated with concomitant appearance of the circulatory system and HIF-2α, both HIF-1 and HIF-2 have important roles in circulatory system development. Conditional knockout of HIF-1α in specific cell types has demonstrated important roles in chondrogenesis (Schipani et al., 2001), adipogenesis (Yun et al., 2002), B-lymphocyte development (Kojima et al., 2002), osteogenesis (Wang et al., 2007), hematopoiesis (Takubo et al., 2010), T-lymphocyte differentiation (Dang et al., 2011), and innate immunity (Zinkernagel et al., 2007). While knockout mouse experiments point to the adverse effects of HIF-1 loss-of-function on development, it is also possible that increased HIF-1 activity, induced by hypoxia in embryonic tissues as a result of abnormalities in placental blood flow, may also dysregulate development and result in congenital malformations. For example, HIF-1α has been shown to interact with, and stimulate the transcriptional activity of, Notch, which plays a key role in many developmental pathways (Gustafsson et al., 2005).

Translational Prospects

Drug discovery programs have been initiated at many pharmaceutical and biotech companies to develop prolyl hydroxylase inhibitors (PHIs) that, as described above for DMOG, induce HIF activity for treatment of disorders in which HIF mediates protective physiological responses. Local and/or short term induction of HIF activity by PHIs, gene therapy, or other means are likely to be useful novel therapies for many of the diseases described above. In the case of ischemic cardiovascular disease, local therapy is needed to provide homing signals for the recruitment of BMDACs. Chronic systemic use of PHIs must be approached with great caution: individuals with genetic mutations that constitutively activate the HIF pathway (described below) have increased incidence of cardiovascular disease and mortality (Yoon et al., 2011). On the other hand, the profound inhibition of HIF activity and vascular responses to ischemia that are associated with aging suggest that systemic replacement therapy might be contemplated as a preventive measure for subjects in whom impaired HIF responses to hypoxia can be documented. In C. elegans, VHL loss-of-function increases lifespan in a HIF-1-dependent manner (Mehta et al., 2009), providing further evidence for a mutually antagonistic relationship between HIF-1 and aging.

Cancer

Cancers contain hypoxic regions as a result of high rates of cell proliferation coupled with the formation of vasculature that is structurally and functionally abnormal. Increased HIF-1α and/or HIF-2α levels in diagnostic tumor biopsies are associated with increased risk of mortality in cancers of the bladder, brain, breast, colon, cervix, endometrium, head/neck, lung, ovary, pancreas, prostate, rectum, and stomach; these results are complemented by experimental studies, which demonstrate that genetic manipulations that increase HIF-1α expression result in increased tumor growth, whereas loss of HIF activity results in decreased tumor growth (Semenza, 2010). HIFs are also activated by genetic alterations, most notably, VHL loss of function in clear cell renal carcinoma (Majmunder et al., 2010). HIFs activate transcription of genes that play key roles in critical aspects of cancer biology, including stem cell maintenance (Wang et al., 2011), cell immortalization, epithelial-mesenchymal transition (Mak et al., 2010), genetic instability (Huang et al., 2007), vascularization (Liao and Johnson, 2007), glucose metabolism (Luo et al., 2011), pH regulation (Swietach et al., 2007), immune evasion (Lukashev et al., 2007), invasion and metastasis (Chan and Giaccia, 2007), and radiation resistance (Moeller et al., 2007). Given the extensive validation of HIF-1 as a potential therapeutic target, drugs that inhibit HIF-1 have been identified and shown to have anti-cancer effects in xenograft models (Table 1Semenza, 2010).

Table 1  Drugs that Inhibit HIF-1

Process Inhibited Drug Class Prototype
HIF-1 α synthesis Cardiac glycosidemTOR inhibitorMicrotubule targeting agent

Topoisomerase I inhibitor

DigoxinRapamycin2-Methoxyestradiol

Topotecan

HIF-1 α protein stability HDAC inhibitorHSP90 inhibitorCalcineurin inhibitor

Guanylate cyclase activator

LAQ82417-AAGCyclosporine

YC-1

Heterodimerization Antimicrobial agent Acriflavine
DNA binding AnthracyclineQuinoxaline antibiotic DoxorubicinEchinomycin
Transactivation Proteasome inhibitorAntifungal agent BortezomibAmphotericin B
Signal transduction BCR-ABL inhibitorCyclooxygenase inhibitorEGFR inhibitor

HER2 inhibitor

ImatinibIbuprofenErlotinib, Gefitinib

Trastuzumab

Over 100 women die every day of breast cancer in the U.S. The mean PO2 is 10 mm Hg in breast cancer as compared to > 60 mm Hg in normal breast tissue and cancers with PO2 < 10 mm Hg are associated with increased risk of metastasis and patient mortality (Vaupel et al., 2004). Increased HIF-1α protein levels, as identified by immunohistochemical analysis of tumor biopsies, are associated with increased risk of metastasis and/or patient mortality in unselected breast cancer patients and in lymph node-positive, lymph node-negative, HER2+, or estrogen receptor+ subpopulations (Semenza, 2011). Metastasis is responsible for > 90% of breast cancer mortality. The requirement for HIF-1 in breast cancer metastasis has been demonstrated for both autochthonous tumors in transgenic mice (Liao et al., 2007) and orthotopic transplants in immunodeficient mice (Zhang et al., 2011Wong et al., 2011). Primary tumors direct the recruitment of bone marrow-derived cells to the lungs and other sites of metastasis (Kaplan et al., 2005). In breast cancer, hypoxia induces the expression of lysyl oxidase (LOX), a secreted protein that remodels collagen at sites of metastatic niche formation (Erler et al., 2009). In addition to LOX, breast cancers also express LOX-like proteins 2 and 4. LOX, LOXL2, and LOXL4 are all HIF-1-regulated genes and HIF-1 inhibition blocks metastatic niche formation regardless of which LOX/LOXL protein is expressed, whereas available LOX inhibitors are not effective against all LOXL proteins (Wong et al., 2011), again illustrating the role of HIF-1 as a master regulator that controls the expression of multiple genes involved in a single (patho)physiological process.

Translational Prospects

Small molecule inhibitors of HIF activity that have anti-cancer effects in mouse models have been identified (Table 1). Inhibition of HIF impairs both vascular and metabolic adaptations to hypoxia, which may decrease O2 delivery and increase O2 utilization. These drugs are likely to be useful (as components of multidrug regimens) in the treatment of a subset of cancer patients in whom high HIF activity is driving progression. As with all novel cancer therapeutics, successful translation will require the development of methods for identifying the appropriate patient cohort. Effects of combination drug therapy also need to be considered. VEGF receptor tyrosine kinase inhibitors, which induce tumor hypoxia by blocking vascularization, have been reported to increase metastasis in mouse models (Ebos et al., 2009), which may be mediated by HIF-1; if so, combined use of HIF-1 inhibitors with these drugs may prevent unintended counter-therapeutic effects.

HIF inhibitors may also be useful in the treatment of other diseases in which dysregulated HIF activity is pathogenic. Proof of principle has been established in mouse models of ocular neovascularization, a major cause of blindness in the developed world, in which systemic or intraocular injection of the HIF-1 inhibitor digoxin is therapeutic (Yoshida et al., 2010). Systemic administration of HIF inhibitors for cancer therapy would be contraindicated in patients who also have ischemic cardiovascular disease, in which HIF activity is protective. The analysis of SNPs at the HIF1A locus described above suggests that the population may include HIF hypo-responders, who are at increased risk of severe ischemic cardiovascular disease. It is also possible that HIF hyper-responders, such as individuals with hereditary erythrocytosis, are at increased risk of particularly aggressive cancer.

O2 and Evolution, Part 2

When lowlanders sojourn to high altitude, hypobaric hypoxia induces erythropoiesis, which is a relatively ineffective response because the problem is not insufficient red cells, but rather insufficient ambient O2. Chronic erythrocytosis increases the risk of heart attack, stroke, and fetal loss during pregnancy. Many high-altitude Tibetans maintain the same hemoglobin concentration as lowlanders and yet, despite severe hypoxemia, they also maintain aerobic metabolism. The basis for this remarkable evolutionary adaptation appears to have involved the selection of genetic variants at multiple loci encoding components of the oxygen sensing system, particularly HIF-2α (Beall et al., 2010Simonson et al., 2010Yi et al., 2010). Given that hereditary erythrocytosis is associated with modest HIF-2α gain-of-function, the Tibetan genotype associated with absence of an erythrocytotic response to hypoxia may encode reduced HIF-2α activity along with other alterations that increase metabolic efficiency. Delineating the molecular mechanisms underlying these metabolic adaptations may lead to novel therapies for ischemic disorders, illustrating the importance of oxygen homeostasis as a nexus where evolution, biology, and medicine converge.

7.9.4 Hypoxia-inducible factor 1. Regulator of mitochondrial metabolism and mediator of ischemic preconditioning

Semenza GL1.
Biochim Biophys Acta. 2011 Jul; 1813(7):1263-8.
http://dx.doi.org/10.1016%2Fj.bbamcr.2010.08.006

Hypoxia-inducible factor 1 (HIF-1) mediates adaptive responses to reduced oxygen availability by regulating gene expression. A critical cell-autonomous adaptive response to chronic hypoxia controlled by HIF-1 is reduced mitochondrial mass and/or metabolism. Exposure of HIF-1-deficient fibroblasts to chronic hypoxia results in cell death due to excessive levels of reactive oxygen species (ROS). HIF-1 reduces ROS production under hypoxic conditions by multiple mechanisms including: a subunit switch in cytochrome c oxidase from the COX4-1 to COX4-2 regulatory subunit that increases the efficiency of complex IV; induction of pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; induction of BNIP3, which triggers mitochondrial selective autophagy; and induction of microRNA-210, which blocks assembly of Fe/S clusters that are required for oxidative phosphorylation. HIF-1 is also required for ischemic preconditioning and this effect may be due in part to its induction of CD73, the enzyme that produces adenosine. HIF-1-dependent regulation of mitochondrial metabolism may also contribute to the protective effects of ischemic preconditioning.

The story of life on Earth is a tale of oxygen production and utilization. Approximately 3 billion years ago, primitive single-celled organisms evolved the capacity for photosynthesis, a biochemical process in which photons of solar energy are captured by chlorophyll and used to power the reaction of CO2 and H2O to form glucose and O2. The subsequent rise in the atmospheric O2 concentration over the next billion years set the stage for the ascendance of organisms with the capacity for respiration, a process that consumes glucose and O2 and generates CO2, H2O, and energy in the form of ATP. Some of these single-celled organisms eventually took up residence within the cytoplasm of other cells and devoted all of their effort to energy production as mitochondria. Compared to the conversion of glucose to lactate by glycolysis, the complete oxidation of glucose by respiration provided such a large increase in energy production that it made possible the evolution of multicellular organisms. Among metazoan organisms, the progressive increase in body size during evolution was accompanied by progressively more complex anatomic structures that function to ensure the adequate delivery of O2 to all cells, ultimately resulting in the sophisticated circulatory and respiratory systems of vertebrates.

All metazoan cells can sense and respond to reduced O2 availability (hypoxia). Adaptive responses to hypoxia can be cell autonomous, such as the alterations in mitochondrial metabolism that are described below, or non-cell-autonomous, such as changes in tissue vascularization (reviewed in ref. 1). Primary responses to hypoxia need to be distinguished from secondary responses to sequelae of hypoxia, such as the adaptive responses to ATP depletion that are mediated by AMP kinase (reviewed in ref 2). In contrast, recent data suggest that O2 and redox homeostasis are inextricably linked and that changes in oxygenation are inevitably associated with changes in the levels of reactive oxygen species (ROS), as will be discussed below.

HIF-1 Regulates Oxygen Homeostasis in All Metazoan Species

A key regulator of the developmental and physiological networks required for the maintenance of O2homeostasis is hypoxia-inducible factor 1 (HIF-1). HIF-1 is a heterodimeric transcription factor that is composed of an O2-regulated HIF-1α subunit and a constitutively expressed HIF-1β subunit [3,4]. HIF-1 regulates the expression of hundreds of genes through several major mechanisms. First, HIF-1 binds directly to hypoxia response elements, which are cis-acting DNA sequences located within target genes [5]. The binding of HIF-1 results in the recruitment of co-activator proteins that activate gene transcription (Fig. 1A). Only rarely does HIF-1 binding result in transcriptional repression [6]. Instead, HIF-1 represses gene expression by indirect mechanisms, which are described below. Second, among the genes activated by HIF-1 are many that encode transcription factors [7], which when synthesized can bind to and regulate (either positively or negatively) secondary batteries of target genes (Fig. 1B). Third, another group of HIF-1 target genes encode members of the Jumonji domain family of histone demethylases [8,9], which regulate gene expression by modifying chromatin structure (Fig. 1C). Fourth, HIF-1 can activate the transcription of genes encoding microRNAs [10], which bind to specific mRNA molecules and either block their translation or mediate their degradation (Fig. 1D). Fifth, the isolated HIF-1α subunit can bind to other transcription factors [11,12] and inhibit (Fig. 1E) or potentiate (Fig. 1F) their activity.

Mechanisms by which HIF-1 regulates gene expression. nihms232046f1

Mechanisms by which HIF-1 regulates gene expression. nihms232046f1

Mechanisms by which HIF-1 regulates gene expression.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3010308/bin/nihms232046f1.gif

Fig. 1 Mechanisms by which HIF-1 regulates gene expression. (A) Top: HIF-1 binds directly to target genes at a cis-acting hypoxia response element (HRE) and recruits coactivator proteins such as p300 to increase gene transcription.

HIF-1α and HIF-1β are present in all metazoan species, including the simple roundworm Caenorhabitis elegans [13], which consists of ~103 cells and has no specialized systems for O2 delivery. The fruit flyDrosophila melanogaster evolved tracheal tubes, which conduct air into the interior of the body from which it diffuses to surrounding cells. In vertebrates, the development of the circulatory and respiratory systems was accompanied by the appearance of HIF-2α, which is also O2-regulated and heterodimerizes with HIF-1β [14] but is only expressed in a restricted number of cell types [15], whereas HIF-1α and HIF-1β are expressed in all human and mouse tissues [16]. In Drosophila, the ubiquitiously expressed HIF-1α ortholog is designatedSimilar [17] and the paralogous gene that is expressed specifically in tracheal tubes is designated Trachealess[18].

HIF-1 Activity is Regulated by Oxygen

In the presence of O2, HIF-1α and HIF-2α are subjected to hydroxylation by prolyl-4-hydroxylase domain proteins (PHDs) that use O2 and α-ketoglutarate as substrates and generate CO2 and succinate as by-products [19]. Prolyl hydroxylation is required for binding of the von Hipple-Lindau protein, which recruits a ubiquitin-protein ligase that targets HIF-1α and HIF-2α for proteasomal degradation (Fig. 2). Under hypoxic conditions, the rate of hydroxylation declines and the non-hydroxylated proteins accumulate. HIF-1α transactivation domain function is also O2-regulated [20,21]. Factor inhibiting HIF-1 (FIH-1) represses transactivation domain function [22] by hydroxylating asparagine residue 803 in HIF-1α, thereby blocking the binding of the co-activators p300 and CBP [23].

Negative regulation of HIF-1 activity by oxygen nihms232046f2

Negative regulation of HIF-1 activity by oxygen nihms232046f2

Negative regulation of HIF-1 activity by oxygen

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3010308/bin/nihms232046f2.gif

Fig. 2 Negative regulation of HIF-1 activity by oxygen. Top: In the presence of O2: prolyl hydroxylation of HIF-1a leads to binding of the von Hippel-Lindau protein (VHL), which recruits a ubiquitin protein-ligase that targets HIF-1a for proteasomal degradation;

When cells are acutely exposed to hypoxic conditions, the generation of ROS at complex III of the mitochondrial electron transport chain (ETC) increases and is required for the induction of HIF-1α protein levels [24]. More than a decade after these observations were first made, the precise mechanism by which hypoxia increases ROS generation and by which ROS induces HIF-1α accumulation remain unknown. However, the prolyl and asparaginyl hydroxylases contain Fe2+ in their active site and oxidation to Fe3+would block their catalytic activity. Since O2 is a substrate for the hydroxylation reaction, anoxia also results in a loss of enzyme activity. However, the concentration at which O2 becomes limiting for prolyl or asparaginyl hydroxylase activity in vivo is not known.

HIF-1 Regulates the Balance Between Oxidative and Glycolytic Metabolism

All metazoan organisms depend on mitochondrial respiration as the primary mechanism for generating sufficient amounts of ATP to maintain cellular and systemic homeostasis. Respiration, in turn, is dependent on an adequate supply of O2 to serve as the final electron acceptor in the ETC. In this process, electrons are transferred from complex I (or complex II) to complex III, then to complex IV, and finally to O2, which is reduced to water. This orderly transfer of electrons generates a proton gradient across the inner mitochondrial membrane that is used to drive the synthesis of ATP. At each step of this process, some electrons combine with O2 prematurely, resulting in the production of superoxide anion, which is reduced to hydrogen peroxide through the activity of mitochondrial superoxide dismutase. The efficiency of electron transport appears to be optimized to the physiological range of O2 concentrations, such that ATP is produced without the production of excess superoxide, hydrogen peroxide, and other ROS at levels that would result in the increased oxidation of cellular macromolecules and subsequent cellular dysfunction or death. In contrast, when O2levels are acutely increased or decreased, an imbalance between O2 and electron flow occurs, which results in increased ROS production.

MEFs require HIF-1 activity to make two critical metabolic adaptations to chronic hypoxia. First, HIF-1 activates the gene encoding pyruvate dehydrogenase (PDH) kinase 1 (PDK1), which phosphorylates and inactivates the catalytic subunit of PDH, the enzyme that converts pyruvate to acetyl coenzyme A (AcCoA) for entry into the mitochondrial tricarboxylic acid (TCA) cycle [25]. Second, HIF-1 activates the gene encoding BNIP3, a member of the Bcl-2 family of mitochondrial proteins, which triggers selective mitochondrial autophagy [26]. Interference with the induction of either of these proteins in hypoxic cells results in increased ROS production and increased cell death. Overexpression of either PDK1 or BNIP3 rescues HIF-1α-null MEFs. By shunting pyruvate away from the mitochondria, PDK1 decreases flux through the ETC and thereby counteracts the reduced efficiency of electron transport under hypoxic conditions, which would otherwise increase ROS production. PDK1 functions cooperatively with the product of another HIF-1 target gene, LDHA [27], which converts pyruvate to lactate, thereby further reducing available substrate for the PDH reaction.

PDK1 effectively reduces flux through the TCA cycle and thereby reduces flux through the ETC in cells that primarily utilize glucose as a substrate for oxidative phosphorylation. However, PDK1 is predicted to have little effect on ROS generation in cells that utilize fatty acid oxidation as their source of AcCoA. Hence another strategy to reduce ROS generation under hypoxic conditions is selective mitochondrial autophagy [26]. MEFs reduce their mitochondrial mass and O2 consumption by >50% after only two days at 1% O2. BNIP3 competes with Beclin-1 for binding to Bcl-2, thereby freeing Beclin-1 to activate autophagy. Using short hairpin RNAs to knockdown expression of BNIP3, Beclin-1, or Atg5 (another component of the autophagy machinery) phenocopied HIF-1α-null cells by preventing hypoxia-induced reductions in mitochondrial mass and O2 consumption as a result of failure to induce autophagy [26]. HIF-1-regulated expression of BNIP3L also contributes to hypoxia-induced autophagy [28]. Remarkably, mice heterozygous for the HIF-1α KO allele have a significantly increased ratio of mitochondrial:nuclear DNA in their lungs (even though this is the organ that is exposed to the highest O2 concentrations), indicating that HIF-1 regulates mitochondrial mass under physiological conditions in vivo [26]. In contrast to the selective mitochondrial autophagy that is induced in response to hypoxia as described above, autophagy (of unspecified cellular components) induced by anoxia does not require HIF-1, BNIP3, or BNIP3L, but is instead regulated by AMP kinase [29].

The multiplicity of HIF-1-mediated mechanisms identified so far by which cells regulate mitochondrial metabolism in response to changes in cellular O2 concentration (Fig. 3) suggests that this is a critical adaptive response to hypoxia. The fundamental nature of this physiological response is underscored by the fact that yeast also switch COX4 subunits in an O2-dependent manner but do so by an entirely different molecular mechanism [33], since yeast do not have a HIF-1α homologue. Thus, it appears that by convergent evolution both unicellular and multicellular eukaryotes possess mechanisms by which they modulate mitochondrial metabolism to maintain redox homeostasis despite changes in O2 availability. Indeed, it is the balance between energy, oxygen, and redox homeostasis that represents the key to life with oxygen.

Regulation of mitochondrial metabolism by HIF-1  nihms232046f3

Regulation of mitochondrial metabolism by HIF-1 nihms232046f3

Regulation of mitochondrial metabolism by HIF-1α

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Fig. 3 Regulation of mitochondrial metabolism by HIF-1α. Acute hypoxia leads to increased mitochondrial generation of reactive oxygen species (ROS). Decreased O2 and increased ROS levels lead to decreased HIF-1α hydroxylation (see Fig. 2) and increased HIF-1-dependent 

 

7.9.5 Regulation of cancer cell metabolism by hypoxia-inducible factor 1

Semenza GL1.
Semin Cancer Biol. 2009 Feb; 19(1):12-6.

The Warburg Effect: The Re-discovery of the Importance of Aerobic Glycolysis in Tumor Cells
http://dx.doi.org:/10.1016/j.semcancer.2008.11.009

The induction of hypoxia-inducible factor 1 (HIF-1) activity, either as a result of intratumoral hypoxia or loss-of-function mutations in the VHL gene, leads to a dramatic reprogramming of cancer cell metabolism involving increased glucose transport into the cell, increased conversion of glucose to pyruvate, and a concomitant decrease in mitochondrial metabolism and mitochondrial mass. Blocking these adaptive metabolic responses to hypoxia leads to cell death due to toxic levels of reactive oxygen species. Targeting HIF-1 or metabolic enzymes encoded by HIF-1 target genes may represent a novel therapeutic approach to cancer.

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7.9.6 Coming up for air. HIF-1 and mitochondrial oxygen consumption

Simon MC1.
Cell Metab. 2006 Mar;3(3):150-1.
http://dx.doi.org/10.1016/j.cmet.2006.02.007

Hypoxic cells induce glycolytic enzymes; this HIF-1-mediated metabolic adaptation increases glucose flux to pyruvate and produces glycolytic ATP. Two papers in this issue of Cell Metabolism (Kim et al., 2006; Papandreou et al., 2006) demonstrate that HIF-1 also influences mitochondrial function, suppressing both the TCA cycle and respiration by inducing pyruvate dehydrogenase kinase 1 (PDK1). PDK1 regulation in hypoxic cells promotes cell survival.

Comment on

Oxygen deprivation (hypoxia) occurs in tissues when O2 supply via the cardiovascular system fails to meet the demand of O2-consuming cells. Hypoxia occurs naturally in physiological settings (e.g., embryonic development and exercising muscle), as well as in pathophysiological conditions (e.g., myocardial infarction, inflammation, and solid tumor formation). For over a century, it has been appreciated that O2-deprived cells exhibit increased conversion of glucose to lactate (the “Pasteur effect”). Activation of the Pasteur effect during hypoxia in mammalian cells is facilitated by HIF-1, which mediates the upregulation of glycolytic enzymes that support an increase in glycolytic ATP production as mitochondria become starved for O2, the substrate for oxidative phosphorylation (Seagroves et al., 2001). Thus, mitochondrial respiration passively decreases due to O2 depletion in hypoxic tissues. However, reports by Kim et al. (2006) and Papandreou et al. (2006) in this issue of Cell Metabolism demonstrate that this critical metabolic adaptation is more complex and includes an active suppression of mitochondrial pyruvate catabolism and O2consumption by HIF-1.

Mitochondrial oxidative phosphorylation is regulated by multiple mechanisms, including substrate availability. Major substrates include O2 (the terminal electron acceptor) and pyruvate (the primary carbon source). Pyruvate, as the end product of glycolysis, is converted to acetyl-CoA by the pyruvate dehydrogenase enzymatic complex and enters the tricarboxylic acid (TCA) cycle. Pyruvate conversion into acetyl-CoA is irreversible; this therefore represents an important regulatory point in cellular energy metabolism. Pyruvate dehydrogenase kinase (PDK) inhibits pyruvate dehydrogenase activity by phosphorylating its E1 subunit (Sugden and Holness, 2003). In the manuscripts by Kim et al. (2006) and Papandreou et al. (2006), the authors find that PDK1 is a HIF-1 target gene that actively regulates mitochondrial respiration by limiting pyruvate entry into the TCA cycle. By excluding pyruvate from mitochondrial metabolism, hypoxic cells accumulate pyruvate, which is then converted into lactate via lactate dehydrogenase (LDH), another HIF-1-regulated enzyme. Lactate in turn is released into the extracellular space, regenerating NAD+ for continued glycolysis by O2-starved cells (see Figure 1). This HIF-1-dependent block to mitochondrial O2 consumption promotes cell survival, especially when O2 deprivation is severe and prolonged.

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multiple-hypoxia-induced-cellular-metabolic-changes-are-regulated-by-hif-1

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Figure 1. Multiple hypoxia-induced cellular metabolic changes are regulated by HIF-1

By stimulating the expression of glucose transporters and glycolytic enzymes, HIF-1 promotes glycolysis to generate increased levels of pyruvate. In addition, HIF-1 promotes pyruvate reduction to lactate by activating lactate dehydrogenase (LDH). Pyruvate reduction to lactate regenerates NAD+, which permits continued glycolysis and ATP production by hypoxic cells. Furthermore, HIF-1 induces pyruvate dehydrogenase kinase 1 (PDK1), which inhibits pyruvate dehydrogenase and blocks conversion of pyruvate to acetyl CoA, resulting in decreased flux through the tricarboxylic acid (TCA) cycle. Decreased TCA cycle activity results in attenuation of oxidative phosphorylation and excessive mitochondrial reactive oxygen species (ROS) production. Because hypoxic cells already exhibit increased ROS, which have been shown to promote HIF-1 accumulation, the induction of PDK1 prevents the persistence of potentially harmful ROS levels.

Papandreou et al. demonstrate that hypoxic regulation of PDK has important implications for antitumor therapies. Recent interest has focused on cytotoxins that target hypoxic cells in tumor microenvironments, such as the drug tirapazamine (TPZ). Because intracellular O2 concentrations are decreased by mitochondrial O2 consumption, HIF-1 could protect tumor cells from TPZ-mediated cell death by maintaining intracellular O2 levels. Indeed, Papandreou et al. show that HIF-1-deficient cells grown at 2% O2 exhibit increased sensitivity to TPZ relative to wild-type cells, presumably due to higher rates of mitochondrial O2 consumption. HIF-1 inhibition in hypoxic tumor cells should have multiple therapeutic benefits, but the use of HIF-1 inhibitors in conjunction with other treatments has to be carefully evaluated for the most effective combination and sequence of drug delivery. One result of HIF-1 inhibition would be a relative decrease in intracellular O2 levels, making hypoxic cytotoxins such as TPZ more potent antitumor agents. Because PDK expression has been detected in multiple human tumor samples and appears to be induced by hypoxia (Koukourakis et al., 2005), small molecule inhibitors of HIF-1 combined with TPZ represent an attractive therapeutic approach for future clinical studies.

Hypoxic regulation of PDK1 has other important implications for cell survival during O2 depletion. Because the TCA cycle is coupled to electron transport, Kim et al. suggest that induction of the pyruvate dehydrogenase complex by PDK1 attenuates not only mitochondrial respiration but also the production of mitochondrial reactive oxygen species (ROS) in hypoxic cells. ROS are a byproduct of electron transfer to O2, and cells cultured at 1 to 5% O2 generate increased mitochondrial ROS relative to those cultured at 21% O2 (Chandel et al., 1998 and Guzy et al., 2005). In fact, hypoxia-induced mitochondrial ROS have also been shown to be necessary for the stabilization of HIF-1 in hypoxic cells (Brunelle et al., 2005Guzy et al., 2005 and Mansfield et al., 2005). However, the persistence of ROS could ultimately be lethal to tissues during chronic O2 deprivation, and PDK1 induction by HIF-1 should promote cell viability during long-term hypoxia. Kim et al. present evidence that HIF-1-deficient cells exhibit increased apoptosis after 72 hr of culture at 0.5% O2 compared to wild-type cells and that cell survival is rescued by enforced expression of exogenous PDK1. Furthermore, PDK1 reduces ROS production by the HIF-1 null cells. These findings support a novel prosurvival dimension of cellular hypoxic adaptation where PDK1 inhibits the TCA cycle, mitochondrial respiration, and chronic ROS production.

The HIF-1-mediated block to mitochondrial O2 consumption via PDK1 regulation also has implications for O2-sensing pathways by hypoxic cells. One school of thought suggests that perturbing mitochondrial O2consumption increases intracellular O2 concentrations and suppresses HIF-1 induction by promoting the activity of HIF prolyl hydroxylases, the O2-dependent enzymes that regulate HIF-1 stability (Hagen et al., 2003 and Doege et al., 2005). This model suggests that mitochondria function as “O2 sinks.” Although Papandreou et al. demonstrate that increased mitochondrial respiration due to PDK1 depletion results in decreased intracellular O2 levels (based on pimonidazole staining), these changes failed to reduce HIF-1 levels in hypoxic cells. Another model for hypoxic activation of HIF-1 describes a critical role for mitochondrial ROS in prolyl hydroxylase inhibition and HIF-1 stabilization in O2-starved cells (Brunelle et al., 2005Guzy et al., 2005 and Mansfield et al., 2005) (see Figure 1). The mitochondrial “O2 sink” hypothesis can account for some observations in the literature but fails to explain the inhibition of HIF-1 stabilization by ROS scavengers (Chandel et al., 1998Brunelle et al., 2005Guzy et al., 2005 and Sanjuán-Pla et al., 2005). While the relationship between HIF-1 stability, mitochondrial metabolism, ROS, and intracellular O2 redistribution will continue to be debated for some time, these most recent findings shed new light on findings by Louis Pasteur over a century ago.

Selected reading

Brunelle et al., 2005

J.K. Brunelle, E.L. Bell, N.M. Quesada, K. Vercauteren, V. Tiranti, M. Zeviani, R.C. Scarpulla, N.S. Chandel

Cell Metab., 1 (2005), pp. 409–414

Article  PDF (324 K) View Record in Scopus Citing articles (357)

Chandel et al., 1998

N.S. Chandel, E. Maltepe, E. Goldwasser, C.E. Mathieu, M.C. Simon, P.T. Schumacker

Proc. Natl. Acad. Sci. USA, 95 (1998), pp. 11715–11720

View Record in Scopus Full Text via CrossRef Citing articles (973)

Doege et al., 2005Doege, S. Heine, I. Jensen, W. Jelkmann, E. Metzen

Blood, 106 (2005), pp. 2311–2317

View Record in Scopus Full Text via CrossRef Citing articles (84)

Guzy et al., 2005

R.D. Guzy, B. Hoyos, E. Robin, H. Chen, L. Liu, K.D. Mansfield, M.C. Simon, U. Hammerling, P.T. Schumacker

Cell Metab., 1 (2005), pp. 401–408

Article  PDF (510 K) View Record in Scopus Citing articles (593)

Hagen et al., 2003

Hagen, C.T. Taylor, F. Lam, S. Moncada

Science, 302 (2003), pp. 1975–1978

View Record in Scopus Full Text via CrossRef Citing articles (450)

7.9.7 HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption

Papandreou I1Cairns RAFontana LLim ALDenko NC.
Cell Metab. 2006 Mar; 3(3):187-97.
http://dx.doi.org/10.1016/j.cmet.2006.01.012

The HIF-1 transcription factor drives hypoxic gene expression changes that are thought to be adaptive for cells exposed to a reduced-oxygen environment. For example, HIF-1 induces the expression of glycolytic genes. It is presumed that increased glycolysis is necessary to produce energy when low oxygen will not support oxidative phosphorylation at the mitochondria. However, we find that while HIF-1 stimulates glycolysis, it also actively represses mitochondrial function and oxygen consumption by inducing pyruvate dehydrogenase kinase 1 (PDK1). PDK1 phosphorylates and inhibits pyruvate dehydrogenase from using pyruvate to fuel the mitochondrial TCA cycle. This causes a drop in mitochondrial oxygen consumption and results in a relative increase in intracellular oxygen tension. We show by genetic means that HIF-1-dependent block to oxygen utilization results in increased oxygen availability, decreased cell death when total oxygen is limiting, and reduced cell death in response to the hypoxic cytotoxin tirapazamine.

Comment in

Tissue hypoxia results when supply of oxygen from the bloodstream does not meet demand from the cells in the tissue. Such a supply-demand mismatch can occur in physiologic conditions such as the exercising muscle, in the pathologic condition such as the ischemic heart, or in the tumor microenvironment (Hockel and Vaupel, 2001 and Semenza, 2004). In either the physiologic circumstance or pathologic conditions, there is a molecular response from the cell in which a program of gene expression changes is initiated by the hypoxia-inducible factor-1 (HIF-1) transcription factor. This program of gene expression changes is thought to help the cells adapt to the stressful environment. For example, HIF-1-dependent expression of erythropoietin and angiogenic compounds results in increased blood vessel formation for delivery of a richer supply of oxygenated blood to the hypoxic tissue. Additionally, HIF-1 induction of glycolytic enzymes allows for production of energy when the mitochondria are starved of oxygen as a substrate for oxidative phosphorylation. We now find that this metabolic adaptation is more complex, with HIF-1 not only regulating the supply of oxygen from the bloodstream, but also actively regulating the oxygen demand of the tissue by reducing the activity of the major cellular consumer of oxygen, the mitochondria.

Perhaps the best-studied example of chronic hypoxia is the hypoxia associated with the tumor microenvironment (Brown and Giaccia, 1998). The tumor suffers from poor oxygen supply through a chaotic jumble of blood vessels that are unable to adequately perfuse the tumor cells. The oxygen tension within the tumor is also a function of the demand within the tissue, with oxygen consumption influencing the extent of tumor hypoxia (Gulledge and Dewhirst, 1996 and Papandreou et al., 2005b). The net result is that a large fraction of the tumor cells are hypoxic. Oxygen tensions within the tumor range from near normal at the capillary wall, to near zero in the perinecrotic regions. This perfusion-limited hypoxia is a potent microenvironmental stress during tumor evolution (Graeber et al., 1996 and Hockel and Vaupel, 2001) and an important variable capable of predicting for poor patient outcome. (Brizel et al., 1996Cairns and Hill, 2004Hockel et al., 1996 and Nordsmark and Overgaard, 2004).

The HIF-1 transcription factor was first identified based on its ability to activate the erythropoetin gene in response to hypoxia (Wang and Semenza, 1993). Since then, it is has been shown to be activated by hypoxia in many cells and tissues, where it can induce hypoxia-responsive target genes such as VEGF and Glut1 (Airley et al., 2001 and Kimura et al., 2004). The connection between HIF-regulation and human cancer was directly linked when it was discovered that the VHL tumor suppressor gene was part of the molecular complex responsible for the oxic degradation of HIF-1α (Maxwell et al., 1999). In normoxia, a family of prolyl hydroxylase enzymes uses molecular oxygen as a substrate and modifies HIF-1α and HIF2α by hydroxylation of prolines 564 and 402 (Bruick and McKnight, 2001 and Epstein et al., 2001). VHL then recognizes the modified HIF-α proteins, acts as an E3-type of ubiquitin ligase, and along with elongins B and C is responsible for the polyubiquitination of HIF-αs and their proteosomal degradation (Bruick and McKnight, 2001Chan et al., 2002Ivan et al., 2001 and Jaakkola et al., 2001). Mutations in VHL lead to constitutive HIF-1 gene expression, and predispose humans to cancer. The ability to recognize modified HIF-αs is at least partly responsible for VHL activity as a tumor suppressor, as introduction of nondegradable HIF-2α is capable of overcoming the growth–inhibitory activity of wild-type (wt) VHL in renal cancer cells (Kondo et al., 2003).

Mitochondrial function can be regulated by PDK1 expression. Mitochondrial oxidative phosphorylation (OXPHOS) is regulated by several mechanisms, including substrate availability (Brown, 1992). The major substrates for OXPHOS are oxygen, which is the terminal electron acceptor, and pyruvate, which is the primary carbon source. Pyruvate is the end product of glycolysis and is converted to acetyl-CoA through the activity of the pyruvate dehydrogenase complex of enzymes. The acetyl-CoA then directly enters the TCA cycle at citrate synthase where it is combined with oxaloacetate to generate citrate. In metazoans, the conversion of pyruvate to acetyl-CoA is irreversible and therefore represents a critical regulatory point in cellular energy metabolism. Pyruvate dehydrogenase is regulated by three known mechanisms: it is inhibited by acetyl-CoA and NADH, it is stimulated by reduced energy in the cell, and it is inhibited by regulatory phosphorylation of its E1 subunit by pyruvate dehydrogenase kinase (PDK) (Holness and Sugden, 2003 and Sugden and Holness, 2003). There are four members of the PDK family in vertebrates, each with specific tissue distributions (Roche et al., 2001). PDK expression has been observed in human tumor biopsies (Koukourakis et al., 2005), and we have reported that PDK3 is hypoxia-inducible in some cell types (Denko et al., 2003). In this manuscript, we find that PDK1 is also a hypoxia-responsive protein that actively regulates the function of the mitochondria under hypoxic conditions by reducing pyruvate entry into the TCA cycle. By excluding pyruvate from mitochondrial consumption, PDK1 induction may increase the conversion of pyruvate to lactate, which is in turn shunted to the extracellular space, regenerating NAD for continued glycolysis.

Identification of HIF-dependent mitochondrial proteins through genomic and bioinformatics approaches

In order to help elucidate the role of HIF-1α in regulating metabolism, we undertook a genomic search for genes that were regulated by HIF-1 in tumor cells exposed to hypoxia in vitro. We used genetically matched human RCC4 cells that had lost VHL during tumorigenesis and displayed constitutive HIF-1 activity, and a cell line engineered to re-express VHL to establish hypoxia-dependent HIF activation. These cells were treated with 18 hr of stringent hypoxia (<0.01% oxygen), and microarray analysis performed. Using a strict 2.5-fold elevation as our cutoff, we identified 173 genes that were regulated by hypoxia and/or VHL status (Table S1 in the Supplemental Data available with this article online). We used the pattern of expression in these experiments to identify putative HIF-regulated genes—ones that were constitutively elevated in the parent RCC4s independent of hypoxia, downregulated in the RCC4VHL cells under normoxia, and elevated in response to hypoxia. Of the 173 hypoxia and VHL-regulated genes, 74 fit the putative HIF-1 target pattern. The open reading frames of these genes were run through a pair of bioinformatics engines in order to predict subcellular localization, and 10 proteins scored as mitochondrial on at least one engine. The genes, fold induction, and mitochondrial scores are listed in Table 1.

HIF-1 downregulates mitochondrial oxygen consumption

Having identified several putative HIF-1 responsive gene products that had the potential to regulate mitochondrial function, we then directly measured mitochondrial oxygen consumption in cells exposed to long-term hypoxia. While other groups have studied mitochondrial function under acute hypoxia (Chandel et al., 1997), this is one of the first descriptions of mitochondrial function after long-term hypoxia where there have been extensive hypoxia-induced gene expression changes. Figure 1A is an example of the primary oxygen trace from a Clark electrode showing a drop in oxygen concentration in cell suspensions of primary fibroblasts taken from normoxic and hypoxic cultures. The slope of the curve is a direct measure of the total cellular oxygen consumption rate. Exposure of either primary human or immortalized mouse fibroblasts to 24 hr of hypoxia resulted in a reduction of this rate by approximately 50% (Figures 1A and 1B). In these experiments, the oxygen consumption can be stimulated with the mitochondrial uncoupling agent CCCP (carbonyl cyanide 3-chloro phenylhydrazone) and was completely inhibited by 2 mM potassium cyanide. We determined that the change in total cellular oxygen consumption was due to changes in mitochondrial activity by the use of the cell-permeable poison of mitochondrial complex 3, Antimycin A. Figure 1C shows that the difference in the normoxic and hypoxic oxygen consumption in murine fibroblasts is entirely due to the Antimycin-sensitive mitochondrial consumption. The kinetics with which mitochondrial function slows in hypoxic tumor cells also suggests that it is due to gene expression changes because it takes over 6 hr to achieve maximal reduction, and the reversal of this repression requires at least another 6 hr of reoxygenation (Figure 1D). These effects are not likely due to proliferation or toxicity of the treatments as these conditions are not growth inhibitory or toxic to the cells (Papandreou et al., 2005a).

Since we had predicted from the gene expression data that the mitochondrial oxygen consumption changes were due to HIF-1-mediated expression changes, we tested several genetically matched systems to determine what role HIF-1 played in the process (Figure 2). We first tested the cell lines that had been used for microarray analysis and found that the parental RCC4 cells had reduced mitochondrial oxygen consumption when compared to the VHL-reintroduced cells. Oxygen consumption in the parental cells was insensitive to hypoxia, while it was reduced by hypoxia in the wild-type VHL-transfected cell lines. Interestingly, stable introduction of a tumor-derived mutant VHL (Y98H) that cannot degrade HIF was also unable to restore oxygen consumption. These results indicate that increased expression of HIF-1 is sufficient to reduce oxygen consumption (Figure 2A). We also investigated whether HIF-1 induction was required for the observed reduction in oxygen consumption in hypoxia using two genetically matched systems. We measured normoxic and hypoxic oxygen consumption in murine fibroblasts derived from wild-type or HIF-1α null embryos (Figure 2B) and from human RKO tumor cells and RKO cells constitutively expressing ShRNAs directed against the HIF-1α gene (Figures 2C and 4C). Neither of the HIF-deficient cell systems was able to reduce oxygen consumption in response to hypoxia. These data from the HIF-overexpressing RCC cells and the HIF-deficient cells indicate that HIF-1 is both necessary and sufficient for reducing mitochondrial oxygen consumption in hypoxia.

HIF-dependent mitochondrial changes are functional, not structural

Because addition of CCCP could increase oxygen consumption even in the hypoxia-treated cells, we hypothesized that the hypoxic inhibition was a regulated activity, not a structural change in the mitochondria in response to hypoxic stress. We confirmed this interpretation by examining several additional mitochondrial characteristics in hypoxic cells such as mitochondrial morphology, quantity, and membrane potential. We examined morphology by visual inspection of both the transiently transfected mitochondrially localized DsRed protein and the endogenous mitochondrial protein cytochrome C. Both markers were indistinguishable in the parental RCC4 and the RCC4VHL cells (Figure 3A). Likewise, we measured the mitochondrial membrane potential with the functional dye rhodamine 123 and found that it was identical in the matched RCC4 cells and the matched HIF wt and knockout (KO) cells when cultured in normoxia or hypoxia (Figure 3B). Finally, we determined that the quantity of mitochondria per cell was not altered in response to HIF or hypoxia by showing that the amount of the mitochondrial marker protein HSP60 was identical in the RCC4 and HIF cell lines (Figure 3C)

PDK1 is a HIF-1 inducible target protein

After examination of the list of putative HIF-regulated mitochondrial target genes, we hypothesized that PDK1 could mediate the functional changes that we observed in hypoxia. We therefore investigated PDK1 protein expression in response to HIF and hypoxia in the genetically matched cell systems. Figure 4A shows that in the RCC4 cells PDK1 and the HIF-target gene BNip3 (Greijer et al., 2005 and Papandreou et al., 2005a) were both induced by hypoxia in a VHL-dependent manner, with the expression of PDK1 inversely matching the oxygen consumption measured in Figure 1 above. Likewise, the HIF wt MEFs show oxygen-dependent induction of PDK1 and BNip3, while the HIF KO MEFs did not show any expression of either of these proteins under any oxygen conditions (Figure 4B). Finally, the parental RKO cells were able to induce PDK1 and the HIF target gene BNip3L in response to hypoxia, while the HIF-depleted ShRNA RKO cells could not induce either protein (Figure 4C). Therefore, in all three cell types, the HIF-1-dependent regulation of oxygen consumption seen in Figure 2, corresponds to the HIF-1-dependent induction of PDK1 seen in Figure 4.

In order to determine if PDK1 was a direct HIF-1 target gene, we analyzed the genomic sequence flanking the 5′ end of the gene for possible HIF-1 binding sites based on the consensus core HRE element (A/G)CGTG (Caro, 2001). Several such sites exist within the first 400 bases upstream, so we generated reporter constructs by fusing the genomic sequence from −400 to +30 of the start site of transcription to the firefly luciferase gene. In transfection experiments, the chimeric construct showed significant induction by either cotransfection with a constitutively active HIF proline mutant (P402A/P564G) (Chan et al., 2002) or exposure of the transfected cells to 0.5% oxygen (Figure 4D). Most noteworthy, when the reporter gene was transfected into the HIF-1α null cells, it did not show induction when the cells were cultured in hypoxia, but it did show induction when cotransfected with expression HIF-1α plasmid. We then generated deletions down to the first 36 bases upstream of transcription and found that even this short sequence was responsive to HIF-1 (Figure 4D). Analysis of this small fragment showed only one consensus HRE site located in an inverted orientation in the 5′ untranslated region. We synthesized and cloned a mutant promoter fragment in which the core element ACGTG was replaced with AAAAG, and this construct lost over 90% of its hypoxic induction. These experiments suggest that it is this HRE within the proximal 5′ UTR that HIF-1 uses to transactivate the endogenous PDK1 gene in response to hypoxia.

PDK1 is responsible for the HIF-dependent mitochondrial oxygen consumption changes

In order to directly test if PDK1 was the HIF-1 target gene responsible for the hypoxic reduction in mitochondrial oxygen consumption, we generated RKO cell lines with either knockdown or overexpression of PDK1 and measured the oxygen consumption in these derivatives. The PDK1 ShRNA stable knockdown line was generated as a pool of clones cotransfected with pSUPER ShPDK1 and pTK-hygro resistance gene. After selection for growth in hygromycin, the cells were tested by Western blot for the level of PDK1 protein expression. We found that normoxic PDK1 is reduced by 75%, however, there was measurable expression of PDK1 in these cells in response to hypoxia (Figure 5A). When we measured the corresponding oxygen consumption in these cells, we found a change commensurate with the level of PDK1. The knockdown cells show elevated baseline oxygen consumption, and partial reduction in this activity in response to hypoxia. Therefore, reduction of PDK1 expression by genetic means increased mitochondrial oxygen consumption in both normoxic and hypoxic conditions. Interestingly, these cells still induced HIF-1α (Figure 5A) and HIF-1 target genes such as BNip3L in response to hypoxia (data not shown), suggesting that altered PDK1 levels do not alter HIF-1α function.

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PDK1 expression directly regulates cellular oxygen consumption rate

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Figure 5. PDK1 expression directly regulates cellular oxygen consumption rate

  1. A)Western blot of RKO cell and ShRNAPDK1RKO cell lysates after exposure to 24 hr of normoxia or 0.5% O2. Blots were probed for HIF 1α, PDK1, and tubulin as a loading control.
  2. B)Oxygen consumption rate in RKO and ShRNAPDK1RKO cells after exposure to 24 hr of normoxia or 0.5% O2.
  3. C)Western blot of RKOiresGUS cell and RKOiresPDK1 cell lysates after exposure to 24 hr of normoxia or 0.5% O2. Blots were probed for HIF 1α, PDK1, and tubulin as a loading control.
  4. D)Oxygen consumption rate in RKOiresGUS and RKOiresPDK1 cells after exposure to 24 hr of normoxia or 0.5% O2.
  5. E)Model describing the interconnected effects of HIF-1 target gene activation on hypoxic cell metabolism. Reduced oxygen conditions causes HIF-1 to coordinately induce the enzymes shown in boxes. HIF-1 activation results in increased glucose transporter expression to increase intracellular glucose flux, induction of glycolytic enzymes increases the conversion of glucose to pyruvate generating energy and NADH, induction of PDK1 decreases mitochondrial utilization of pyruvate and oxygen, and induction of LDH increases the removal of excess pyruvate as lactate and also regenerates NAD+ for increased glycolysis.

For all graphs, the error bars represent the standard error of the mean.

We also determined if overexpression of PDK1 could lead to reduced mitochondrial oxygen consumption. A separate culture of RKO cells was transfected with a PDK1-IRES-puro expression plasmid and selected for resistance to puromycin. The pool of puromycin resistant cells was tested for PDK1 expression by Western blot. These cells showed a modest increase in PDK1 expression under control conditions when compared to the cells transfected with GUS-IRES-puro, with an additional increase in PDK1 protein in response to hypoxia (Figure 5C). The corresponding oxygen consumption measurements showed that the mitochondria is very sensitive to changes in the levels of PDK1, as even this slight increase was able to significantly reduce oxygen consumption in the normoxic PDK1-puro cultures. Further increase in PDK1 levels with hypoxia further reduced oxygen consumption in both cultures (Figure 5D). The model describing the relationship between hypoxia, HIF-1, PDK1, and intermediate metabolism is described inFigure 5E.

Altering oxygen consumption alters intracellular oxygen tension and sensitivity to hypoxia-dependent cell killing

The intracellular concentration of oxygen is a net result of the rate at which oxygen diffuses into the cell and the rate at which it is consumed. We hypothesized that the rate at which oxygen was consumed within the cell would significantly affect its steady-state intracellular concentrations. We tested this hypothesis in vitro using the hypoxic marker drug pimonidazole (Bennewith and Durand, 2004). We plated high density cultures of HIF wild-type and HIF knockout cells and placed these cultures in normoxic, 2% oxygen, and anoxic incubators for overnight treatment. The overnight treatment gives the cells time to adapt to the hypoxic conditions and establish altered oxygen consumption profiles. Pimonidozole was then added for the last 4 hr of the growth of the culture. Pimonidazole binding was detected after fixation of the cells using an FITC labeled anti-pimonidazole antibody and it was quantitated by flow cytometry. The quantity of the bound drug is a direct indication of the oxygen concentration within the cell (Bennewith and Durand, 2004). The histograms in Figure 6A show that the HIF-1 knockout and wild-type cells show similar staining in the cells grown in 0% oxygen. However, the cells treated with 2% oxygen show the consequence of the genetic removal of HIF-1. The HIF-proficient cells showed relatively less pimonidazole binding at 2% when compared to the 0% culture, while the HIF-deficient cells showed identical binding between the cells at 2% and those at 0%. We interpret these results to mean that the HIF-deficient cells have greater oxygen consumption, and this has lowered the intracellular oxygenation from the ambient 2% to close to zero intracellularly. The HIF-proficient cells reduced their oxygen consumption rate so that the rate of diffusion into the cell is greater than the rate of consumption.

Figure 6. HIF-dependent decrease in oxygen consumption raises intracellular oxygen concentration, protects when oxygen is limiting, and decreases sensitivity to tirapazamine in vitro

  1. A)Pimonidazole was used to determine the intracellular oxygen concentration of cells in culture. HIF wt and HIF KO MEFs were grown at high density and exposed to 2% O2or anoxia for 24 hr in glass dishes. For the last 4 hr of treatment, cells were exposed to 60 μg/ml pimonidazole. Pimonidazole binding was quantitated by flow cytometry after binding of an FITC conjugated anti-pimo mAb. Results are representative of two independent experiments.
  2. B)HIF1α reduces oxygen consumption and protects cells when total oxygen is limited. HIF wt and HIF KO cells were plated at high density and sealed in aluminum jigs at <0.02% oxygen. At the indicated times, cells were harvested, and dead cells were quantitated by trypan blue exclusion. Note both cell lines are equally sensitive to anoxia-induced apoptosis, so the death of the HIF null cells indicates that the increased oxygen consumption removed any residual oxygen in the jig and resulted in anoxia-induced death.
  3. C)PDK1 is responsible for HIF-1’s adaptive response when oxygen is limiting. A similar jig experiment was performed to measure survival in the parental RKO, the RKO ShRNAHIF1α, and the RKOShPDK1 cells. Cell death by trypan blue uptake was measured 48 hr after the jigs were sealed.
  4. D)HIF status alters sensitivity to TPZ in vitro. HIF wt and HIF KO MEFs were grown at high density in glass dishes and exposed to 21%, 2%, and <0.01% O2conditions for 18 hr in the presence of varying concentrations of Tirapazamine. After exposure, cells were harvested and replated under normoxia to determine clonogenic viability. Survival is calculated relative to the plating efficiency of cells exposed to 0 μM TPZ for each oxygen concentration.
  5. E)Cell density alters sensitivity to TPZ. HIF wt and HIF KO MEFs were grown at varying cell densities in glass dishes and exposed to 2% O2in the presence of 10 μM TPZ for 18 hr. After the exposure, survival was determined as described in (C).

For all graphs, the error bars represent the standard error of the mean.

HIF-induced PDK1 can reduce the total amount of oxygen consumed per cell. The reduction in the amount of oxygen consumed could be significant if there is a finite amount of oxygen available, as would be the case in the hours following a blood vessel occlusion. The tissue that is fed by the vessel would benefit from being economical with the oxygen that is present. We experimentally modeled such an event using aluminum jigs that could be sealed with defined amounts of cells and oxygen present (Siim et al., 1996). We placed 10 × 106 wild-type or HIF null cells in the sealed jig at 0.02% oxygen, waited for the cells to consume the remaining oxygen, and measured cell viability. We have previously shown that these two cell types are resistant to mild hypoxia and equally sensitive to anoxia-induced apoptosis (Papandreou et al., 2005a). Therefore, any death in this experiment would be the result of the cells consuming the small amount of remaining oxygen and dying in response to anoxia. We found that in sealed jigs, the wild-type cells are more able to adapt to the limited oxygen supply by reducing consumption. The HIF null cells continued to consume oxygen, reached anoxic levels, and started to lose viability within 36 hr (Figure 6B). This is a secondary adaptive effect of HIF1. We confirmed that PDK1 was responsible for this difference by performing a similar experiment using the parental RKO cells, the RKOShRNAHIF1α and the RKOShRNAPDK1 cells. We found similar results in which both the cells with HIF1α knockdown and PDK1 knockdown were sensitive to the long-term effects of being sealed in a jig with a defined amount of oxygen (Figure 6c). Note that the RKOShPDK1 cells are even more sensitive than the RKOShHIF1α cells, presumably because they have higher basal oxygen consumption rates (Figure 5B).

Because HIF-1 can help cells adapt to hypoxia and maintain some intracellular oxygen level, it may also protect tumor cells from killing by the hypoxic cytotoxin tirapazamine (TPZ). TPZ toxicity is very oxygen dependent, especially at oxygen levels between 1%–4% (Koch, 1993). We therefore tested the relative sensitivity of the HIF wt and HIF KO cells to TPZ killing in high density cultures (Figure 6D). We exposed the cells to the indicated concentrations of drug and oxygen concentrations overnight. The cells were then harvested and replated to determine reproductive viability by colony formation. Both cell types were equally resistant to TPZ at 21% oxygen, while both cell types are equally sensitive to TPZ in anoxic conditions where intracellular oxygen levels are equivalent (Figure 6A). The identical sensitivity of both cell types in anoxia indicates that both cell types are equally competent in repairing the TPZ-induced DNA damage that is presumed to be responsible for its toxicity. However, in 2% oxygen cultures, the HIF null cells displayed a significantly greater sensitivity to the drug than the wild-type cells. This suggests that the increased oxygen consumption rate in the HIF-deficient cells is sufficient to lower the intracellular oxygen concentration relative to that in the HIF-proficient cells. The lower oxygen level is significant enough to dramatically sensitize these cells to killing by TPZ.

If the increased sensitivity to TPZ in the HIF ko cells is determined by intracellular oxygen consumption differences, then this effect should also be cell-density dependent. We showed that this is indeed the case in Figure 6E where oxygen and TPZ concentrations were held constant, and increased cell density lead to increased TPZ toxicity. The effect was much more pronounced in the HIF KO cells, although the HIF wt cells showed some increased toxicity in the highest density cultures, consistent with the fact they were still consuming some oxygen, even with HIF present (Figure 1). The in vitro TPZ survival data is therefore consistent with our hypothesis that control of oxygen consumption can regulate intracellular oxygen concentration, and suggests that increased oxygen consumption could sensitize cells to hypoxia-dependent therapy.

Discussion

The findings presented here show that HIF-1 is actively responsible for regulating energy production in hypoxic cells by an additional, previously unrecognized mechanism. It has been shown that HIF-1 induces the enzymes responsible for glycolysis when it was presumed that low oxygen did not support efficient oxidative phosphorylation (Iyer et al., 1998 and Seagroves et al., 2001). The use of glucose to generate ATP is capable of satisfying the energy requirements of a cell if glucose is in excess (Papandreou et al., 2005a). We now find that at the same time that glycolysis is increasing, mitochondrial respiration is decreasing. However, the decreased respiration is not because there is not enough oxygen present to act as a substrate for oxidative phosphorylation, but because the flow of pyruvate into the TCA cycle has been reduced by the activity of pyruvate dehydrogenase kinase. Other reports have suggested that oxygen utilization is shifted in cells exposed to hypoxia, but these reports have focused on other regulators such as nitric oxide synthase (Hagen et al., 2003). NO can reduce oxygen consumption through direct inhibition of cytochrome oxidase, but this effect seems to be more significant at physiologic oxygen concentrations, not at severe levels seen in the tumor (Palacios-Callender et al., 2004).

7.9.8 HIF-1. upstream and downstream of cancer metabolism

Semenza GL1.
Curr Opin Genet Dev. 2010 Feb; 20(1):51-6
http://dx.doi.org/10.1016%2Fj.gde.2009.10.009

Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression. Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression.

Metastatic cancer is characterized by reprogramming of cellular metabolism leading to increased uptake of glucose for use as both an anabolic and catabolic substrate. Increased glucose uptake is such a reliable feature that it is utilized clinically to detect metastases by positron emission tomography using 18F-fluorodeoxyglucose (FDG-PET) with a sensitivity of ~90% [1]. As with all aspects of cancer biology, the details of metabolic reprogramming differ widely among individual tumors. However, the role of specific signaling pathways and transcription factors in this process is now understood in considerable detail. This review will focus on the involvement of hypoxia-inducible factor 1 (HIF-1) in both mediating metabolic reprogramming and responding to metabolic alterations. The placement of HIF-1 both upstream and downstream of cancer metabolism results in a feed-forward mechanism that may play a major role in the development of the invasive, metastatic, and lethal cancer phenotype.

O2 concentrations are significantly reduced in many human cancers compared to the surrounding normal tissue. The median PO2 in breast cancers is ~10 mm Hg, as compared to ~65 mm Hg in normal breast tissue [2]. Reduced O2 availability induces HIF-1, which regulates the transcription of hundreds of genes [3*,4*] that encode proteins involved in every aspect of cancer biology, including: cell immortalization and stem cell maintenance; genetic instability; glucose and energy metabolism; vascularization; autocrine growth factor signaling; invasion and metastasis; immune evasion; and resistance to chemotherapy and radiation therapy [5].

HIF-1 is a transcription factor that consists of an O2-regulated HIF-1α and a constitutively expressed HIF-1β subunit [6]. In well-oxygenated cells, HIF-1α is hydroxylated on proline residue 402 (Pro-402) and/or Pro-564 by prolyl hydroxylase domain protein 2 (PHD2), which uses O2 and α-ketoglutarate as substrates in a reaction that generates CO2 and succinate as byproducts [7]. Prolyl-hydroxylated HIF-1α is bound by the von Hippel-Lindau tumor suppressor protein (VHL), which recruits an E3-ubiquitin ligase that targets HIF-1α for proteasomal degradation (Figure 1A). Asparagine 803 in the transactivation domain is hydroxylated in well-oxygenated cells by factor inhibiting HIF-1 (FIH-1), which blocks the binding of the coactivators p300 and CBP [7]. Under hypoxic conditions, the prolyl and asparaginyl hydroxylation reactions are inhibited by substrate (O2) deprivation and/or the mitochondrial generation of reactive oxygen species (ROS), which may oxidize Fe(II) present in the catalytic center of the hydroxylases [8].

HIF-1 and metabolism  nihms156580f1

HIF-1 and metabolism nihms156580f1

HIF-1 and metabolism

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2822127/bin/nihms156580f1.gif

Figure 1 HIF-1 and metabolism. (A) Regulation of HIF-1α protein synthesis and stability and HIF-1-dependent metabolic reprogramming. The rate of translation of HIF-1α mRNA into protein in cancer cells is dependent upon the activity of the mammalian 

The finding that acute changes in PO2 increase mitochondrial ROS production suggests that cellular respiration is optimized at physiological PO2 to limit ROS generation and that any deviation in PO2 — up or down — results in increased ROS generation. If hypoxia persists, induction of HIF-1 leads to adaptive mechanisms to reduce ROS and re-establish homeostasis, as described below. Prolyl and asparaginyl hydroxylation provide a molecular mechanism by which changes in cellular oxygenation can be transduced to the nucleus as changes in HIF-1 activity. This review will focus on recent advances in our understanding of the role of HIF-1 in controlling glucose and energy metabolism, but it should be appreciated that any increase in HIF-1 activity that leads to changes in cell metabolism will also affect many other critical aspects of cancer biology [5] that will not be addressed here.

HIF-1 target genes involved in glucose and energy metabolism

HIF-1 activates the transcription of SLC2A1 and SLC2A3, which encode the glucose transporters GLUT1 and GLUT3, respectively, as well as HK1 and HK2, which encode hexokinase, the first enzyme of the Embden-Meyerhoff (glycolytic) pathway [9]. Once taken up by GLUT and phosphorylated by HK, FDG cannot be metabolized further; thus, FDG-PET signal is determined by FDG delivery to tissue (i.e. perfusion) and GLUT/HK expression/activity. Unlike FDG, glucose is further metabolized to pyruvate by the action of the glycolytic enzymes, which are all encoded by HIF-1 target genes (Figure 1A). Glycolytic intermediates are also utilized for nucleotide and lipid synthesis [10]. Lactate dehydrogenase A (LDHA), which converts pyruvate to lactate, and monocarboxylate transporter 4 (MCT4), which transports lactate out of the cell (Figure 1B), are also regulated by HIF-1 [9,11]. Remarkably, lactate produced by hypoxic cancer cells can be taken up by non-hypoxic cells and used as a respiratory substrate [12**].

Pyruvate represents a critical metabolic control point, as it can be converted to acetyl coenzyme A (AcCoA) by pyruvate dehydrogenase (PDH) for entry into the tricarboxylic acid (TCA) cycle or it can be converted to lactate by LDHA (Figure 1B). Pyruvate dehydrogenase kinase (PDK), which phosphorylates and inactivates the catalytic domain of PDH, is encoded by four genes and PDK1 is activated by HIF-1 [13,14]. (Further studies are required to determine whether PDK2PDK3, or PDK4 is regulated by HIF-1.) As a result of PDK1 activation, pyruvate is actively shunted away from the mitochondria, which reduces flux through the TCA cycle, thereby reducing delivery of NADH and FADH2 to the electron transport chain. This is a critical adaptive response to hypoxia, because in HIF-1α–null mouse embryo fibroblasts (MEFs), PDK1 expression is not induced by hypoxia and the cells die due to excess ROS production, which can be ameliorated by forced expression of PDK1 [13]. MYC, which is activated in ~40% of human cancers, cooperates with HIF-1 to activate transcription of PDK1, thereby amplifying the hypoxic response [15]. Pharmacological inhibition of HIF-1 or PDK1 activity increases O2 consumption by cancer cells and increases the efficacy of a hypoxia-specific cytotoxin [16].

Hypoxia also induces mitochondrial autophagy in many human cancer cell lines through HIF-1-dependent expression of BNIP3 and a related BH3 domain protein, BNIP3L [19**]. Autocrine signaling through the platelet-derived growth factor receptor in cancer cells increases HIF-1 activity and thereby increases autophagy and cell survival under hypoxic conditions [21]. Autophagy may also occur in a HIF-1-independent manner in response to other physiological stimuli that are associated with hypoxic conditions, such as a decrease in the cellular ATP:AMP ratio, which activates AMP kinase signaling [22].

In clear cell renal carcinoma, VHL loss of function (LoF) results in constitutive HIF-1 activation, which is associated with impaired mitochondrial biogenesis that results from HIF-1-dependent expression of MXI1, which blocks MYC-dependent expression of PGC-1β, a coactivator that is required for mitochondrial biogenesis [23]. Inhibition of wild type MYC activity in renal cell carcinoma contrasts with the synergistic effect of HIF-1 and oncogenic MYC in activating PDK1 transcription [24].

Genetic and metabolic activators of HIF-1

Hypoxia plays a critical role in cancer progression [2,5] but not all cancer cells are hypoxic and a growing number of O2-independent mechanisms have been identified by which HIF-1 is induced [5]. Several mechanisms that are particularly relevant to cancer metabolism are described below.

Activation of mTOR

Alterations in mitochondrial metabolism

NAD+ levels

It is of interest that the NAD+-dependent deacetylase sirtuin 1 (SIRT1) was found to bind to, deacetylate, and increase transcriptional activation by HIF-2α but not HIF-1α [42**]. Another NAD+-dependent enzyme is poly(ADP-ribose) polymerase 1 (PARP1), which was recently shown to bind to HIF-1α and promote transactivation through a mechanism that required the enzymatic activity of PARP1 [43]. Thus, transactivation mediated by both HIF-1α and HIF-2α can be modulated according to NAD+ levels.

Nitric oxide

Increased expression of nitric oxide (NO) synthase isoforms and increased levels of NO have been shown to increase HIF-1α protein stability in human oral squamous cell carcinoma [44]. In prostate cancer, nuclear co-localization of endothelial NO synthase, estrogen receptor β, HIF-1α, and HIF-2α was associated with aggressive disease and the proteins were found to form chromatin complexes on the promoter of TERT gene encoding telomerase [45**]. The NOS2 gene encoding inducible NO synthase is HIF-1 regulated [5], suggesting another possible feed-forward mechanism.

7.9.9 In Vivo HIF-Mediated Reductive Carboxylation

Gameiro PA1Yang JMetelo AMPérez-Carro R, et al.
Cell Metab. 2013 Mar 5; 17(3):372-85.
http://dx.doi.org/10.1016%2Fj.cmet.2013.02.002

Hypoxic and VHL-deficient cells use glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate. To gain insights into the role of HIF and the molecular mechanisms underlying RC, we took advantage of a panel of disease-associated VHL mutants and showed that HIF expression is necessary and sufficient for the induction of RC in human renal cell carcinoma (RCC) cells. HIF expression drastically reduced intracellular citrate levels. Feeding VHL-deficient RCC cells with acetate or citrate or knocking down PDK-1 and ACLY restored citrate levels and suppressed RC. These data suggest that HIF-induced low intracellular citrate levels promote the reductive flux by mass action to maintain lipogenesis. Using [1–13C] glutamine, we demonstrated in vivo RC activity in VHL-deficient tumors growing as xenografts in mice. Lastly, HIF rendered VHL-deficient cells sensitive to glutamine deprivation in vitro, and systemic administration of glutaminase inhibitors suppressed the growth of RCC cells as mice xenografts.

Cancer cells undergo fundamental changes in their metabolism to support rapid growth, adapt to limited nutrient resources, and compete for these supplies with surrounding normal cells. One of the metabolic hallmarks of cancer is the activation of glycolysis and lactate production even in the presence of adequate oxygen. This is termed the Warburg effect, and efforts in cancer biology have revealed some of the molecular mechanisms responsible for this phenotype (Cairns et al., 2011). More recently, 13C isotopic studies have elucidated the complementary switch of glutamine metabolism that supports efficient carbon utilization for anabolism and growth (DeBerardinis and Cheng, 2010). Acetyl-CoA is a central biosynthetic precursor for lipid synthesis, being generated from glucose-derived citrate in well-oxygenated cells (Hatzivassiliou et al., 2005). Warburg-like cells, and those exposed to hypoxia, divert glucose to lactate, raising the question of how the tricarboxylic acid (TCA) cycle is supplied with acetyl-CoA to support lipogenesis. We and others demonstrated, using 13C isotopic tracers, that cells under hypoxic conditions or defective mitochondria primarily utilize glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate by isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) (Filipp et al., 2012Metallo et al., 2012;Mullen et al., 2012Wise et al., 2011).

The transcription factors hypoxia inducible factors 1α and 2α (HIF-1α, HIF-2α) have been established as master regulators of the hypoxic program and tumor phenotype (Gordan and Simon, 2007Semenza, 2010). In addition to tumor-associated hypoxia, HIF can be directly activated by cancer-associated mutations. The von Hippel-Lindau (VHL) tumor suppressor is inactivated in the majority of sporadic clear-cell renal carcinomas (RCC), with VHL-deficient RCC cells exhibiting constitutive HIF-1α and/or HIF-2α activity irrespective of oxygen availability (Kim and Kaelin, 2003). Previously, we showed that VHL-deficient cells also relied on RC for lipid synthesis even under normoxia. Moreover, metabolic profiling of two isogenic clones that differ in pVHL expression (WT8 and PRC3) suggested that reintroduction of wild-type VHL can restore glucose utilization for lipogenesis (Metallo et al., 2012). The VHL tumor suppressor protein (pVHL) has been reported to have several functions other than the well-studied targeting of HIF. Specifically, it has been reported that pVHL regulates the large subunit of RNA polymerase (Pol) II (Mikhaylova et al., 2008), p53 (Roe et al., 2006), and the Wnt signaling regulator Jade-1. VHL has also been implicated in regulation of NF-κB signaling, tubulin polymerization, cilia biogenesis, and proper assembly of extracellular fibronectin (Chitalia et al., 2008Kim and Kaelin, 2003Ohh et al., 1998Thoma et al., 2007Yang et al., 2007). Hypoxia inactivates the α-ketoglutarate-dependent HIF prolyl hydroxylases, leading to stabilization of HIF. In addition to this well-established function, oxygen tension regulates a larger family of α-ketoglutarate-dependent cellular oxygenases, leading to posttranslational modification of several substrates, among which are chromatin modifiers (Melvin and Rocha, 2012). It is therefore conceivable that the effect of hypoxia on RC that was reported previously may be mediated by signaling mechanisms independent of the disruption of the pVHL-HIF interaction. Here we (1) demonstrate that HIF is necessary and sufficient for RC, (2) provide insights into the molecular mechanisms that link HIF to RC, (3) detected RC activity in vivo in human VHL-deficient RCC cells growing as tumors in nude mice, (4) provide evidence that the reductive phenotype ofVHL-deficient cells renders them sensitive to glutamine restriction in vitro, and (5) show that inhibition of glutaminase suppresses growth of VHL-deficient cells in nude mice. These observations lay the ground for metabolism-based therapeutic strategies for targeting HIF-driven tumors (such as RCC) and possibly the hypoxic compartment of solid tumors in general.

Functional Interaction between pVHL and HIF Is Necessary to Inhibit RC

Figure 1  HIF Inactivation Is Necessary for Downregulation of Reductive Carboxylation by pVHL

We observed a concurrent regulation in glucose metabolism in the different VHL mutants. Reintroduction of wild-type or type 2C pVHL mutant, which can meditate HIF-α destruction, stimulated glucose oxidation via pyruvate dehydrogenase (PDH), as determined by the degree of 13C-labeled TCA cycle metabolites (M2 enrichment) (Figures 1D and 1E). In contrast, reintroduction of an HIF nonbinding Type 2B pVHL mutant failed to stimulate glucose oxidation, resembling the phenotype observed in VHL-deficient cells (Figures 1D and 1E). Additional evidence for the overall glucose utilization was obtained from the enrichment of M3 isotopomers using [U13-C6]glucose (Figure S1A), which shows a lower contribution of glucose-derived carbons to the TCA cycle in VHL-deficient RCC cells (via pyruvate carboxylase and/or continued TCA cycling).

To test the effect of HIF activation on the overall glutamine incorporation in the TCA cycle, we labeled an isogenic pair of VHL-deficient and VHL-reconstituted UMRC2 cells with [U-13C5]glutamine, which generates M4 fumarate, M4 malate, M4 aspartate, and M4 citrate isotopomers through glutamine oxidation. As seen in Figure S1BVHL-deficient/VHL-positive UMRC2 cells exhibit similar enrichment of M4 fumarate, M4 malate, and M4 asparate (but not citrate) showing that VHL-deficient cells upregulate reductive carboxylation without compromising oxidative metabolism from glutamine. …  Labeled carbon derived from [5-13C1]glutamine can be incorporated into fatty acids exclusively through RC, and the labeled carbon cannot be transferred to palmitate through the oxidative TCA cycle (Figure 1B, red carbons). Tracer incorporation from [5-13C1]glutamine occurs in the one carbon (C1) of acetyl-CoA, which results in labeling of palmitate at M1, M2, M3, M4, M5, M6, M7, and M8 mass isotopomers. In contrast, lipogenic acetyl-CoA molecules originating from [U-13C6]glucose are fully labeled, and the labeled palmitate is represented by M2, M4, M6, M8, M10, M12, M14, and M16 mass isotopomers.

Figure 2 HIF Inactivation Is Necessary for Downregulation of Reductive Lipogenesis by pVHL

To determine the specific contribution from glucose oxidation or glutamine reduction to lipogenic acetyl-CoA, we performed isotopomer spectral analysis (ISA) of palmitate labeling patterns. ISA indicates that wild-type pVHL or pVHL L188V mutant-reconstituted UMRC2 cells relied mainly on glucose oxidation to produce lipogenic acetyl-CoA, while UMRC2 cells reconstituted with a pVHL mutant defective in HIF inactivation (Y112N or Y98N) primarily employed RC. Upon disruption of the pVHL-HIF interaction, glutamine becomes the preferred substrate for lipogenesis, supplying 70%–80% of the lipogenic acetyl-CoA (Figure 2C). This is not a cell-line-specific phenomenon, but it applies to VHL-deficient human RCC cells in general; the same changes are observed in 786-O cells reconstituted with wild-type pVHL or mutant pVHL or infected with vector only as control (Figure S2).

HIF Is Sufficient to Induce RC (reductive carboxylation) from Glutamine in RCC Cells

As shown in Figure 3C, reintroduction of wild-type VHLinto 786-O cells suppressed RC, whereas the expression of the constitutively active HIF-2α mutant was sufficient to stimulate this reaction, restoring the M1 enrichment of TCA cycle metabolites observed in VHL-deficient 786-O cells. Expression of HIF-2α P-A also led to a concomitant decrease in glucose oxidation, corroborating the metabolic alterations observed in glutamine metabolism (Figures 3D and 3E).

Figure 3 Expression of HIF-2α Is Sufficient to Induce Reductive Carboxylation and Lipogenesis from Glutamine in RCC Cells

Expression of HIF-2α P-A in 786-O cells phenocopied the loss-of-VHL with regards to glutamine reduction for lipogenesis (Figure 3G), suggesting that HIF-2α can induce the glutamine-to-lipid pathway in RCC cells per se. Although reintroduction of wild-type VHL restored glucose oxidation in UMRC2 and UMRC3 cells (Figures S3B–S3I), HIF-2α P-A expression did not measurably affect the contribution of each substrate to the TCA cycle or lipid synthesis in these RCC cells (data not shown). UMRC2 and UMRC3 cells endogenously express both HIF-1α and HIF-2α, whereas 786-O cells exclusively express HIF-2α. There is compelling evidence suggesting, at least in RCC cells, that HIF-α isoforms have overlapping—but also distinct—functions and their roles in regulating bioenergetic processes remain an area of active investigation. Overall, HIF-1α has an antiproliferative effect, and its expression in vitro leads to rapid death of RCC cells while HIF-2α promotes tumor growth (Keith et al., 2011Raval et al., 2005).

Metabolic Flux Analysis Shows Net Reversion of the IDH Flux upon HIF Activation

To determine absolute fluxes in RCC cells, we employed 13C metabolic flux analysis (MFA) as previously described (Metallo et al., 2012). Herein, we performed MFA using a combined model of [U-13C6]glucose and [1-13C1]glutamine tracer data sets from the 786-O derived isogenic clones PRC3 (VHL−/ −)/WT8 (VHL+) cells, which show a robust metabolic regulation by reintroduction of pVHL. To this end, we first determined specific glucose/glutamine consumption and lactate/glutamate secretion rates. As expected, PRC3 exhibited increased glucose consumption and lactate production when compared to WT8 counterparts (Figure 4A). While PRC3 exhibited both higher glutamine consumption and glutamate production rates than WT8 (Figure 4A), the net carbon influx was higher in PRC3 cells (Figure 4B). Importantly, the fitted data show that the flux of citrate to α-ketoglutarate was negative in PRC3 cells (Figure 4C). This indicates that the net (forward plus reverse) flux of isocitrate dehydrogenase and aconitase (IDH + ACO) is toward citrate production. The exchange flux was also higher in PRC3 than WT8 cells, whereas the PDH flux was lower in PRC3 cells. In agreement with the tracer data, these MFA results strongly suggest that the reverse IDH + ACO fluxes surpass the forward flux in VHL-deficient cells. The estimated ATP citrate lyase (ACLY) flux was also lower in PRC3 than in WT8 cells. Furthermore, the malate dehydrogenase (MDH) flux was negative, reflecting a net conversion of oxaloacetate into malate in VHL-deficient cells (Figure 4C). This indicates an increased flux through the reductive pathway downstream of IDH, ACO, and ACLY. Additionally, some TCA cycle flux estimates downstream of α-ketoglutarate were not significantly different between PRC and WT8 (Table S1). This shows that VHL-deficient cells maintain glutamine oxidation while upregulating reductive carboxylation (Figure S1B). This finding is in agreement with the higher glutamine uptake observed in VHL-deficient cells. Table S1 shows the metabolic network and complete MFA results. …

Addition of citrate in the medium, in contrast to acetate, led to an increase in the citrate-to-α-ketoglutarate ratio (Figure 5L) and absolute citrate levels (Figure S4H) not only in VHL-deficient but alsoVHL-reconstituted cells. The ability of exogenous citrate, but not acetate, to also affect RC in VHL-reconstituted cells may be explained by compartmentalization differences or by allosteric inhibition of citrate synthase (Lehninger, 2005); that is, the ability of acetate to raise the intracellular levels of citrate may be limited in (VHL-reconstituted) cells that exhibit high endogenous levels of citrate. Whatever the mechanism, the results imply that increasing the pools of intracellular citrate has a direct biochemical effect in cells with regards to their reliance on RC. Finally, we assayed the transcript and protein levels of enzymes involved in the reductive utilization of glutamine and did not observe significant differences between VHL-deficient andVHL-reconstituted UMRC2 cells (Figures S4I and S4J), suggesting that HIF does not promote RC by direct transactivation of these enzymes. The IDH1/IDH2 equilibrium is defined as follows:

[α−ketoglutrate][NADPH][CO2]/[Isocitrate][NADP+]=K(IDH)

Figure 5 Regulation of HIF-Mediated Reductive Carboxylation by Citrate Levels

We sought to investigate whether HIF could affect the driving force of the IDH reaction by also enhancing NADPH production. We did not observe a significant alteration of the NADP+/NADPH ratio between VHL-deficient and VHL-positive cells in the cell lysate (Figure S4I). Yet, we determined the ratio of the free dinucleotides using the measured ratios of suitable oxidized (α-ketoglutarate) and reduced (isocitrate/citrate) metabolites that are linked to the NADP-dependent IDH enzymes. The determined ratios (Figure S4J) are in close agreement with the values initially reported by the Krebs lab (Veech et al., 1969) and showed that HIF-expressing UMRC2 cells exhibit a higher NADP+/NADPH ratio. Collectively, these data strongly suggest that HIF-regulated citrate levels modulate the reductive flux to maintain adequate lipogenesis.

Reductive Carboxylation from Glutamine Is Detectable In Vivo

Figure 6 Evidence for Reductive Carboxylation Activity In Vivo

Loss of VHL Renders RCC Cells Sensitive to Glutamine Deprivation

We hypothesized that VHL deficiency results in cell addiction to glutamine for proliferation. We treated the isogenic clones PRC3 (VHL-deficient cells) and WT8 (VHL-reconstituted cells) with the glutaminase inhibitor 968 (Wang et al., 2010a). VHL-deficient PRC3 cells were more sensitive to treatment with 968, compared to the VHL-reconstituted WT8 cells (Figure 7A). To confirm that this is not only a cell-line-specific phenomenon, we also cultured UMRC2 cells in the presence of 968 or diluent control and showed selective sensitivity of VHL-deficient cells (Figure 7B).

Figure 7 VHL-Deficient Cells and Tumors Are Sensitive to Glutamine Deprivation

(A–E) Cell proliferation is normalized to the corresponding cell type grown in 1 mM glutamine-containing medium. Effect of treatment with glutaminase (GLS) inhibitor 968 in PRC3/WT8 (A) and UMRC2 cells (B). Rescue of GLS inhibition with dimethyl alpha-ketoglutarate (DM-Akg; 4 mM) or acetate (4 mM) in PRC3/WT8 clonal cells (C) and polyclonal 786-O cells (D). Effect of GLS inhibitor BPTES in UMRC2 cells (E). Student’s t test compares VHL-reconstituted cells to control cells in (A), (B), and (E) and DM-Akg or acetate-rescued cells to correspondent control cells treated with 968 only in (C) and (D) (asterisk in parenthesis indicates comparison between VHL-reconstituted to control cells). Error bars represent SEM.

(F) GLS inhibitor BPTES suppresses growth of human UMRC3 RCC cells as xenografts in nu/nu mice. When the tumors reached 100mm3, injections with BPTES or vehicle control were carried out daily for 14 days (n = 12). BPTES treatment decreases tumor size and mass (see insert). Student’s t test compares control to BPTES-treated mice (F). Error bars represent SEM.

(G) Diagram showing the regulation of reductive carboxylation by HIF.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003458/bin/nihms449661f7.jpg

In summary, our findings show that HIF is necessary and sufficient to promote RC from glutamine. By inhibiting glucose oxidation in the TCA cycle and reducing citrate levels, HIF shifts the IDH reaction toward RC to support citrate production and lipogenesis (Figure 7G). The reductive flux is active in vivo, fuels tumor growth, and can potentially be targeted pharmacologically. Understanding the significance of reductive glutamine metabolism in tumors may lead to metabolism-based therapeutic strategies.

Along with others, we reported that hypoxia and loss of VHL engage cells in reductive carboxylation (RC) from glutamine to support citrate and lipid synthesis (Filipp et al., 2012Metallo et al., 2012Wise et al., 2011). Wise et al. (2011) suggested that inactivation of HIF in VHL-deficient cells leads to reduction of RC. These observations raise the hypothesis that HIF, which is induced by hypoxia and is constitutively active inVHL-deficient cells, mediates RC. In our current work, we provide mechanistic insights that link HIF to RC. First, we demonstrate that polyclonal reconstitution of VHL in several human VHL-deficient RCC cell lines inhibits RC and restores glucose oxidation. Second, the VHL mutational analysis demonstrates that the ability of pVHL to mitigate reductive lipogenesis is mediated by HIF and is not the outcome of previously reported, HIF-independent pVHL function(s). Third, to prove our hypothesis we showed that constitutive expression of a VHL-independent HIF mutant is sufficient to phenocopy the reductive phenotype observed in VHL-deficient cells. In addition, we showed that RC is not a mere in vitro phenomenon, but it can be detected in vivo in human tumors growing as mouse xenografts. Lastly, treatment of VHL-deficient human xenografts with glutaminase inhibitors led to suppression of their growth as tumors.

7.9.10 Evaluation of HIF-1 inhibitors as anticancer agents

Semenza GL1.
Drug Discov Today. 2007 Oct; 12(19-20):853-9
http://dx.doi.org/10.1016/j.drudis.2007.08.006

Hypoxia-inducible factor 1 (HIF-1) regulates the transcription of many genes involved in key aspects of cancer biology, including immortalization, maintenance of stem cell pools, cellular dedifferentiation, genetic instability, vascularization, metabolic reprogramming, autocrine growth factor signaling, invasion/metastasis, and treatment failure. In animal models, HIF-1 overexpression is associated with increased tumor growth, vascularization, and metastasis, whereas HIF-1 loss-of-function has the opposite effect, thus validating HIF-1 as a target. In further support of this conclusion, immunohistochemical detection of HIF-1α overexpression in biopsy sections is a prognostic factor in many cancers. A growing number of novel anticancer agents have been shown to inhibit HIF-1 through a variety of molecular mechanisms. Determining which combination of drugs to administer to any given patient remains a major obstacle to improving cancer treatment outcomes.

Aurelian Udristioiu

Aurelian

Aurelian Udristioiu

Lab Director at Emergency County Hospital Targu Jiu

Mechanisms that control T cell metabolic reprogramming are now coming to light, and many of the same oncogenes importance in cancer metabolism are also crucial to drive T cell metabolic transformations, most notably Myc, hypoxia inducible factor (HIF)1a, estrogen-related receptor (ERR) a, and the mTOR pathway.
The proto-oncogenic transcription factor, Myc, is known to promote transcription of genes for the cell cycle, as well as aerobic glycolysis and glutamine metabolism. Recently, Myc has been shown to play an essential role in inducing the expression of glycolytic and glutamine metabolism genes in the initial hours of T cell activation. In a similar fashion, the transcription factor (HIF)1a can up-regulate glycolytic genes to allow cancer cells to survive under hypoxic conditions

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Sirtuins

Writer and Curator: Larry H. Bernstein, MD, FCAP 

7.8  Sirtuins

7.8.1 Function and regulation of the mitochondrial Sirtuin isoform Sirt5 in Mammalia

7.8.2 Substrates and Regulation Mechanisms for the Human Mitochondrial Sirtuins- Sirt3 and Sirt5

7.8.3 The mTORC1 Pathway Stimulates Glutamine Metabolism and Cell Proliferation by Repressing SIRT4

7.8.4  Rab1A and small GTPases Activate mTORC1

7.8.5 PI3K.Akt signaling in osteosarcoma

7.8.6 The mTORC1-S6K1 Pathway Regulates Glutamine Metabolism through the eIF4B-Dependent Control of c-Myc Translation

7.8.7 Localization of mouse mitochondrial SIRT proteins

7.8.8 SIRT4 Has Tumor-Suppressive Activity and Regulates the Cellular Metabolic Response to DNA Damage by Inhibiting Mitochondrial Glutamine Metabolism

7.8.9 Mitochondrial sirtuins and metabolic homeostasis

7.8.10 Mitochondrial sirtuins

7.8.11 Sirtuin regulation of mitochondria: energy production, apoptosis, and signaling

 

7.8.1 Function and regulation of the mitochondrial Sirtuin isoform Sirt5 in Mammalia

Gertz M1Steegborn C.
Biochim Biophys Acta. 2010 Aug; 1804(8):1658-65
http://dx.doi.org:/10.1016/j.bbapap.2009.09.011

Sirtuins are a family of protein deacetylases that catalyze the nicotinamide adenine dinucleotide (NAD(+))-dependent removal of acetyl groups from modified lysine side chains in various proteins. Sirtuins act as metabolic sensors and influence metabolic adaptation but also many other processes such as stress response mechanisms, gene expression, and organismal aging. Mammals have seven Sirtuin isoforms, three of them – Sirt3, Sirt4, and Sirt5 – located to mitochondria, our centers of energy metabolism and apoptosis initiation. In this review, we shortly introduce the mammalian Sirtuin family, with a focus on the mitochondrial isoforms. We then discuss in detail the current knowledge on the mitochondrial isoform Sirt5. Its physiological role in metabolic regulation has recently been confirmed, whereas an additional function in apoptosis regulation remains speculative. We will discuss the biochemical properties of Sirt5 and how they might contribute to its physiological function. Furthermore, we discuss the potential use of Sirt5 as a drug target, structural features of Sirt5 and of an Sirt5/inhibitor complex as well as their differences to other Sirtuins and the current status of modulating Sirt5 activity with pharmacological compounds.

removal of acetyl groups from modified lysine side chain

removal of acetyl groups from modified lysine side chain

http://ars.els-cdn.com/content/image/1-s2.0-S1570963909002593-gr1.sml
removal of acetyl groups from modified lysine side chain

sirtuin structure

sirtuin structure

http://ars.els-cdn.com/content/image/1-s2.0-S1570963909002593-gr2.sml
sirtuin structure

7.8.2 Substrates and Regulation Mechanisms for the Human Mitochondrial Sirtuins- Sirt3 and Sirt5

Schlicker C1Gertz MPapatheodorou PKachholz BBecker CFSteegborn C
J Mol Biol. 2008 Oct 10; 382(3):790-801
http://dx.doi.org/10.1016/j.jmb.2008.07.048

The enzymes of the Sirtuin family of nicotinamide-adenine-dinucleotide-dependent protein deacetylases are emerging key players in nuclear and cytosolic signaling, but also in mitochondrial regulation and aging. Mammalian mitochondria contain three Sirtuins, Sirt3, Sirt4, and Sirt5. Only one substrate is known for Sirt3 as well as for Sirt4, and up to now, no target for Sirt5 has been reported. Here, we describe the identification of novel substrates for the human mitochondrial Sirtuin isoforms Sirt3 and Sirt5. We show that Sirt3 can deacetylate and thereby activate a central metabolic regulator in the mitochondrial matrix, glutamate dehydrogenase. Furthermore, Sirt3 deacetylates and activates isocitrate dehydrogenase 2, an enzyme that promotes regeneration of antioxidants and catalyzes a key regulation point of the citric acid cycle. Sirt3 thus can regulate flux and anapleurosis of this central metabolic cycle. We further find that the N- and C-terminal regions of Sirt3 regulate its activity against glutamate dehydrogenase and a peptide substrate, indicating roles for these regions in substrate recognition and Sirtuin regulation. Sirt5, in contrast to Sirt3, deacetylates none of the mitochondrial matrix proteins tested. Instead, it can deacetylate cytochrome c, a protein of the mitochondrial intermembrane space with a central function in oxidative metabolism, as well as apoptosis initiation. Using a mitochondrial import assay, we find that Sirt5 can indeed be translocated into the mitochondrial intermembrane space, but also into the matrix, indicating that localization might contribute to Sirt5 regulation and substrate selection.

Mitochondria are central organelles in cellular energy metabolism, but also in processes such as apoptosis, cellular senescence, and lifespan regulation.1 and 2 Failures in mitochondrial function and regulation contribute to aging-related diseases, such as atherosclerosis3 and Parkinson’s disease,4 likely by increasing cellular levels of reactive oxygen species and the damage they cause.1 Emerging players in metabolic regulation and cellular signaling are members of the Sirtuin family of homologs of “silent information regulator 2” (Sir2), a yeast protein deacetylase.5 and 6 Sir2 was found to be involved in aging processes and lifespan determination in yeast,7 and 8 and its homologs were subsequently identified as lifespan regulators in various higher organisms.89 and 10 Sirtuins form class III of the protein deacetylase superfamily and hydrolyze one nicotinamide adenine dinucleotide (NAD +) as cosubstrate for each lysine residue they deacetylate.11 and 12 The coupling of deacetylation to NAD + was proposed to link changes in cellular energy levels to deacetylation activity,13 and 14 which would indicate Sirtuins as metabolic sensors. Other known regulation mechanisms for Sirtuin activity are the modulation of the expression levels of their genes6 and the autoinhibitory effect of an N-terminal region on the yeast Sirtuin “homologous to SIR2 protein 2” (Hst2).15

The seven mammalian Sirtuin proteins (Sirt1–Sirt7) have various substrate proteins that mediate functions in genetic, cellular, and mitochondrial regulation.5 and 6 The best-studied mammalian Sir2 homolog, Sirt1, was shown to regulate, among others, transcription factor p53, nuclear factor-kappa B, and peroxisome proliferator-activated receptor gamma coactivator-1-alpha.6 Three human Sirtuin proteins are known to be located in the mitochondria, Sirt3, Sirt4, and Sirt5,161718 and 19 although Sirt3 was reported to change its localization to nuclear when coexpressed with Sirt5.20 The recent identification of the first substrates for mitochondrial Sirtuins—acetyl coenzyme A synthetase 221 and 22 and glutamate dehydrogenase (GDH)16—as targets of Sirtuins 3 and 4, respectively, revealed that these Sirtuins control a regulatory network that has implications for energy metabolism and the mechanisms of caloric restriction (CR) and lifespan determination.23 Sirt3 regulates adaptive thermogenesis and decreases mitochondrial membrane potential and reactive oxygen species production, while increasing cellular respiration.24 Furthermore, Sirt3 is down-regulated in several genetically obese mice,24 and variability in the human SIRT3 gene has been linked to survivorship in the elderly. 25 In contrast to the deacetylases Sirt3 and Sirt5, Sirt4 appears to be an ADP ribosyltransferase. 16 Through this activity, Sirt4 inhibits GDH and thereby down-regulates insulin secretion in response to amino acids. 16 For Sirt5, however, there is no report yet on its physiological function or any physiological substrate. It is dominantly expressed in lymphoblasts and heart muscle cells,17 and 26 and its gene contains multiple repetitive elements that might make it a hotspot for chromosomal breaks. 26 Interestingly, the Sirt5 gene has been located to a chromosomal region known for abnormalities associated with malignant diseases. 26

A proteomics study found 277 acetylation sites in 133 mitochondrial proteins;27 many of them should be substrates for the mitochondrial Sirtuins mediating their various functions, but up to now, only one physiological substrate could be identified for Sirt3,21 and 22 and none could be identified for Sirt5. Our understanding of substrate selection by Sirtuins is incomplete, and knowledge of specific Sirtuin targets would be essential for a better understanding of Sirtuin-mediated processes and Sirtuin-targeted therapy. A first study on several Sirtuins showed varying preferences among acetylated peptides.28 Structural and thermodynamic analysis of peptides bound to the Sirtuin Sir2Tm from Thermatoga maritima indicated that positions − 1 and + 2 relative to the acetylation site play a significant role in substrate binding. 29 However, these studies were conducted with nonphysiological Sirtuin/substrate pairs, and other studies indicated little sequence specificity; instead, the yeast Sirtuin Hst2 was described to display contextual and conformational specificity: Hst2 deacetylated acetyl lysine only in the context of a protein, and it preferentially deacetylated within flexible protein regions. 30 Finally, statistical analysis of a proteomics study on acetylated proteins identified preferences at various positions such as + 1, − 2, and − 3, and deacetylation sites appeared to occur preferentially in helical regions. 27 Thus, our present knowledge of Sirtuin substrates and of factors determining Sirtuin specificity is incomplete and insufficient for sequence-based identification of physiological substrates.

Here, we describe the identification of novel targets for the mitochondrial deacetylases Sirt3 and Sirt5. We show that Sirt3 can deacetylate and thereby activate the enzymes GDH and isocitrate dehydrogenase (ICDH) 2—two key metabolic regulators in the mitochondrial matrix. We find that the N- and C-terminal regions of Sirt3 influence its activity against GDH and a peptide substrate, indicating roles in regulation and substrate recognition for these regions. Furthermore, we find that Sirt5 can deacetylate cytochrome c, a protein of the mitochondrial intermembrane space (IMS) with a central function in oxidative metabolism and apoptosis.

The upstream sequence contributes to the target specificity of Sirt3 and Sirt5

Sirtuins have been reported to have little sequence specificity,30 but other studies indicated a sequence preference dominated by positions − 1 and + 2.29 We tested the importance of the amino acid pattern preceding the acetylation site for recognition by the mitochondrial Sirtuins Sirt3 and Sirt5 through a fluorescence assay. First, the fluorogenic and commercially available modified p53-derived tetrapeptide QPK-acetylK, originally developed for Sirt2 assays but also efficiently used by Sirt3, was tested. Even 60 μg of Sirt5 did not lead to any deacetylation signal, whereas 0.35 μg of Sirt3 efficiently deacetylated the peptide (Fig. 1a). We then tested Sirt3 and Sirt5 on a second modified p53-derived tetrapeptide, RHK-acetylK. Sirt3 (0.5 μg) showed a slightly increased activity against this substrate as compared to QPK-acetylK (Fig. 1b); more importantly, 0.5 μg of Sirt5 showed significant activity against this peptide. These results show that the mitochondrial Sirtuins Sirt3 and, especially, Sirt5 indeed recognize the local target sequence, and target positions further upstream of − 1 seem to be involved in substrate recognition. For identification of novel substrates for the mitochondrial Sirtuins and further characterization of their target recognition mechanisms, we then turned to testing full-length proteins, as the downstream sequence and the larger protein context of the deacetylation site might also contribute to substrate selection.

Sirtuin substrate specificity

Sirtuin substrate specificity

Fig. 1. Testing the substrate specificity of Sirt3 and Sirt5 with peptides. (a) Sirt3, but not Sirt5, deacetylates the fluorogenic peptide QPK-acetylK. (b) Sirt3 efficiently deacetylates the fluorogenic peptide RHK-acetylK, and Sirt5 also significantly deacetylates this substrate.
http://ars.els-cdn.com/content/image/1-s2.0-S0022283608009029-gr1.jpg

Sirt3 deacetylates and activates GDH

In order to identify novel physiological substrates of the mitochondrial Sirtuins, we used proteins isolated in their partly acetylated form from natural sources (i.e., from mammalian mitochondria). These proteins, carrying physiological acetylations, were tested as Sirt3 and Sirt5 substrates in vitro in an ELISA system using an antibody specific for acetylated lysine. In a recent proteomics study, 27 GDH, a central regulator of mitochondrial metabolism, was identified to be acetylated in a feeding-dependent manner. With our ELISA, we found that Sirt3 and Sirt5 can both deacetylate pure GDH isolated from mitochondria, but with very different efficiencies ( Fig. 2a). Sirt3 significantly deacetylated GDH, but even large amounts of Sirt5 decreased the acetylation level of this substrate only slightly. We next tested the effect of GDH deacetylation on its activity. Deacetylation of GDH through incubation with Sirt3 and NAD + before its examination in a GDH activity assay increased its activity by 10%, and a stronger stimulation of GDH activity was seen when larger amounts of Sirt3 were used for deacetylation ( Fig. 2b). GDH is colocalized with Sirt3 in the mitochondrial matrix 1618 and 19 and, thus, likely could be a physiological substrate of this Sirtuin. Indeed, GDH from a Sirt3 knockout mouse was recently shown to be hyperacetylated compared to protein from wild-type mice. 31 Thus, Sirt3 deacetylates GDH in vivo, and our results show that this direct deacetylation of GDH by Sirt3 leads to GDH activation.

sirtuin structure

sirtuin structure

Fig. 2. Sirt3 can deacetylate and thereby activate GDH. (a) Deacetylation of GDH tested in ELISA. Sirt3 efficiently deacetylates GDH, whereas Sirt5 has only a small effect on the acetylation state. (b) GDH activity is increased after deacetylation of the enzyme by Sirt3. The increase in GDH activity depends on the amount of Sirt3 activity used for deacetylation.
http://ars.els-cdn.com/content/image/1-s2.0-S0022283608009029-gr2.jpg

Sirt3 can deacetylate and thereby activate ICDH2

In the proteomics study by Kim et al., the mitochondrial citric acid cycle enzymes fumarase and ICDH2 (a key regulator of this metabolic cycle) were found to be acetylated in a feeding-dependent manner. 27 In our ELISA system, we found that Sirt3 efficiently deacetylated the ICDH2 substrate isolated from mitochondria ( Fig. 3a). Western blot analysis (data not shown) and mass spectrometry confirmed that, indeed, the ICDH2 fraction of the partially purified protein was deacetylated by Sirt3. In contrast, even large amounts of Sirt5 did not significantly decrease the acetylation level of this substrate ( Fig. 3a). As expected, deacetylation of ICDH2 by Sirt3 was dependent on NAD +. Fumarase, in contrast, could not be deacetylated as efficiently as ICDH2 through treatment with either Sirt3 or Sirt5 ( Fig. 3b). The low absolute values over background for the ELISA with fumarase, however, might indicate low acetylation levels of the natively purified protein, and a stronger effect might be attainable when testing fumarase with a higher acetylation level.

Fig. 3. Sirt3 deacetylates ICDH2, but not fumarase. (a) Deacetylation of ICDH2 by Sirt3 and Sirt5 tested in ELISA. Sirt3, but not Sirt5, deacetylates ICDH2 in a NAD +-dependent manner. (b) Fumarase acetylation determined through ELISA cannot be significantly decreased by incubation with recombinant Sirt3 or Sirt5. (c) ICDH2 activity measured in a spectrophotometric assay based on the formation of NADPH. ICDH2 activity (continuous line) is increased after deacetylation of the enzyme by Sirt3 (dashed line). (d) The stimulatory effect of deacetylation on ICDH2 activity depends on the amount of deacetylase activity added during pretreatment. (e) ICDH2 with and without Sirt3 treatment analyzed by mass spectrometry after proteolytic digest. The decrease in the signal at 962.3 Da and the increase in signal at 903.5 Da indicate deacetylation at either K211 or K212.

In order to analyze the potential physiological function of ICDH2 deacetylation, we tested the effect of Sirt3-mediated ICDH2 deacetylation on its activity. Incubation of ICDH2 with Sirt3 and NAD + prior to its analysis in an ICDH activity assay increased its activity (Fig. 3c). The stimulation of ICDH2 activity was further increased when larger amounts of Sirt3 were used for deacetylation (Fig. 3d), and no significant increase in ICDH2 activity was observed when the Sirtuin inhibitor dihydrocoumarin was present during incubation with Sirt3 (data not shown). Sirt3 and ICDH2 are colocalized in the mitochondrial matrix,1619 and 32 and we therefore assume that ICDH2 is likely a physiological substrate for Sirt3, which activates ICDH2 by deacetylation.
http://ars.els-cdn.com/content/image/1-s2.0-S0022283608009029-gr3.jpg

Sirt3 can deacetylate KK motifs in substrate proteins

In order to identify the site of ICDH2 deacetylation upon treatment with Sirt3, we analyzed ICDH2 by mass spectrometry. For analyzing pure ICDH2, we excised its band from an SDS gel before mass spectrometry analysis. In the proteomics study by Kim et al., two acetylation sites were reported for ICDH2: K75 and K241 (numbering of the partial sequence of the unprocessed precursor; SwissProt entry P33198). 27 After digest of ICDH2, we could not detect peptides comprising K75 and, therefore, could not determine its acetylation status, and we only observed the deacetylated form of K241. We identified an additional acetylation site, however, by detecting signals at m/z = 903.5 and m/z = 962.3 for the peptide QYAIQKK (residues 206–212) carrying one and two acetyl groups, respectively ( Fig. 3e; calculated m/z = 903.5 and 962.5). Sirt3 treatment decreased the signal for the double-acetylated form and increased the signal for the single-acetylated form as compared to internal peptides [e.g., m/z = 890.5 (calculated m/z = 890.5) andm/z = 1041.4 (calculated m/z = 1041.5)]. These data indicate that Sirt3 deacetylates either position K211 or K212 of this KK motif located at a surface-exposed end of a helix that flanks the active site of ICDH2. 33Deacetylation of a KK motif by Sirt3 is consistent with the efficient use of the tested peptide substrates (see above) that both carry KK motifs.

Fig. 4. Increased activity of N- and C-terminally truncated Sirt3. (a) Specific activity against a peptide substrate of the longest Sirt3 form after proteolytic processing that covers residues 102–399. N-terminal truncation increases the specific activity dramatically, and an additional C-terminal truncation activates the catalytic core further. (b) Homology model of Sirt3 based on the crystal structure of Sirt2. The part comprising the catalytic core is shown in red. The NAD + and peptide ligands were manually placed into their binding sides based on the crystal structure of their complex with a bacterial Sir2 homolog from T. maritima. Parts removed in N- and C-terminal truncation constructs are shown in cyan and blue, respectively. (c) Level of acetylation of GDH tested in ELISA. The shortest Sirt3 form Sirt3(114–380) deacetylates more efficiently than Sirt3(114–399) and Sirt3(102–399), which show activities comparable to each other.

Sirt5 can deacetylate cytochrome c

Sirt5 can deacetylate cytochrome c

http://ars.els-cdn.com/content/image/1-s2.0-S0022283608009029-gr4.jpg

Sirt5 can deacetylate cytochrome c

The Sirt5 protein that we used for our study comprises residues 34–302, corresponding to the fully active catalytic core determined for Sirt3 (see above). This protein is indeed active against a peptide substrate, but it showed no significant activity against the acetylated mitochondrial matrix proteins tested so far: GDH, ICDH2, and fumarase. We thus picked cytochrome c, a central protein in energy metabolism and apoptosis localized in the mitochondrial IMS, from the list of acetylated mitochondrial proteins 27 for testing as deacetylation substrate. Sirt5 showed deacetylation activity against pure cytochrome c in our ELISA system, whereas Sirt3 had almost no activity against this substrate ( Fig. 5a). Even the more active shortened form of Sirt3(114–380) showed no considerable activity against this substrate.

Fig. 5.  Sirt5 can deacetylate cytochrome c. (a) Deacetylation of cytochrome c tested in ELISA. Sirt5 uses cytochrome c as substrate for deacetylation, whereas Sirt3 treatment leaves the acetylation level of cytochrome c unchanged. (b) Model of the action of the mammalian Sirtuins Sirt3, Sirt4, and Sirt5 in mitochondria. CAC: citric acid cycle. (c) Digest of Sirt5 synthesized in vitro with PK. The protein is fully degraded at proteinase concentrations of 25 μg/ml and above. (d) Import of Sirt5 into isolated yeast mitochondria. Sirt5 reaches an inner mitochondrial compartment in the presence and in the absence of the mitochondrial membrane potential (ΔΨ), whereas Sirt3, as a control for a matrix-targeted protein, is not imported into uncoupled mitochondria. (e) Intramitochondrial localization of Sirt5. Part of the imported Sirt5 is sensitive to PK after swelling (SW) and thus localized in the IMS, but another part of the protein remains protease-resistant and therefore appears to be localized to the matrix. Atp3, a protein localized at the matrix site of the mitochondrial inner membrane, and an IMS-located domain of translocase of inner membrane 23 detected by Western blot analysis served as controls for matrix transport and swelling, respectively. aTim23: anti-Tim23. (f) Scheme of the domain organizations of Sirt3 and Sirt5. Numbers in brackets are residue numbers for boundaries of protein parts. NLS: nuclear localization sequence; MLS: mitochondrial localization sequence; R1, regulatory region 1; R2: regulatory region 2.
http://ars.els-cdn.com/content/image/1-s2.0-S0022283608009029-gr5.jpg

Cytochrome c might be a physiological substrate of Sirt5 if this Sirtuin is localized to the mitochondrial IMS (Fig. 5b). A recent study on overexpressed tagged mouse Sirt5 in COS7 cells 20 indeed indicated that Sirt5, at least from mouse, is localized in the IMS. In order to test whether human Sirt5 can be localized to the IMS, we performed import experiments with human Sirt3 and Sirt5 using isolated yeast mitochondria as a model system. 3 Sirt3 and Sirt5 proteins were incubated with mitochondria, followed by PK treatment for degradation of nonimported protein ( Fig. 5d). In a parallel reaction, mitochondria were uncoupled prior to the import reaction by addition of valinomycin (− ΔΨ). Sirt3, a protein known to be located in the mitochondrial matrix, 19 was only efficiently imported in the presence of a membrane potential. Dependence on the mitochondrial potential is a hallmark of matrix import, 38 and the results thus show that Sirt3 is imported into the correct compartment in our experimental system. Sirt5, in contrast, reaches an inner-mitochondrial compartment both in the presence and in the absence of the membrane potential, suggesting that Sirt5 may accumulate in the IMS.

In order to further test the localization of Sirt5, we removed the outer mitochondrial membrane after the import reaction by osmotic swelling, followed by PK digest of then accessible proteins (Fig. 5e). Rupture of the outer membrane was confirmed by monitoring the accessibility of an IMS-exposed domain of endogenous translocase of inner membrane 23 (detected by Western blot analysis). Part of the imported Sirt5 was degraded by PK, indicating its localization in the IMS.

Sirtuins are involved in central physiological regulation mechanisms, many of them with relevance to metabolic regulation and aging processes.5 and 6 Therefore, the seven mammalian Sirtuin isoforms are emerging targets for the treatment of metabolic disorders and aging-related diseases.39 For most Sirtuin effects, however, the specific signaling mechanisms and molecular targets are not yet known. We have identified novel potential targets for Sirtuins in mitochondria, the major metabolic centers in cells. We found that Sirt3 can deacetylate and thereby activate ICDH2, a key regulation point for flux throughout the citric acid cycle. Interestingly, the ICDH isoform regulated by Sirt3 forms NADPH instead of the NADH used for ATP synthesis. This activity is assumed to be important for the NADPH-dependent regeneration of antioxidants,40 and its stimulation by Sirt3 should thus help to slow oxidative damage and cellular aging processes. Furthermore, Sirt3 deacetylates GDH in vitro (this study) and in vivo31 and we find that this modification also stimulates GDH activity that promotes glucose and ATP synthesis by enabling amino acids to be used as fuels for citric acid cycle and gluconeogenesis. 41 Consistently, Sirt3 was reported to increase respiration, 24 which is needed for ATP synthesis but also for conversion of amino acids into glucose and urea. 41 The enzyme previously identified to be activated by Sirt3, acetyl coenzyme A synthetase 2, 21 and 22 also fuels the citric acid cycle independently of glycolysis by activating free acetate (Fig. 5b). Interestingly, a shift away from liver glycolysis is one of the metabolic changes observed under CR, a feeding regimen with 20–40% fewer calories than consumed ad libitum that is found to extend the lifespan of a variety of organisms. 6 CR was previously reported to increase GDH activity in the liver, 42where Sirt3 is highly expressed, 17 and Sirt3 activity is known to be increased by CR. 6 and 24 It thus appears that Sirt3 mediates some of the effects of CR and lifespan regulation, consistent with its implication in survivorship in the elderly 25 and 43 and the prominent role of Sirtuins in CR found for various organisms,6 and 44 and it also appears that GDH activation likely contributes to the Sirt3-dependent effects.

Little is known about additional factors regulating the activity and specificity of Sirtuin enzymes. Their requirement for NAD + indicates that the NAD +/NADH ratio should regulate Sirtuins,13 and 14 but even changes to ratios observed under extreme conditions such as CR appear to influence Sirtuin activity only slightly.35 Furthermore, NAD + levels would influence all Sirtuins similarly, but a more specific tuning of individual Sirtuin activities appears necessary in order to orchestrate the many effects mediated by Sirtuins (see, e.g., discussion above).6 and 45 A deeper insight into the regulation of Sirtuin enzymes would also be required for the development of more specific Sirtuin inhibitors—a prerequisite for Sirtuin-targeted therapy.39 The regulatory parts flanking the catalytic cores might be interesting target sites (Fig. 5f). N-terminal extensions between ∼ 30 and 120 residues are present in all human Sirtuins but show little conservation, indicating that they might respond to various regulators. Our results indicate that the corresponding N-terminal region in Sirt3 also blocks productive binding for small peptides (Fig. 4a), but enables access for entire protein substrates (Fig. 4c). The C-terminal truncated part in our experiments (Sirt3 residues 380–399) is formed by α14 (secondary structure numbering for Sirt236) whose end corresponds to the N-terminus of Hst2 α13 that partly occupies the NAD +binding site.15 In Sirt3, however, the C-terminal truncation alone lowers activity only slightly, and we assume that it has no regulatory function on its own but might instead assist the N-terminal autoinhibitory region. This module of the N-terminus and the C-terminus (Figs. 4b and 5f) appears to contribute to the substrate specificity of the enzyme, and ligands binding to it might enable or block rearrangements opening up the active site and thereby regulate the enzyme’s activity. Alternatively, the flanking parts might be removed by proteolytic processing or alternative splicing, thereby changing Sirtuin activity and specificity.

7.8.3 The mTORC1 Pathway Stimulates Glutamine Metabolism and Cell Proliferation by Repressing SIRT4

Csibi A1Fendt SMLi CPoulogiannis GChoo AYChapski DJ, et al.
Cell. 2013 May 9; 153(4):840-54.
http://dx.doi.org:/10.1016/j.cell.2013.04.023

Proliferating mammalian cells use glutamine as a source of nitrogen and as a key anaplerotic source to provide metabolites to the tricarboxylic acid cycle (TCA) for biosynthesis. Recently, mTORC1 activation has been correlated with increased nutrient uptake and metabolism, but no molecular connection to glutaminolysis has been reported. Here, we show that mTORC1 promotes glutamine anaplerosis by activating glutamate dehydrogenase (GDH). This regulation requires transcriptional repression of SIRT4, the mitochondrial-localized sirtuin that inhibits GDH. Mechanistically, mTORC1 represses SIRT4 by promoting the proteasome-mediated destabilization of cAMP response element binding-2 (CREB2). Thus, a relationship between mTORC1, SIRT4 and cancer is suggested by our findings. Indeed, SIRT4 expression is reduced in human cancer, and its overexpression reduces cell proliferation, transformation and tumor development. Finally, our data indicate that targeting nutrient metabolism in energy-addicted cancers with high mTORC1 signaling may be an effective therapeutic approach.

Proliferating mammalian cells use glutamine as a source of nitrogen and as a key anaplerotic source to provide metabolites to the tricarboxylic acid cycle (TCA) for biosynthesis. Recently, mTORC1 activation has been correlated with increased nutrient uptake and metabolism, but no molecular connection to glutaminolysis has been reported. Here, we show that mTORC1 promotes glutamine anaplerosis by activating glutamate dehydrogenase (GDH). This regulation requires transcriptional repression of SIRT4, the mitochondrial-localized sirtuin that inhibits GDH. Mechanistically, mTORC1 represses SIRT4 by promoting the proteasome-mediated destabilization of cAMP response element binding-2 (CREB2). Thus, a relationship between mTORC1, SIRT4 and cancer is suggested by our findings. Indeed, SIRT4 expression is reduced in human cancer, and its overexpression reduces cell proliferation, transformation and tumor development. Finally, our data indicate that targeting nutrient metabolism in energy-addicted cancers with high mTORC1 signaling may be an effective therapeutic approach.

Nutrient availability plays a pivotal role in the decision of a cell to commit to cell proliferation. In conditions of sufficient nutrient sources and growth factors (GFs), the cell generates enough energy and acquires or synthesizes essential building blocks at a sufficient rate to meet the demands of proliferation. Conversely, when nutrients are scarce, the cell responds by halting the biosynthetic machinery and by stimulating catabolic processes such as fatty acid oxidation and autophagy to provide energy maintenance (Vander Heiden et al., 2009). Essential to the decision process between anabolism and catabolism is the highly conserved, atypical Serine/Threonine kinase mammalian Target of Rapamycin Complex 1 (mTORC1), whose activity is deregulated in many cancers (Menon and Manning, 2008). This complex, which consists of mTOR, Raptor, and mLST8, is activated by amino acids (aa), GFs (insulin/IGF-1) and cellular energy to drive nutrient uptake and subsequently proliferation (Yecies and Manning, 2011). The molecular details of these nutrient-sensing processes are not yet fully elucidated, but it has been shown that aa activate the Rag GTPases to regulate mTORC1 localization to the lysosomes (Kim et al., 2008Sancak et al., 2008); and GFs signal through the PI3K-Akt or the extracellular signal-regulated kinase (ERK)-ribosomal protein S6 kinase (RSK) pathways to activate mTORC1 by releasing the Ras homolog enriched in brain (RHEB) GTPase from repression by the tumor suppressors, tuberous sclerosis 1 (TSC1)– TSC2 (Inoki et al., 2002Manning et al., 2002Roux et al., 2004). Finally, low energy conditions inhibit mTORC1 by activating AMPK and by repressing the assembly of the TTT-RUVBL1/2 complex. (Inoki et al., 2003Gwinn et al., 2008Kim et al., 2013).

Glutamine, the most abundant amino acid in the body plays an important role in cellular proliferation. It is catabolized to α-ketoglutarate (αKG), an intermediate of the tricarboxylic acid (TCA) cycle through two deamination reactions in a process termed glutamine anaplerosis (DeBerardinis et al., 2007). The first reaction requires glutaminase (GLS) to generate glutamate, and the second occurs by the action of either glutamate dehydrogenase (GDH) or transaminases. Incorporation of αKG into the TCA cycle is the major anaplerotic step critical for the production of biomass building blocks including nucleotides, lipids and aa (Wise and Thompson, 2010). Recent studies have demonstrated that glutamine is also an important signaling molecule. Accordingly, it positively regulates the mTORC1 pathway by facilitating the uptake of leucine (Nicklin et al., 2009) and by promoting mTORC1 assembly and lysosomal localization (Duran et al., 2012;Kim et al., 2013).

Commonly occurring oncogenic signals directly stimulate nutrient metabolism, resulting in nutrient addiction. Oncogenic levels of Myc have been linked to increased glutamine uptake and metabolism through a coordinated transcriptional program (Wise et al., 2008Gao et al., 2009). Hence, it is not surprising that cancer cells are addicted to glutamine (Wise and Thompson, 2010). Thus, considering the prevalence of mTORC1 activation in cancer and the requirement of nutrients for cell proliferation, understanding how mTORC1 activation regulates nutrient levels and metabolism is critical. Activation of the mTORC1 pathway promotes the utilization of glucose, another nutrient absolutely required for cell growth. However, no study has yet investigated if and how the mTORC1 pathway regulates glutamine uptake and metabolism. Here, we discover a novel role of the mTORC1 pathway in the stimulation of glutamine anaplerosis by promoting the activity of GDH. Mechanistically, mTORC1 represses the transcription of SIRT4, an inhibitor of GDH. SIRT4 is a mitochondrial-localized member of the sirtuin family of NAD-dependent enzymes known to play key roles in metabolism, stress response and longevity (Haigis and Guarente, 2006). We demonstrate that the mTORC1 pathway negatively controls SIRT4 by promoting the proteasome-mediated degradation of cAMP-responsive element-binding (CREB) 2. We reveal that SIRT4 levels are decreased in a variety of cancers, and when expressed, SIRT4 delays tumor development in a Tsc2−/− mouse embryonic fibroblasts (MEFs) xenograft model. Thus, our findings provide new insights into how mTORC1 regulates glutamine anaplerosis, contributing therefore to the metabolic reprogramming of cancer cells, an essential hallmark to support their excessive needs for proliferation.

The mTORC1 pathway regulates glutamine metabolism via GDH

The activation of the mTORC1 pathway has recently been linked to glutamine addiction of cancer cells (Choo et al., 2010), yet it remains to be resolved if mTORC1 serves as a regulator of glutamine anaplerosis. To investigate this possibility, we first determined the effect of mTORC1 activity on glutamine uptake. We measured glutamine uptake rates in Tsc2 wild-type (WT) and Tsc2−/− MEFs. We found that Tsc2−/− MEFs consumed significantly more glutamine (Figure 1A), showing that mTORC1 activation stimulates the uptake of this nutrient. In addition, re-expression of Tsc2 in Tsc2−/− cells reduced glutamine uptake (Figure S1A). Similarly, mTORC1 inhibition with rapamycin resulted in decreased glutamine uptake in MEFs (Figure 1A). The decreased on glutamine uptake was significantly reduced after 6h of rapamycin treatment when compared to control (data not shown). To further confirm the role of mTORC1 on glutamine uptake, we used human embryonic kidney (HEK) 293T cells stably expressing either WT-RHEB or a constitutively active mutant (S16H) of RHEB. Increased mTORC1 signaling, as evidenced by sustained phosphorylation of S6K1 and its target rpS6, was observed in RHEB-expressing cells (Figure S1B). The activation of the mTORC1 pathway nicely correlated with an increase in glutamine consumption, therefore confirming that changes in mTORC1 signaling are reflected in cellular glutamine uptake (Figure S1B). To determine whether the modulation of glutamine uptake by the mTORC1 pathway occurs in cancer cells, we examined glutamine uptake rates in conditions of mTORC1 inhibition in human epithelial tumor cell lines, including the colon carcinoma DLD1, and the prostate cancer DU145. Rapamycin treatment resulted in decreased proliferation (data not shown) and yielded a decreased glutamine uptake in both cell lines (Figure 1B & data not shown). Glutamine is the major nitrogen donor for the majority of ammonia production in cells (Figure 1C) (Shanware et al., 2011). Consistent with decreased glutamine uptake, we found that ammonia levels were also diminished after rapamycin treatment (Figure S1C).

Figure 1  The mTORC1 pathway regulates glutamine metabolism via glutamate dehydrogenase

We next examined the fate of glutamine in conditions of mTORC1 inhibition, using gas chromatography/mass spectrometry (GC/MS) analysis to monitor the incorporation of uniformly labeled [U-13C5]-Glutamine into TCA cycle intermediates. Direct glutamine contribution to I̧KG (m+5), succinate (m+4), malate (m+4) and citrate (m+4) was decreased in rapamycin treated cells (Figure S1D) indicating that rapamycin impaired glutamine oxidation and subsequent carbon contribution into the TCA cycle.

To test whether glutamine uptake or glutamine conversion is limiting, we measured the intracellular levels of glutamine and glutamate in DLD1 cells. Increased levels of glutamine and/or glutamate will show that the catalyzing enzyme activity is limiting and not glutamine transport itself (Fendt et al., 2010). Rapamycin treatment resulted in increased intracellular levels of both glutamine and glutamate, showing that glutamate to αKG conversion is the critical limiting reaction (Figures 1D & 1E). To further confirm the implication of the glutamate catalyzing reaction we also measured αKG levels. If glutamate conversion is indeed critical we expect no alteration in αKG levels. This is expected because αKG is downstream of the potentially limiting glutamate conversion step, and it has been shown that product metabolite concentrations of limiting metabolic enzymes stay unaltered, while the substrate metabolite concentrations change to keep metabolic homeostasis (Fendt et al., 2010). We found that αKG levels were unaltered after rapamycin treatment, corroborating that the limiting enzymatic step is glutamate conversion (Figure 1F). To further confirm the limitation in glutamate-to-αKG conversion, we measured flux through this reaction. Strikingly, this flux was significantly reduced during rapamycin treatment (Figure 1G). Additionally, the inhibition of mTORC1 resulted in increased glutamate secretion (Figure 1H), thus confirming that the glutamate-to-αKG conversion step is a major bottleneck in the glutamine pathway during rapamycin treatment.

Glutamate conversion can be conducted by GDH (Figure 1C), suggesting that the mTORC1 pathway potentially regulates this enzyme. In agreement, rapamycin treatment resulted in decreased GDH activity in DLD1 cells (Figure 1I). To exclude that transaminases play a role in the mTORC1-induced regulation of glutamine metabolism, we used amin ooxyacetate (AOA) at a concentration shown to effectively inhibit the two predominant transaminases, alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (Figure 1C) (Wise et al., 2008), or rapamycin in the presence of α-15N-labeled glutamine. Subsequently, we measured 15N-labeling patterns and metabolite levels of alanine, an amino acid that is predominately produced by a transaminase-catalyzed reaction (Possemato et al., 2011). We found that AOA dramatically decreased 15N contribution and metabolite levels of alanine, while rapamycin only mildly affected the 15N contribution to this amino acid and showed no effect on alanine levels compared to the control condition (Figures 1J & S1E). In conclusion, these data demonstrate that GDH, not transaminases, plays a major role in the regulation of glutamine metabolism downstream of mTORC1.

mTORC1 controls GDH activity by repressing SIRT4

As our results show that mTORC1 regulates glutamate dehydrogenase, we sought to identify the molecular mechanism. SIRT4 is a negative regulator of GDH activity through ADP-ribosylation (Haigis et al., 2006), thus suggesting that mTORC1 potentially controls this step of glutamine metabolism via SIRT4. To test this possibility, we first assessed the ADP-ribosylation status of GDH by introducing biotin-labeled NAD followed by immunoprecipitation using avidin-coated beads. Rapamycin treatment led to an increase in the mono-ADP-ribosylation status of GDH, similar to that observed in cells stably expressing SIRT4 (Figure 2A). Importantly, we found that the knockdown of SIRT4 abrogated the rapamycin-induced decrease in the activity of GDH (Figures 2B & S2A). Strikingly, SIRT4 protein levels were increased upon mTORC1 inhibition in MEFs (Figures 2C). This regulation was confirmed in both DLD1 and DU145 cells (Figures 2D). Remarkably, rapamycin potently increased SIRT4 levels after 6h of treatment (Figure S2B), correlating with reduced glutamine consumption at the same time point (data not shown). In contrast, SIRT4 levels were not influenced by the treatment of MEFs with U0216, an inhibitor of MEK1/2 in the MAPK pathway (Figure S2C). All other mTOR catalytic inhibitors tested in Tsc2−/− MEFs also resulted in increased SIRT4 protein levels (Figure S2D). To evaluate a potential regulation of SIRT4 by mTORC2, we performed RNA interference (RNAi) experiments of either raptor or the mTORC2 component, rictor, in Tsc2−/− MEFs. The knockdown of raptor, but not rictor, was sufficient to increase SIRT4 protein levels, confirming the role of the mTORC1 pathway in the regulation of SIRT4 (Figure 2E). To investigate whether mTORC1 regulation of SIRT4 occurs in tumor samples, a TSC-xenograft model was used. We injected a TSC2−/− rat leiomyoma cell line; ELT3 cells, expressing either an empty vector (V3) or TSC2 (T3), in the flank of nude mice. SIRT4 levels were dramatically increased in TSC2-expressing tumors compared to empty vector samples (Figure S2E). In addition, we assessed the levels of SIRT4 in both ELT3 xenograft tumors and in mouse Tsc2+/− liver tumors after rapamycin treatment. As expected, these tumor samples exhibited robust elevation of SIRT4 after rapamycin treatment (Figures 2F & S2F). Thus, these data demonstrate that the mTORC1 pathway represses SIRT4 in several tumor systems.

Figure 2  mTORC1 controls glutamate dehydrogenase activity by repressing SIRT4

CREB2 regulates the transcription of SIRT4 in an mTORC1-dependent fashion

We next asked whether the mTORC1-dependent regulation of SIRT4 occurred at the mRNA level. Quantitative RT-PCR results show that rapamycin treatment significantly increased the expression of SIRT4mRNA in Tsc2−/− MEFs (Figure 3A). SIRT4 mRNA levels were dramatically reduced in Tsc2−/− MEFs compared to their WT counterpart (Figure 3B). Similar results were obtained from transcriptional profiling analysis of the SIRT4 gene from a previously published dataset (GSE21755) (Figure 3C) (Duvel et al. 2010). Altogether, our data demonstrate that mTORC1 negatively regulates the transcription of SIRT4. To determine whether CREB2 is involved in the mTORC1-dependent regulation of SIRT4, we performed RNAi experiments. The silencing of CREB2 abolished the rapamycin-induced expression of SIRT4 (Figures 3E & S3A). The knockdown of CREB1 did not affect the upregulation of SIRT4 upon mTORC1 inhibition, thus demonstrating the specificity of CREB2 to induce SIRT4 (Figure S3B), and the knockdown of CREB2 significantly abrogated the rapamycin-induced increase in the activity of the SIRT4 promoter.

Figure 3  SIRT4 is regulated at the mRNA level in an mTORC1-dependent fashion

mTORC1 regulates the stability of CREB2

We next investigated whether the mTORC1 pathway regulates CREB2. Although we did not observe major changes in Creb2 mRNA in normal growth conditions (Figure S4A), mTORC1 inhibition resulted in accumulation of CREB2 protein levels by 2h of rapamycin treatment (Figure 4A). U0126 failed to cause the accumulation of CREB2 (Figure S4B). In contrast, CREB1 protein levels were not affected after 24h rapamycin treatment (Figure S4C). As observed for SIRT4, mTOR catalytic inhibitors, and the specific knockdown of mTOR, resulted in upregulation of CREB2 protein levels (Figures S4D & S4E). CREB2 is upregulated in diverse cell types as a response to a variety of stresses, including hypoxia, DNA damage, and withdrawal of GFs, glucose, and aa (Cherasse et al., 2007Rouschop et al., 2010Yamaguchi et al., 2008;Whitney et al., 2009). Interestingly, mTORC1 is negatively regulated by all of these environmental inputs (Zoncu et al., 2011). Since mTORC1 signaling in Tsc2−/− MEFs is insensitive to serum deprivation, we assessed the role of aa withdrawal and re-stimulation on CREB2 levels. As shown in Fig. 4B, CREB2 accumulated upon aa deprivation, and was decreased following aa re-addition. This phenomenon required the action of the proteasome as MG132 efficiently blocked CREB2 degradation following aa re-addition. Importantly, we found that mTORC1 inhibition abrogated the aa-induced decrease of CREB2 (Figure 4B).

Figure 4  mTORC1 regulates the stability of CREB2

mTORC1 activation promotes the binding of CREB2 to βTrCP and modulates CREB2 ubiquitination

Next, we attempted to identify the E3 ubiquitin ligase that might be responsible for CREB2 turnover. Consistent with a recent study, we found CREB2 to bind the E3 ligase, βTrCP (Frank et al., 2010). However, other related E3 ligases including Fbxw2, Fbxw7a, and Fbxw9 did not bind to CREB2 (data not shown). The interaction of CREB2 with Flag-βTrCP1 was enhanced in the presence of insulin, and was abolished by rapamycin pretreatment (Figure 4D). Importantly, insulin treatment promoted the ubiquitination of CREB2 in an mTORC1-dependent fashion (Figure 4E). Altogether, our results support the notion that the mTORC1 pathway regulates the targeting of CREB2 for proteasome-mediated degradation. βTrCP binds substrates via phosphorylated residues in conserved degradation motifs (degrons), typically including the consensus sequence DpSGX(n)pS or similar variants. We found an evolutionary conserved putative βTrCP binding site (DSGXXXS) in CREB2 (Figure 4F). Interestingly, we noted a downward mobility shift in CREB2 protein with mTORC1 inhibition, consistent with a possible decrease in the phosphorylation of CREB2. (Figure 4A). Frank et al. (2010) showed that phosphorylation of the first serine in the degron motif corresponding to Ser218 is required for the CREB2/βTrCP interaction, and this modification acts as a priming site for a gradient of phosphorylation events on five proline-directed residues codons (T212, S223, S230, S234, and S247) that is required for CREB2 degradation during the cell cycle progression (Frank et al., 2010). Consistent with these observations, we found that the mutation of the five residues to alanine (5A mutant) resulted in strong stabilization of CREB2, comparable to the serine-to-alanine mutation on the priming Ser218 phosphorylation site (Figure S4G).

SIRT4 represses bioenergetics and cell proliferation

We observed that glutamine utilization is repressed by rapamycin treatment (Figure 1) and SIRT4 is induced by mTORC1 inhibition (Figure 2). Thus, we tested whether SIRT4 itself directly regulates cellular glutamine uptake. The stable expression of SIRT4 resulted in the repression of glutamine uptake in Tsc2−/− MEFs and DLD1 cells (Figures 5A & 5B). Glucose uptake was not affected by SIRT4 expression (data not shown). Because glutamine can be an important nutrient for energy production, we examined ATP levels in SIRT4 expressing cells. Consistent with reduced glutamine consumption, the expression of SIRT4 in Tsc2−/− cells resulted in decreased ATP/ADP ratio compared to control cells (Figure 5C). Cells produce ATP via glycolysis and oxidative phosphorylation (OXPHOS). To test the contribution of mitochondrial metabolism versus glycolysis to ATP, we measured the ATP/ADP ratio after the treatment with oligomycin, an inhibitor of ATP synthesis from OXPHOS. Importantly, the difference of the ATP/ADP ratio between control and SIRT4 expressing cells was abrogated by oligomycin (Figure 5C), further demonstrating that SIRT4 may repress the ability of cells to generate energy from mitochondrial glutamine catabolism. Mitochondrial glutamine catabolism is essential for energy production and viability in the absence of glucose (Yang et al., 2009Choo et al., 2010). Thus, we examined the effect of SIRT4 on the survival of Tsc2−/− MEFs during glucose deprivation. Control cells remained viable following 48h of glucose deprivation. Conversely, SIRT4 expressing cells showed a dramatic increase in cell death under glucose-free conditions, which was rescued by the addition of the cell permeable dimethyl-I̧KG (DM-I̧KG) (Figure 5D). Conversely, the expression of SIRT4 did not affect the viability of glucose-deprived Tsc2 WT MEFs (Figure S5A). Glucose deprivation also induced death of the human DU145 cancer cell line stably expressing SIRT4 (data not shown).

Figure 5  SIRT4 represses bioenergetics and proliferation

Glutamine is an essential metabolite for proliferating cells, and many cancer cells exhibit a high rate of glutamine consumption (DeBerardinis et al., 2007). Thus, decreased glutamine uptake in DLD1 and DU145 cancer cells expressing SIRT4 might result in decreased proliferation. Indeed, these cells grew significantly slower than did control cells. Remarkably, DM-I̧KG completely abrogated the decreased proliferation of SIRT4 expressing cells (Figure 5E & 5F), suggesting that repressed glutamine metabolism drove the reduced proliferation of cells expressing SIRT4. The expression of SIRT4 also slowed the proliferation of Tsc2−/− MEFs but did not affect Tsc2 WT MEFs (Figures S5B & S5C). Finally, to rule out that the effect on proliferation was due to aberrant localization and to off-target effects of the overexpressed protein, we examined the localization of HA-SIRT4. We found that SIRT4 is co-localized with the MitoTracker, a mitochondrial-selective marker (Figure S5D). Taken together, these data demonstrate that SIRT4 is a critical negative regulator of mitochondrial glutamine metabolism and cell proliferation.

SIRT4 represses TSC-tumor development

Recent studies have demonstrated a major role of glutamine metabolism in driving oncogenic transformation of many cell lines (Gao et al., 2009Wang et al., 2011). Since SIRT4 expression represses glutamine uptake and cell proliferation (Figure 5), we hypothesized that it could affect tumorigenesis. To test this idea, we assessed the role of SIRT4 in cell transformation by using an anchorage-independent growth assay. SIRT4 expression reduced the ability of Tsc2−/−p53−/− MEFs to grow in soft agar. However, the expression of SIRT4 in Tsc2+/+p53−/− did not impair their colony formation properties (Figure 6A). Tumor incidence in mice injected with Tsc2+/+p53−/− MEFs was not affected by SIRT4 (data not shown). Conversely, in the Tsc2−/−p53−/− cohort, SIRT4 reduced tumor incidence by 20 days at median (Figure 6B). SIRT4 expression inTsc2−/−p53−/− MEFs resulted in reduction of Ki-67 positivity by 60% (Figure 6E), consistent with the finding that SIRT4 inhibits the proliferation of these cells in vitro (Figure S5B). Finally, we performed a comprehensive meta-analysis of SIRT4 expression in human tumors and found significantly lower expression levels of SIRT4, relative to normal tissue, in bladder, breast, colon, gastric, ovarian and thyroid carcinomas (Figure 6F). Interestingly, loss of SIRT4 expression showed a strong association with shorter time to metastasis in patients with breast cancer (Figures 6G & 6H). Altogether, these data strongly suggest that SIRT4 delays tumorigenesis regulated by the mTORC1 pathway.

Figure 6
SIRT4 suppresses TSC-tumor development

The pharmacologic inhibition of glutamine anaplerosis synergizes with glycolytic inhibition to induce the specific death of mTORC1 hyperactive cells

The activation of mTORC1 leads to glucose and glutamine addiction as a result of increased uptake and metabolism of these nutrients (Choo et al., 2010Duvel et al., 2010 & Figure 1). These observations suggest that targeting this addiction offers an interesting therapeutic approach for mTORC1-driven tumors. The alkylating agent, mechlorethamine (Mechlo), incites cell toxicity in part by the inhibition of the GAPDH step of glycolysis via poly-ADP ribose polymerase (PARP)-dependent cellular consumption of cytoplasmic NAD+. The ultimate consequence is glycolytic inhibition, thus mimicking glucose deprivation (Zong et al., 2004). Treatment of Tsc2−/− MEFs with Mechlo decreased both NAD levels and lactate production (Figure 7A and data not shown). The decrease in NAD+ levels was rescued by addition of DPQ (Figure 7A), a PARP inhibitor (Zong et al., 2004). We next tested the ability of glutamine inhibition to determine the sensitivity of Tsc2−/− MEFs to Mechlo. As shown in Figure 7B, the treatment with EGCG, a GDH inhibitor (Figure 1G), potently synergized with Mechlo to kill Tsc2−/− MEFs with the greatest effect observed at 30μM (Figure 7B). As a result, this combination dramatically increased the cleavage of PARP, an apoptotic marker (Figure 7E). Similarly, glutamine deprivation sensitized Tsc2−/− MEFs to Mechlo (data not shown). The RNAi-mediated knockdown of GDH also synergized with Mechlo to induce death of Tsc2−/− MEFs (Figure 7D). Importantly, at these concentrations the combination did not induce death of a Tsc2-rescued cell line (Figure 7C).

Figure 7 The combination of glutamine metabolism inhibitors with glycolytic inhibition is an effective therapy to kill Tsc2−/− and PTEN−/− cells

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Because the metabolic properties of cells with activated mTORC1 by Tsc2– deficiency can be efficiently targeted, we also examined other cell types in which mTORC1 is hyperactive by the loss of PTEN. We found that the combination of Mechlo and EGCG was also effective to induce specific toxicity of PTEN−/− MEFs, while PTEN+/+ MEFs were not affected (Figures S7A & S7B). In addition, the PTEN-deficient human prostate adenocarcinoma cell line, LNCaP, was also sensitive to treatment with Mechlo and EGCG (Figure 7F). This effect was specifically due to lack of TCA cycle replenishment as pyruvate supplementation completely reversed the synergistic effect (Figure 7F). The combination of Mechlo with the GLS1 inhibitor, BPTES (Figure 1G), also resulted in decreased viability of Tsc2−/− cells but not of Tsc2-reexpressing cells (Figures S7C & S7D). Again, death in Tsc2−/− cells was rescued with pyruvate or OAA (Figure S7E). To further investigate if the potent cell death in Tsc2−/− was restricted to Mechlo, we used 2-DG, a glycolytic inhibitor. The combination of 2-DG with either EGCG or BPTES resulted in enhanced cell death of Tsc2−/− MEFs compared to single agent treatments (Figure S7F). This effect was also specific to Tsc2−/− cells, since this combination was less toxic in Tsc2-reexpressing MEFs (Figure S7G). Taken together, our results demonstrate that the combination treatments aimed at inhibiting glycolysis and glutaminolysis potently synergize to kill cells with hyperactive mTORC1 signaling.

Here, we define a novel mTORC1-regulated pathway that controls glutamine-dependent anaplerosis and energy metabolism (Figure 7G). We discovered that the mTORC1 pathway regulates glutamine metabolism by promoting the activity of GDH (Figures 1​-3).3). We show that this regulation occurs by repressing the expression of SIRT4, an inhibitor of GDH (Figures 2 & 3). Molecularly, this is the result of mTORC1-dependent proteasome-mediated degradation of the SIRT4 transcriptional regulator, CREB2 (Figure 4). Interestingly, the modulation of CREB2 levels correlates with increased sensitivity to glutamine deprivation (Ye et al., 2010Qing et al., 2012), fitting with our model of glutamine addiction as a result of mTORC1 activation (Choo et al., 2010). Our data suggest that mTORC1 promotes the binding of the E3 ligase, βTrCP, to CREB2 (Figure 4D), promoting CREB2 degradation by the proteasome (Figure 4E). A previous study has demonstrated that five residues in CREB2 located next to the βTrCP degron are required for its stability (Frank et al., 2010). Accordingly, the mutation of these residues to alanine resulted in stabilization of CREB2 and SIRT4 following insulin and aa-dependent mTORC1 activation (Figure 4G). Future work is aimed at determining if mTORC1 and/or downstream kinases are directly responsible for the multisite phosphorylation of CREB2.

The identification of CREB2 as an mTORC1-regulated transcription factor increases the repertoire of transcriptional regulators modulated by this pathway including HIF1α (glycolysis), Myc (glycolysis) and SREBP1 (lipid biosynthesis) (Duvel et al., 2010Yecies and Manning, 2011). The oncogene Myc has also been linked to the regulation of glutamine metabolism by increasing the expression of the surface transporters ASCT2 and SN2, and the enzyme GLS. Thus, enhanced activity of Myc correlates with increased glutamine uptake and glutamate production (Wise et al., 2008Gao et al., 2009). Our findings describe a new level of control to this metabolic node as shown by the modulation of the glutamate-to-αKG flux (Figure 2). This regulation is particularly relevant as some cancer cells produce more than 50% of their ATP by oxidizing glutamine-derived αKG in the mitochondria (Reitzer et al JBC, 1979). Therefore, these studies support the notion that Myc and CREB2/SIRT4 cooperate to regulate the metabolism of glutamine to αKG.

7.8.4  Rab1A and small GTPases Activate mTORC1

7.8.4.1 Rab1A Is an mTORC1 Activator and a Colorectal Oncogene

Thomas JD1Zhang YJ2Wei YH3Cho JH3Morris LE3Wang HY4Zheng XF5.
Cancer Cell. 2014 Nov 10; 26(5):754-69.
http://dx.doi.org:/10.1016/j.ccell.2014.09.008.

Highlights

  • Rab1A mediates amino acid signaling to activate mTORC1 independently of Rag
  • Rab1A regulates mTORC1-Rheb interaction on the Golgi apparatus
  • Rab1A is an oncogene that is frequently overexpressed in human cancer
  • Hyperactive amino acid signaling is a common driver for cancer

Amino acid (AA) is a potent mitogen that controls growth and metabolism. Here we describe the identification of Rab1 as a conserved regulator of AA signaling to mTORC1. AA stimulates Rab1A GTP binding and interaction with mTORC1 and Rheb-mTORC1 interaction in the Golgi. Rab1A overexpression promotes mTORC1 signaling and oncogenic growth in an AA- and mTORC1-dependent manner. Conversely, Rab1A knockdown selectively attenuates oncogenic growth of Rab1-overexpressing cancer cells. Moreover, Rab1A is overexpressed in colorectal cancer (CRC), which is correlated with elevated mTORC1 signaling, tumor invasion, progression, and poor prognosis. Our results demonstrate that Rab1 is an mTORC1 activator and an oncogene and that hyperactive AA signaling through Rab1A overexpression drives oncogenesis and renders cancer cells prone to mTORC1-targeted therapy.

7.8.4.2 Regulation of TOR by small GTPases

Raúl V Durán1 and Michael N Halla,1
EMBO Rep. 2012 Feb; 13(2): 121–128.
http://dx.doi.org/10.1038%2Fembor.2011.257

TOR is a conserved serine/threonine kinase that responds to nutrients, growth factors, the bioenergetic status of the cell and cellular stress to control growth, metabolism and ageing. A diverse group of small GTPases including Rheb, Rag, Rac1, RalA and Ryh1 play a variety of roles in the regulation of TOR. For example, while Rheb binds to and activates TOR directly, Rag and Rac1 regulate its localization and RalA activates it indirectly through the production of phosphatidic acid. Here, we review recent findings on the regulation of TOR by small GTPases.

The growth-controlling TOR signalling pathway is structurally and functionally conserved from unicellular eukaryotes to humans. TOR, an atypical serine/threonine kinase, was originally discovered inSaccharomyces cerevisiae as the target of rapamycin (Heitman et al, 1991). It was later described in many other organisms including the protozoan Trypanosoma brucei, the yeast Schizosaccharomyces pombe, photosynthetic organisms such as Arabidopsis thaliana and Chlamydomonas reinhardtii, and in metazoans such as Caenorhabditis elegansDrosophila melanogaster and mammals. TOR integrates various stimuli to control growth, metabolism and ageing (Avruch et al, 2009Kim & Guan, 2011Soulard et al, 2009;Wullschleger et al, 2006Zoncu et al, 2011a). In mammals, mTOR is activated by nutrients, growth factors and cellular energy, and is inhibited by stress. Thus, the molecular regulation of TOR is complex and diverse. Among the increasing number of TOR regulators, small GTPases are currently garnering much attention. Small GTPases (20–25 kDa) are either in an inactive GDP-bound form or an active GTP-bound form (Bos et al, 2007). GDP–GTP exchange is regulated by GEFs, which mediate the replacement of GDP by GTP, and by GAPs, which stimulate the intrinsic GTPase activity of a cognate GTPase to convert GTP into GDP (Fig 1). Upon activation, small GTPases interact with effector proteins, thereby stimulating downstream signalling pathways. Small GTPases constitute a superfamily that comprises several subfamilies, such as the Rho, Ras, Rab, Ran and Arf families. Rheb, Rag, RalA, Rac1 and Ryh1, all members of the small GTPase superfamily, play a role in the concerted regulation of TOR by different stimuli. This review summarizes recent advances in the understanding of TOR regulation by these small GTPases.

Regulation of small GTPases by GEFs and GAPs

Regulation of small GTPases by GEFs and GAPs

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Figure 1 Regulation of small GTPases by GEFs and GAPs. A guanine nucleotide exchange factor (GEF) replaces GDP with GTP to activate the signalling function of the GTPase. Conversely, a GTPase-activating protein (GAP) stimulates hydrolysis of GTP into GDP

The TOR complexes

TOR is found in two functionally and structurally distinct multiprotein complexes, named TORC1 and TORC2 (Avruch et al, 2009Kim & Guan, 2011Soulard et al, 2009Wullschleger et al, 2006Zoncu et al, 2011a). TORC1 regulates several cellular processes including protein synthesis, ribosome biogenesis, nutrient uptake and autophagy. TORC2, in turn, regulates actin cytoskeleton organization, cell survival, lipid synthesis and probably other processes. TORC1 and TORC2 are rapamycin-sensitive and rapamycin-insensitive, respectively, although in some organisms, for example A. thaliana and T. brucei, this rule does not apply (Barquilla et al, 2008Mahfouz et al, 2006). Nevertheless, long-term treatment with rapamycin can also indirectly inhibit TORC2 in mammalian cell lines (Sarbassov et al, 2006). Furthermore, there is accumulating evidence that not all TORC1 readouts are rapamycin-sensitive (Choo & Blenis, 2009Dowling et al, 2010Peterson et al, 2011).

Upstream of TOR

Four main inputs regulate mTORC1: nutrients, growth factors, the bioenergetic status of the cell and oxygen availability. It is well established that growth factors activate mTORC1 through the PI3K–AKT pathway. Once activated, AKT phosphorylates and inhibits the heterodimeric complex TSC1–TSC2, a GAP for Rheb and thus an inhibitor of mTORC1 (Avruch et al, 2009). The TSC1–TSC2 heterodimer is a ‘reception centre’ for various stimuli that are then transduced to mTORC1, including growth factor signals transduced through the AKT and ERK pathways, hypoxia through HIF1 and REDD1, and energy status through AMPK (Wullschleger et al, 2006). In addition to the small GTPases Rheb and Rag (see below), PA also binds to and activates mTORC1 (Fang et al, 2001). Pharmacological or genetic inhibition of PA production, through the inhibition of PLD, impairs activation of mTORC1 by nutrients and growth factors (Fang et al, 2001). Moreover, elevated PLD activity leads to rapamycin resistance in human breast cancer cells (Chen et al, 2003), further supporting a role for PA as an mTORC1 regulator. As discussed below, the small GTPase RalA participates in the mechanism by which PA activates mTORC1 (Maehama et al, 2008Xu et al, 2011).

In the case of nutrients, amino acids in particular, several elements mediate the activation of TORC1. As discussed below, the Rag GTPases are necessary to activate TORC1 in response to amino acids (Binda et al, 2009Kim et al, 2008Sancak et al, 2008). In mammals, it has also been proposed that amino acids stimulate an increase in intracellular calcium concentration, which in turn activates mTORC1 through the class III PI3K Vps34 (Gulati et al, 2008).

Downstream of TOR

TORC1 regulates growth-related processes such as transcription, ribosome biogenesis, protein synthesis, nutrient transport and autophagy (Wullschleger et al, 2006). In mammals, the best-characterized substrates of mTORC1 are S6K and 4E-BP1, through which mTORC1 stimulates protein synthesis. mTORC1 activates S6K, which is a positive regulator of protein synthesis, and inhibits 4E-BP1, which is a negative regulator of protein synthesis. Upon phosphorylation by mTORC1, 4E-BP1 releases eIF4E. Once released from 4E-BP1, eIF4E interacts with the eIF4G subunit of the eIF4F complex, allowing initiation of translation. In mammals, 4E-BP1 participates mainly in the regulation of cell proliferation and metabolism (Dowling et al, 2010). In S. cerevisiae, the main substrate of TORC1 is the S6K orthologue Sch9 (Urban et al, 2007). Sch9 is required for the activation of ribosome biogenesis and translation initiation stimulated by TORC1. Furthermore, it participates in TORC1-dependent inhibition of G0 phase entry.

Regulation of TOR by Rheb

The small GTPase Rheb was first identified in 1994 in a screen for genes induced in neurons in response to synaptic activity (Yamagata et al, 1994), and was first described to interact with the Raf1 kinase (Yee & Worley, 1997). A later report showed that loss of Rhb1, the Rheb orthologue in S. pombe, causes a starvation-like growth arrest (Mach et al, 2000). In 2003, several independent groups working with mammalian cells in vitro and Drosophila in vivo demonstrated that Rheb is the target of the TSC1–TSC2 GAP and a TORC1 activator (Avruch et al, 2009).

Interestingly, the Rheb–mTOR interaction both in vivo and in vitro does not depend on GTP loading of Rheb. This is unusual for GTPases as GTP loading usually regulates effector binding. However, GTP loading of Rheb is crucial for the activation of mTOR kinase activity (Sancak et al, 2007). Conversely, mTOR becomes inactive after association with a nucleotide-deficient Rheb (Long et al, 2005a; Fig 2). Similar results were obtained in S. pombe, making use of mutations that hyperactivate Rheb by increasing its overall GTP : GDP binding ratio (Urano et al, 2005). In contrast to the situation in mammals, interaction of Rheb with SpTOR2 in fission yeast is detected only with a hyperactive Rheb mutant. This suggests that, in S. pombe, Rheb binds to SpTOR2 in a GTP-dependent manner.

Rheb activates TORC1

Rheb activates TORC1

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3271343/bin/embor2011257f2.gif

Figure 2 Rheb activates TORC1 both directly and indirectly. GTP-bound Rheb interacts directly with TORC1 to activate TORC1 kinase. GTP-bound Rheb also activates RalA, which activates PLD to increase production of PA. PA in turn interacts with TORC1

In addition to the direct interaction between mTOR and Rheb, activation of PA production by Rheb is an additional mechanism by which Rheb might regulate mTORC1. Rheb binds to and activates PLD in a GTP-dependent manner (Sun et al, 2008). PLD produces PA, which binds directly to and upregulates mTORC1. This finding reveals cross-talk between the TSC–Rheb and the PA pathways in the regulation of mTORC1 signalling. A recent study by Yoon and colleagues further demonstrated the role of PLD in mTORC1 regulation (Yoon et al, 2011). They showed that amino acids activate PLD through translocation of PLD to the lysosomal compartment. This translocation is positively regulated by human Vps34 and is necessary for the activation of mTORC1 by amino acids. These authors propose the existence of a Vps34–PLD1 pathway that activates mTORC1 in parallel to the Rag pathway (Yoon et al, 2011).

Although Rheb is required for the activation of mTORC1 by amino acids, Rheb itself does not participate in amino acid sensing, and GTP-loading of Rheb is not affected by amino acid depletion (Long et al, 2005b). Furthermore, amino acid depletion inhibits mTORC1 even in TSC2−/− fibroblasts (Roccio et al, 2006). Nevertheless, interaction of mTORC1 with Rheb depends on amino acid availability (Long et al, 2005b). As discussed below, the current model proposes that amino acids mediate translocation of mTORC1 to the lysosomal surface where mTORC1 interacts with and is activated by GTP-loaded Rheb (Sancak et al, 2008).

Regulation of TOR by Rag

Rag GTPases have unique features among the Ras GTPase subfamily members: they form heterodimers and lack a membrane-targeting sequence (Nakashima et al, 1999Sekiguchi et al, 2001). Gtr1 in S. cerevisiaewas the first member of this GTPase subfamily to be identified (Bun-Ya et al, 1992). The mammalian RagA and RagB GTPases were later described as Gtr1 orthologues (Hirose et al, 1998). Gtr2 in yeast (Nakashima et al, 1999) and its mammalian orthologues RagC and RagD (Sekiguchi et al, 2001) were subsequently discovered due to their ability to form heterodimers with Gtr1 in yeast and RagA and RagB in mammals, respectively. The crystal structure of the Gtr1–Gtr2 complex has been determined recently (Gong et al, 2011). Gtr1 and Gtr2 have similar structures, organized in two domains: an amino-terminal GTPase domain (designated as the G domain) and a carboxy-terminal domain. The Gtr1–Gtr2 heterodimer presents a pseudo-twofold symmetry resembling a horseshoe. The crystal structure reveals that Gtr1–Gtr2 dimerization results from extensive contacts between the C-terminal domains of both proteins, while the G domains do not contact each other (Gong et al, 2011).

Rag proteins mediate the activation of TORC1 in response to amino acids.

Rag proteins mediate the activation of TORC1 in response to amino acids.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3271343/bin/embor2011257f3.gif

Figure 3 Rag proteins mediate the activation of TORC1 in response to amino acids. The RagA/B–RagC/D heterodimer is anchored to the MP1–p14–p18 complex on the surface of the lysosome.

Overexpressed Rheb is mislocalized throughout the cell, and therefore interaction of mTORC1 with Rheb does not require amino-acid-induced translocation of mTORC1 to the lysosome. The model is further supported by observations in Drosophila showing that expression of a constitutively active mutant of RagA significantly increases the size of individual cells, whereas expression of a dominant negative mutant of RagA reduces cell size (Kim et al, 2008). Moreover, Rag plays a role in TORC1-mediated inhibition of autophagy both in Drosophila (Kim et al, 2008) and in human cells (Narita et al, 2011).

mTOR and small GTPases are therapeutic targets in the treatment of cancer (Berndt et al, 2011Dazert & Hall, 2011). Aberrant activation of GTPases, including Ras, Rho, Rab or Ran GTPases, promotes cell transformation and cancer (Agola et al, 2011Ly et al, 2010Pylayeva-Gupta et al, 2011), in some cases by acting in the mTOR pathway. Targeting GTPases by using farnesyltransferase inhibitors or geranylgeranyltransferase inhibitors affects signal transduction pathways, cell cycle progression, proliferation and cell survival. Both types of inhibitor are currently under investigation for cancer therapy, although only a small subset of patients responds to these inhibitors (Berndt et al, 2011). A better understanding of the relationship between GTPases and mTOR is essential for the design of combined therapies.

From a mechanistic point of view, research on TOR in different systems is continually adding new insight on the role of TOR in cell biology. However, what is lacking is an integration of the various proposed regulators of TOR, in particular small GTPases (see Sidebar A).

Sidebar A | In need of answers

  1. How are amino acids sensed by the cell?
  2. What is the mechanism by which amino acids regulate the GTP-loading of Rag proteins? What are the GEF and GAP for the Rag proteins?
  3. Is there a GEF that regulates the GTP-loading of Rheb?
  4. What is the molecular mechanism by which Rheb activates TORC1?
  5. How is the dual effect of Rac1 being both upstream and downstream from TOR regulated?
  6. How are the diverse GTPases that impinge on TOR integrated?

7.8.5 PI3K.Akt signaling in osteosarcoma

Zhang J1Yu XH2Yan YG1Wang C1Wang WJ3.
Clin Chim Acta. 2015 Apr 15; 444:182-192.
http://dx.doi.org:/10.1016/j.cca.2014.12.041

Highlights

  • Activation of the PI3K/Akt signaling regulates various cellular functions.
  • The PI3K/Akt signaling may play a key role in the progression of osteosarcoma.
  • Targeting the PI3K/Akt signaling has therapeutic potential for osteosarcoma.

Osteosarcoma (OS) is the most common nonhematologic bone malignancy in children and adolescents. Despite the advances of adjuvant chemotherapy and significant improvement of survival, the prognosis remains generally poor. As such, the search for more effective anti-OS agents is urgent. The phosphatidylinositol 3-kinase (PI3K)/Akt pathway is thought to be one of the most important oncogenic pathways in human cancer. An increasing body of evidence has shown that this pathway is frequently hyperactivated in OS and contributes to disease initiation and development, including tumorigenesis, proliferation, invasion, cell cycle progression, inhibition of apoptosis, angiogenesis, metastasis and chemoresistance. Inhibition of this pathway through small molecule compounds represents an attractive potential therapeutic approach for OS. The aim of this review is to summarize the roles of the PI3K/Akt pathway in the development and progression of OS, and to highlight the therapeutic potential of targeting this signaling pathway. Knowledge obtained from the application of these compounds will help in further understanding the pathogenesis of OS and designing subsequent treatment strategies.

PK.Akt signaling

PK.Akt signaling

http://ars.els-cdn.com/content/image/1-s2.0-S0009898115001059-gr1.sml

PI3K/Akt signaling

PI3K.Akt signaling pathway

PI3K.Akt signaling pathway

http://ars.els-cdn.com/content/image/1-s2.0-S0009898115001059-gr2.sml

PI3K/Akt signaling pathway

PK.Akt therapeutic target

PK.Akt therapeutic target

http://ars.els-cdn.com/content/image/1-s2.0-S0009898115001059-gr3.sml

PK/Akt therapeutic target

7.8.6 The mTORC1-S6K1 Pathway Regulates Glutamine Metabolism through the eIF4B-Dependent Control of c-Myc Translation

Csibi A1Lee G1Yoon SO1Tong H2,…, Fendt SM4Roberts TM2Blenis J5.
Curr Biol. 2014 Oct 6; 24(19):2274-80.
http://dx.doi.org:/10.1016/j.cub.2014.08.007

Growth-promoting signaling molecules, including the mammalian target of rapamycin complex 1 (mTORC1), drive the metabolic reprogramming of cancer cells required to support their biosynthetic needs for rapid growth and proliferation. Glutamine is catabolyzed to α-ketoglutarate (αKG), a tricarboxylic acid (TCA) cycle intermediate, through two deamination reactions, the first requiring glutaminase (GLS) to generate glutamate and the second occurring via glutamate dehydrogenase (GDH) or transaminases. Activation of the mTORC1 pathway has been shown previously to promote the anaplerotic entry of glutamine to the TCA cycle via GDH. Moreover, mTORC1 activation also stimulates the uptake of glutamine, but the mechanism is unknown. It is generally thought that rates of glutamine utilization are limited by mitochondrial uptake via GLS, suggesting that, in addition to GDH, mTORC1 could regulate GLS. Here we demonstrate that mTORC1 positively regulates GLS and glutamine flux through this enzyme. We show that mTORC1 controls GLS levels through the S6K1-dependent regulation of c-Myc (Myc). Molecularly, S6K1 enhances Myc translation efficiency by modulating the phosphorylation of eukaryotic initiation factor eIF4B, which is critical to unwind its structured 5′ untranslated region (5’UTR). Finally, our data show that the pharmacological inhibition of GLS is a promising target in pancreatic cancers expressing low levels of PTEN.

Highlights

  • The mTORC1 pathway positively regulates GLS and glutamine flux
  • mTORC1 controls the translation efficiency of Myc mRNA
  • S6K1 regulates Myc translation through eIF4B phosphorylation
  • Inhibition of GLS decreases the growth of pancreatic cancer cells

Figure 1. The mTORC1 Pathway Regulates GLS1 (A–C and E) GLS protein levels in whole cell lysates from Tsc2 WT and Tsc22/2 MEFs treated with rapamycin (Rapa) for 8 hr (A); HEK293T cells stably expressing Rheb WT, the mutant S16H Rheb, or EV and treated with rapamycin for 24 hr (B); Tsc22/2 MEFs treated with rapamycin at the indicated time points (C); and Tsc2 WT and Tsc22/2 MEFs treated with the indicated compounds for 8 hr (E). The concentrations of the compounds were as follows: rapamycin, 20 ng/ml; LY294002 (LY), 20 mM; and BEZ235, 10 mM. (D) Time course of glutamine consumption in Tsc22/2 MEFs incubated with or without 20ng/ml rapamycin for 24 hr. Each time data point is an average of triplicate experiments. (F) Intracellular glutamine levels in Tsc22/2 MEFs treated with rapamycin for 24 hr. (G) Glutamineflux inTsc22/2 MEFs expressing an EV or re-expressingTSC2 treated with theindicated compounds for 24hr.The concentrations of the compounds were as follows: rapamycin 20 ng/ml; LY294002, 20 mM; BEZ235, 10 mM; BPTES, 10 mM; and 6-diazo-5-oxo-l-norleucine, 1mM. The mean is shown. Error bars represent the SEM from at least three biological replicates. Numbers below the immunoblot image represent quantification normalized to the loading control. See also Figure S1.

Figure2. The mTORC1 Pathway Regulates GLS1 via Myc GLS and Myc protein levels in whole cell lysates from BxPC3 cells transfected with a nontargeting control (NTC) siRNA or four independent siRNAs against Myc for 72 hr (A), Tsc2 WT and Tsc22/2 MEFs treated with rapamycin (20 ng/ml) for 8 hr (B), and Tsc22/2 MEFs stably expressing Myc or EV and treated with rapamycin (20 ng/ml) for 24 hr (C).

Figure 3. The mTORC1 Substrate S6K1 Controls GLS through Myc mRNA Translation (A) Normalized luciferase light units of Tsc22/2 MEFs stably expressing a Myc-responsive firefly luciferase construct (Myc-Luc) or vector control (pCignal Lenti-TRE Reporter). Myc transcriptional activity was measured after treatment with rapamycin (20 ng/ml) or PF4708671 (10 mM) for 8 hr. (B) GLS and Myc protein levels in whole cell lysates from HEK293T cells expressing HA-S6K1-CA (F5A-R3A-T389E) or EV treated with rapamycin (20 ng/ml) for 24 hr. HA, hemagglutinin. (CandD) Intracellular glutamine levels of Tsc22/2 MEFs stably expressing S6K-CA(F5A/R5A/T389E, mutating either the three arginines or all residues within the RSPRR motif to alanines shows the same effect; [10]) or empty vector and treated with rapamycin (20 ng/ml) or DMSO for 48 hr (C) or transfected with NTC siRNA or siRNA against both S6K1/2 (D). 24 hr posttransfection, cells transfected with NTC siRNA were treated with PF4708671 (10 mM) or DMSO for 48 hr. (E) Glutamine consumption of Tsc22/2 MEFs transfected with NTC siRNA or siRNA against both S6K1/2. 72 hr posttransfection, media were collected, and levels of glutamine in the media were determined. (F) Normalized luciferase light units of Tsc2WTMEFs transfected with thepDL-N reporter construct containing the 50 UTR of Myc under the control of Renilla luciferase. Firefly luciferase was used as an internal control. 48hr posttransfection, cells were treated with rapamycin (20ng/ml) or PF4708671 (10mM) for 8h. (G) Relative levels of Myc, Gls, and Actin mRNA in each polysomal gradient fraction. mRNA levels were measured by quantitative PCR and normalized to the 5S rRNA level. HEK293T cells were treated with rapamycin (20 ng/ml) for 24 hr, and polysomes were fractionated on sucrose density gradients. The values are averaged from two independent experiments performed in duplicate, and the error bars denote SEM (n = 4). (Hand I) GLS and Myc protein levels in whole cell lysates from Tsc22/2 MEFs transfected with NTC siRNA or two independent siRNAs against eIF4B for 72hr (H) and Tsc22/2 MEFs stably expressing eIF4B WT, mutant S422D, or EV) and treated with rapamycin for 24 hr (I). The mean is shown. Error bars represent the SEM from at least three biological replicates. The asterisk denotes a nonspecific band. The numbers below the immunoblot image represent quantification normalized to the loading control. See also Figures S2 and S3.

Figure 4. Inhibition of GLS Reduces the Growth of Pancreatic Cancer Cells (A) GLS and Myc protein levels in whole cell lysates from BxPC3, MIAPaCa-2, or AsPC-1 cells treated with rapamycin (20 ng/ml) or BEZ235 (1 mM) for 24 hr. (B) Glutamine consumption of BxPC3 or AsPC-1 cells 48 hr after plating. (Cand D) Soft agar assays with BxPC3 or AsPC-1 cells treated with BPTES (10 mM), the combination of BPTES (10 mM) + OAA (2 mM) (C) and BxPC3 or AsPC-1 cells treated with BPTES, and the combination of BPTES (10 mM) + NAC (10 mM) (D). NS, not significant. The mean is shown. Error bars represent the SEM from at least three biological replicates.

7.8.7 Localization of mouse mitochondrial SIRT proteins

Nakamura Y1Ogura MTanaka DInagaki N.
Biochem Biophys Res Commun. 2008 Feb 1; 366(1):174-9
http://www.ncbi.nlm.nih.gov/pubmed/18054327#

Yeast silent information regulator 2 (SIR2) is involved in extension of yeast longevity by calorie restriction, and SIRT3, SIRT4, and SIRT5 are mammalian homologs of SIR2 localized in mitochondria. We have investigated the localization of these three SIRT proteins of mouse. SIRT3, SIRT4, and SIRT5 proteins were localized in different compartments of the mitochondria. When SIRT3 and SIRT5 were co-expressed in the cell, localization of SIRT3 protein changed from mitochondria to nucleus. These results suggest that the SIRT3, SIRT4, and SIRT5 proteins exert distinct functions in mitochondria. In addition, the SIRT3 protein might function in nucleus

Fig. 1. Localization of SIRT3, SIRT4, and SIRT5 in mitochondria. (A) Confocal microscopy. SIRT3-myc (upper panels), SIRT4-myc (middle panels), and SIRT5-FLAG (lower panels) were expressed in COS7 cells and immunostained with anti-myc antibody or anti-FLAG antibody. Mitochondria and nuclei were stained by MitoTracker Red and DAPI, respectively, and fluorescent images were obtained using a confocal microscope. (B) Fractionation of post-nuclear supernatant. SIRT3-myc, SIRT4-myc, and SIRT5-FLAG proteins each was expressed in COS7 cells, and the obtained PNS was fractionated into mitochondria-enriched precipitate (P1), microsome-enriched precipitate (P2), and supernatant (S) fractions. The three fractions were separated by SDS–PAGE and then analyzed by Western blotting using anti-myc antibody for SIRT3-myc and SIRT4-myc or anti-FLAG antibody for SIRT5-FLAG. Hsp60, calnexin, and GAPDH were used as endogenous markers for mitochondria, microsome, and cytosol, respectively. (C) Alkaline treatment of mitochondria. Mitochondria prepared from the COS7 cells expressing each of the SIRT3-myc, SIRT4-myc, and SIRT5-FLAG proteins were treated with Na2CO3. The reaction mixture was centrifuged to separate the precipitate and supernatant fractions, containing membrane-integrated proteins and soluble proteins, respectively. The two fractions were analyzed by Western blotting. Cytochrome c (cytc) and hsp60 were used as endogenous protein markers for mitochondrial soluble protein. (D) Submitochondrial fractionation. The mitochondria from COS7 cells expressing one of three SIRT proteins were treated with either H2O (hypotonic) or TX-100, and then treated with trypsin. The reaction mixtures were analyzed by Western blotting. Cytochrome c and hsp60 were used as endogenous markers for mitochondrial intermembrane space protein and matrix protein, respectively.

Fig. 2. Localization of SIRT3 when co-expressed with SIRT5. (A) Confocal microscopic analysis of COS7 cells expressing two of the three mitochondrial SIRT proteins. SIRT3-myc and SIRT5-FLAG (upper panels), SIRT3-myc and SIRT4-FLAG (middle panels), and SIRT4-myc and SIRT5-FLAG (lower panels) were co-expressed in COS7 cells, and immunostained using antibodies against myc tag and FLAG tag. Nuclei were stained by DAPI. (B) Subcellular fractionation of PNS. PNS of COS7 cells co-expressing SIRT3-myc and SIRT5-FLAG was fractionated into mitochondria-enriched precipitate (P1), microsome-enriched precipitate (P2), and supernatant (S) fractions, and these fractions along with whole cell lysate were analyzed by Western blotting. (C) Subcellular fractionation using digitonin. COS7 cells expressing either SIRT3-myc (left) or SIRT5-FLAG (middle) or both (right) were solubilized by digitonin, and the obtained lysate was centrifuged and fractionated into nuclear-enriched insoluble (INS), and soluble (SOL) fractions. Hsp60 and laminA/C were used as endogenous markers for mitochondria protein and nucleus protein, respectively.

Because the segment containing amino acid residues 66– 88 potentially forms a basic amphiphilic a-helical structure, it could serve as a MTS. To examine the role of this segment, SIRT3 mutant SIRT3mt, in which the four amino acid residues 72–75 were replaced by four alanine residues, was constructed (Fig. 3A). When SIRT3mt alone was expressed in COS7 cells, SIRT3mt protein was not detected in mitochondria but was widely distributed in the cell in confocal microscopic analysis (Fig. 3B, upper panels). In addition, when SIRT3mt and SIRT5 were co-expressed, the distribution of SIRT3mt protein was not changed compared to that expressed alone (Fig. 3B, lower panels). In fractionation of PNS, SIRT3mt protein was fractionated into S fraction both when SIRT3mt was expressed alone and when SIRT3mt and SIRT5 were co-expressed. SIRT5 protein was localized in mitochondria when SIRT3mt and SIRT5 were co-expressed (Fig. 3C). These results indicate that the MTS is necessary not only for targeting SIRT3 to mitochondria in the absence of SIRT5 but also for targeting SIRT3 to nucleus in the presence of SIRT5.

Fig. 3. Effect of disruption of putative mitochondrial targeting signal of SIRT3. (A) Alanine replacement of putative MTS of SIRT3. Four residues of the putative MTS of SIRT3 (amino acid residues 72–75) were replaced with four alanine residues. In the SIRT3mt sequence, amino acid residues identical with wild-type SIRT3 protein are indicated with dots. (B) Confocal microscopy. Immunofluorescent images of COS7 cells expressing SIRT3mt-myc alone (upper panels) or both SIRT3mt-myc and SIRT5-FLAG (lower panels) are shown. Mitochondria and nuclei were stained by MitoTracker Red and DAPI, respectively. (C) Subcellular fractionation of PNS. PNSs of COS7 cells expressing SIRT3mt-myc alone (an upper panel) or co-expressing SIRT3mt-myc and SIRT5-FLAG (middle and lower panels) were centrifuged and fractionated into mitochondria-enriched precipitate (P1), microsome-enriched precipitate (P2), and supernatant (S) fractions. The fractions were analyzed by Western blotting.

Fig. 4. Effect of disruption of putative nuclear localization signal of SIRT3. (A) Comparison of the amino acid sequences of putative NLS of SIRT3, SIRT3nu, and SV40 large T antigen. Three basic amino acid residues of the putative NLS of SIRT3 (amino acid residues 214–216) were replaced with three alanine residues. In the SIRT3nu sequence, amino acid residues identical with wild-type SIRT3 protein are indicated with dots. The classical NLS of SV40 large T antigen also is shown (SV40). (B) Confocal microscopy. Immunofluorescent images of COS7 cells expressing SIRT3nu-myc alone (upper panels) or both SIRT3nu-myc and SIRT5-FLAG (lower panels) are shown. Mitochondria and nuclei were stained by MitoTracker Red and DAPI, respectively. (C) Subcellular fractionation of PNS. PNSs of the COS7 cells expressing SIRT3nu-myc alone (an upper panel) or co-expressing SIRT3numyc and SIRT5-FLAG (middle and lower panels) were fractionated into mitochondria-enriched precipitate (P1), microsome-enriched precipitate (P2), and supernatant (S) fractions. The fractions were analyzed by Western blotting.

The sequence containing amino acid sequence 213-219 of the SIRT3 closely resembles the putative protein classical NLS of the SV40 T antigen (Fig. 4A). To examine whether this sequence functions as a NLS, the mutant SIRT3 protein SIRT3nu, in which the three basic amino acid residues (214–216) in the putative NLS of SIRT3 were replaced by three alanine residues (Fig. 4A), was constructed. When SIRT3nu alone was expressed in COS7 cells, it was localized in mitochondria (Fig. 4B, upper panels). In the cells co-expressing SIRT3nu and SIRT5, a shift of SIRT3nu protein to the nucleus was not observed, and SIRT3nu protein and a part of SIRT5 protein were scattered widely in the cell in confocal microscopic analysis (Fig. 4B, lower panels). In fractionation of PNS, all of the SIRT3nu protein and nearly half of the SIRT5 protein were shifted from P1 fraction to S fraction by co-expression (Figs. 1B and 4C). These results suggest that the segment containing amino acid residues 213–219 of SIRT3 plays an important role in the localization shift of SIRT3 protein to nucleus when co-expressed with SIRT5. Furthermore, SIRT5 may well hamper SIRT3nu localization in mitochondria through interaction with SIRT3nu. However, further study is required to elucidate the mechanism of the localization shift of SIRT3 protein. Interestingly, recent study has reported that human prohibitin 2 (PHB2), known as a repressor of estrogen receptor (ER) activity, is localized in the mitochondrial inner membrane, and translocates to the nucleus in the presence of ER and estradiol [18]. Although the mechanism of regulation of the expression level of SIRT5 remains unknown, SIRT3 might play a role in communication between nucleus and mitochondria in a SIRT5-dependent manner. The function of mitochondrial SIRT proteins is still not well known. In the present study, we determined the exact localization of mouse SIRT3, SIRT4, and SIRT5 proteins in mitochondria. In addition, we demonstrated that SIRT3 can be present in nucleus in the presence of SIRT5. It has been reported that SIRT3 deacetylates proteins that are not localized in mitochondria in vitro such as histone-4 peptide and tubulin [14]. Thus, if SIRT3 is present in nucleus in vivo, SIRT3 protein might well deacetylate nuclear proteins. These results provide useful information for the investigation of the function of these proteins.

References

[1] J.C. Tanny, G.J. Dowd, J. Huang, H. Hilz, D. Moazed, An enzymatic activity in the yeast Sir2 protein that is essential for gene silencing, Cell 99 (1999) 735–745.
[2] S. Imai, C.M. Armstrong, M. Kaeberlein, L. Guarente, Transcriptional silencing and longevity protein Sir2 is an NAD-dependent histone deacetylase, Nature 403 (2000) 795–800.
[3] M. Gotta, S. Strahl-Bolsinger, H. Renauld, T. Laroche, B.K. Kennedy, M. Grunstein, S.M. Gasser, Localization of Sir2p: the nucleolus as a compartment for silent information regulators, EMBO J. 16 (1997) 3243–3255.
[4] I. Muller, M. Zimmermann, D. Becker, M. Flomer, Calendar life span versus budding life span of Saccharomyces cerevisiae, Mech. Aging Dev. 12 (1980) 47–52.
[5] S.J. Lin, M. Kaeberlein, A.A. Andalis, L.A. Sturtz, P.A. Defossez, V.C. Culotta, G.R. Fink, L. Guarente, Calorie restriction extends Saccharomyces cerevisiae lifespan by increasing respiration, Nature 418 (2002) 344–348.
[6] S.J. Lin, P.A. Defossez, L. Guarente, Requirement of NAD and SIR2 for life-span extension by calorie restriction in Saccharomyces cerevisiae, Science 289 (2000) 2126–2128.

7.8.8 SIRT4 Has Tumor-Suppressive Activity and Regulates the Cellular Metabolic Response to DNA Damage by Inhibiting Mitochondrial Glutamine Metabolism

Jeong SM1Xiao CFinley LWLahusen TSouza ALPierce KLi YH, et al.
Cancer Cell. 2013 Apr 15; 23(4):450-63.
http://www.ncbi.nlm.nih.gov/pubmed/23562301#
http://dx.doi.org:/10.1016/j.ccr.2013.02.024

DNA damage elicits a cellular signaling response that initiates cell cycle arrest and DNA repair. Here we find that DNA damage triggers a critical block in glutamine metabolism, which is required for proper DNA damage responses. This block requires the mitochondrial SIRT4, which is induced by numerous genotoxic agents and represses the metabolism of glutamine into TCA cycle. SIRT4 loss leads to both increased glutamine-dependent proliferation and stress-induced genomic instability, resulting in tumorigenic phenotypes. Moreover, SIRT4 knockout mice spontaneously develop lung tumors. Our data uncover SIRT4 as an important component of the DNA damage response pathway that orchestrates a metabolic block in glutamine metabolism, cell cycle arrest and tumor suppression.

DNA damage initiates a tightly coordinated signaling response to maintain genomic integrity by promoting cell cycle arrest and DNA repair. Upon DNA damage, ataxia telangiectasia mutated (ATM) and ataxia telangiectasia and RAD3-related protein (ATR) are activated and induce phosphorylation of Chk1, Chk2 and γ-H2AX to trigger cell cycle arrest and to initiate assembly of DNA damage repair machinery (Abraham, 2001Ciccia and Elledge, 2010Su, 2006). Cell cycle arrest is a critical outcome of the DNA damage response (DDR) and defects in the DDR often lead to increased incorporation of mutations into newly synthesized DNA, the accumulation of chromosomal instability and tumor development (Abbas and Dutta, 2009Deng, 2006Negrini et al., 2010).

The cellular metabolic response to DNA damage is not well elucidated. Recently, it has been shown that DNA damage causes cells to upregulate the pentose phosphate pathway (PPP) to generate nucleotide precursors needed for DNA repair (Cosentino et al., 2011). Intriguingly, a related metabolic switch to increase anabolic glucose metabolism has been observed for tumor cells and is an important component of rapid generation of biomass for cell growth and proliferation (Jones and Thompson, 2009Koppenol et al., 2011). Hence, cells exposed to genotoxic stress face a metabolic challenge; they must be able to upregulate nucleotide biosynthesis to facilitate DNA repair, while at the same time limiting proliferation and inducing cell cycle arrest to limit the accumulation of damaged DNA. The molecular events that regulate this specific metabolic program in response to DNA damage are still unclear.

Sirtuins are a highly conserved family of NAD+-dependent deacetylases, deacylases, and ADP-ribosyltransferases that play various roles in metabolism, stress response and longevity (Finkel et al., 2009;Haigis and Guarente, 2006). In this study, we studied the role of SIRT4, a mitochondria-localized sirtuin, in cellular metabolic response to DNA damage and tumorigenesis.

DNA damage represses glutamine metabolism

To investigate how cells might balance needs for continued nucleotide synthesis, while also preparing for cell cycle arrest, we assessed the metabolic response to DNA damage by monitoring changes in the cellular consumption of two important fuels, glucose and glutamine, after DNA-damage. Strikingly, treatment of primary mouse embryonic fibroblasts (MEFs) with camptothecin (CPT), a topoisomerase 1 inhibitor that causes double-stranded DNA breaks (DSBs), resulted in a pronounced reduction in glutamine consumption (Figure 1A). Glutamine metabolism in mammalian cells is complex and contributes to a number of metabolic pathways. Glutamine is the primary nitrogen donor for protein and nucleotide synthesis, which are essential for cell proliferation (Wise and Thompson, 2010). Additionally, glutamine provides mitochondrial anaplerosis. Glutamine can be metabolized via glutaminase (GLS) to glutamate and NH4+, and further converted to the tricarboxylic acid (TCA) cycle intermediate α-ketoglutarate via glutamate dehydrogenase (GDH) or aminotransferases. This metabolism of glutamine provides an important entry point of carbon to fuel the TCA cycle (Jones and Thompson, 2009), and accounts for the majority of ammonia production in cells (Yang et al., 2009). CPT-induced reduction of glutamine consumption was accompanied by a reduction in ammonia secretion from cells (Figure 1B). Notably, under these conditions, we observed no obvious decrease in glucose uptake and lactate production (Figures 1C and 1D), consistent with previous studies showing that intact glucose utilization through the PPP is important for a normal DNA damage response (Cosentino et al., 2011). Preservation of glucose uptake also suggests that repression of glutamine consumption may be a specific metabolic response to genotoxic stress and not reflective of a non-specific metabolic crisis.

Figure 1 Glutamine metabolism is repressed by genotoxic stress

To examine the metabolic response to other forms of genotoxic stress, we monitored the metabolic response to ultra-violet (UV) exposure in primary MEFs. Similar to CPT treatment, UV exposure reduced glutamine uptake, without significant changes in glucose consumption (Figures 1E and 1F). Similarly two human cell lines, HepG2 and HEK293T, also demonstrated marked reductions in glutamine uptake in response to DNA damaging agents without comparable changes in glucose uptake (Figures 1G and 1HFigures S1A and S1B). Taken together, these results suggest that a variety of primary and tumor cell lines (from mouse or human) respond to genotoxic stress by down-regulating glutamine metabolism.

To examine in more detail the changes in cellular glutamine metabolism after genotoxic stress, we performed a global metabolomic analysis with transformed MEFs before and after DNA damage. As previously reported, we observed that PPP intermediates were increased in response to DNA damage (Figures 1I and 1J). Remarkably, we observed a decrease in measured TCA cycle intermediates after UV exposure (Figures 1I and 1K). Moreover, we found that HepG2 cells showed a similar metabolomic shift in response to DNA damage (Figure S1D). We did not observe a clear, coordinated repression of nucleotides or glutamine-derived amino acids after exposure to DNA damage (Figure S1C).

To determine whether reduction in TCA cycle metabolites was the consequence of reduced glutamine metabolism, we performed a time-course tracer study to monitor the incorporation of [U-13C5]glutamine into TCA cycle intermediates at 0, 2 and 4 hr after UV treatment. We observed that after UV exposure, cells reduced contribution of glutamine to TCA cycle intermediates in a time-dependent manner (Figure 1L). Moreover, the vast majority of the labeled fumarate and malate contained four carbon atoms derived from [U-13 C5]glutamine (Figure S1F, M+3 versus M+4), indicating that most glutamine was used in the non-reductive direction towards succinate, fumarate and malate production. We were able to observe little contribution of glutamine flux into nucleotides or glutathione in control or UV-treated cells at these time points (data not shown), suggesting that the mitochondrial metabolism of glutamine accounts for the majority of glutamine consumption in these cells. Taken together, the metabolic flux analysis demonstrates that DNA damage results in a reduction of mitochondrial glutamine anaplerosis, thus limiting the critical refueling of carbons into the TCA cycle.

To assess the functional relevance of decreased glutamine metabolism after DNA damage, we deprived cells of glucose, thereby shifting cellular dependence to glutamine to maintain viability (Choo et al., 2011Dang, 2010). If DNA damage represses glutamine usage, we reasoned that cells would be more sensitive to glucose deprivation. Indeed, following 72 hr of glucose deprivation, cell death in primary MEFs was significantly elevated at 10 hr after UV exposure (Figure S1E). However, cells cultured with glucose remained viable in these conditions. Thus, these data demonstrate that genotoxic stress limits glutamine entry into the central mitochondrial metabolism of the TCA cycle.

SIRT4 is induced in response to genotoxic stress

Because sirtuins regulate both cellular metabolism and stress responses (Finkel et al., 2009Schwer and Verdin, 2008), we examined whether sirtuins were involved in the metabolic adaptation to DNA damage. We first examined the expression of sirtuins in the response to DNA damage. Specifically, we probed SIRT1, which is involved in stress responses (Haigis and Guarente, 2006), as well as mitochondrial sirtuins (SIRT3–5), which have been shown to regulate amino acid metabolism (Haigis et al., 2006Hallows et al., 2011Nakagawa et al., 2009). Remarkably, SIRT4 mRNA levels were induced by nearly 15-fold at 15 hr after CPT treatment and 5-fold after etoposide (ETS), a topoisomerase 2 inhibitor, in HEK293T cells (Figure 2A). Interestingly, the induction of SIRT4 was significantly higher than the induction of SIRT1 and mitochondrial SIRT3 (~2-fold), sirtuins known to be induced by DNA damage and regulate cellular responses to DNA damage (Sundaresan et al., 2008Vaziri et al., 2001Wang et al., 2006). Moreover, overall mitochondrial mass was increased by only 10% in comparison with control cells (Figure S2A), indicating that the induction of SIRT4 is not an indirect consequence of mitochondrial biogenesis. These data hint that SIRT4 may have an important, previously undetermined role in the DDR.

Figure 2 SIRT4 is induced by DNA damage stimuli

To test the induction of SIRT4 in the general genotoxic stress response, we treated cells with other types of DNA damage, including UV and gamma-irradiation (IR). SIRT4 mRNA levels were also increased by these genotoxic agents (Figures S2B and S2C) and low doses of CPT and UV treatment also induced SIRT4expression (Figures S2D and S2E). We observed similar results with MEFs (Figures 2B and 2DFigure S2F) and HepG2 cells (Figure S2G). DNA damaging agents elevated SIRT4 in p53-inactive HEK293T cells (Figures 2A and 2C) and in p53-null PC3 human prostate cancer cells (Figure S2H), suggesting that SIRT4can be induced in a p53-independent manner.

To examine whether the induction of SIRT4 occurred as a result of cell cycle arrest, we measured SIRT4levels after the treatment of nocodazole, which inhibits microtubule polymerization to block mitosis. While treatment with nocodazole completely inhibited cell proliferation (data not shown), SIRT4 expression was not elevated (Figure S2I). In addition, we analyzed SIRT4 expression in distinct stages of the cell cycle in HepG2 cells synchronized with thymidine block (Figure S2J, Left). SIRT4 mRNA levels were measured at different times after release and were not elevated during G1 or G2/M phases (Figure S2J, Right), suggesting thatSIRT4 is not induced as a general consequence of cell cycle arrest. Next, we re-examined the localization of SIRT4 after DNA damage. SIRT4 localizes to the mitochondria of human and mouse cells under basal, unstressed conditions (Ahuja et al., 2007Haigis et al., 2006). Following CPT treatment, SIRT4 colocalized with MitoTracker, a mitochondrial-selective marker, indicating that SIRT4 retains its mitochondrial localization after exposure to DNA damage (Figure S2K). Taken together, our findings demonstrate that SIRT4 is induced by multiple forms of DNA damage in numerous cell types, perhaps to coordinate the mitochondrial response to genotoxic stress.

SIRT4 represses glutamine anaplerosis

We observed that glutamine anaplerosis is repressed by genotoxic stress (Figure 1) and SIRT4 is induced by DNA damage (Figure 2). Additionally, previous studies reported that SIRT4 represses glutamine anaplerosis (Haigis et al., 2006). We next tested whether SIRT4 directly regulates cellular glutamine metabolism and contribution of glutamine to the TCA cycle. Like DNA damage, SIRT4 overexpression (SIRT4-OE) in HepG2, HeLa or HEK293T cells resulted in the repression of glutamine consumption (Figure 3AFigures S3A–C). Conversely, SIRT4 knockout (KO) MEFs consumed more glutamine than did wild-type (WT) cells (Figure 3B).

Figure 3 SIRT4 represses mitochondrial glutamine metabolism in response to DNA damage

Mitochondrial glutamine catabolism refuels the TCA cycle and is essential for viability in the absence of glucose (Choo et al., 2011Yang et al., 2009). Thus, we examined the effect of SIRT4 on cell survival during glucose deprivation. Overexpression of SIRT4 in HEK293T or HeLa cells increased cell death in glucose-free media compared to control cells (Figure 3CFigure S3D). Importantly, this cell death was completely rescued by the addition of pyruvate or cell permeable dimethyl α-ketoglutarate (DM-KG), demonstrating that SIRT4 overexpression reduced the ability of cells to utilize glutamine for mitochondrial energy production. Moreover, cell death was equally maximized in the absence of glucose and presence of the mitochondrial ATPase inhibitor oligomycin (Figure 3C). These findings are in line with the model that SIRT4 induction with DNA damage limits glutamine metabolism and utilization by the TCA cycle

We next utilized a metabolomic approach to interrogate glutamine usage in the absence of SIRT4. SIRT4 KO MEFs demonstrated elevated levels of TCA cycle intermediates (Figure 3J, WT versus KO), whereas intermediates of glycolysis were comparable with WT cells (data not shown). Nucleotides and other metabolites downstream of glutamine metabolism were not coordinately regulated by SIRT4 loss (Figure S3E and data not shown). Next, we analyzed glutamine flux in WT and SIRT4 KO MEFs in medium containing [U-13C5]glutamine for 2 or 4 hours and measured isotopic enrichment of TCA cycle intermediates. Loss of SIRT4 promoted a higher rate of incorporation of 13C-labeled metabolites derived from [U-13C5]glutamine in all TCA cycle intermediates measured (Figure 3D). These data provide direct evidence that SIRT4 loss drives increased entry of glutamine-derived carbon into the TCA cycle.

Next, we examined the mechanisms involved in this repression of glutamine anaplerosis. GLS is the first required enzyme for mitochondrial glutamine metabolism (Curthoys and Watford, 1995) and its inhibition limits glutamine flux into the TCA cycle (Wang et al., 2010; Le et al., 2012; Yuneva et al., 2012). Treatment with bis-2-(5-phenylacetoamido-1,2,4-thiadiazol-2-yl)ethyl sulfide (BPTES) (Robinson et al., 2007), an inhibitor of GLS1, repressed glutamine uptake and completely rescued the increased glutamine consumption of SIRT4 KO cells (Figure 3E). Moreover, SIRT4 overexpression no longer inhibited glutamine uptake when GLS1 was reduced by using short hairpin RNAs (shRNAs) (Figures 3F and 3G), demonstrating that SIRT4 regulates mitochondrial glutamine metabolism. SIRT4 is a negative regulator of GDH activity (Haigis et al., 2006) and SIRT4 KO MEFs exhibited increased GDH activity in comparison with WT MEFs (Figure S3F). To test whether SIRT4 regulates mitochondrial glutamine metabolism via inhibiting GDH activity, we measured glutamine uptake in WT and SIRT4 KO cells in the presence of EGCG, a GDH inhibitor (Choo et al., 2011Li et al., 2006). The treatment of EGCG partially rescued the increased glutamine uptake of KO cells (Figure S3G), suggesting that GDH contributes to the role of SIRT4 in glutamine metabolism.

SIRT4 represses mitochondrial glutamine metabolism after DNA damage

SIRT4 regulates cell cycle progression and genomic fidelity in response to DNA damage

Figure 4 SIRT4 is involved in cellular DNA damage responses

SIRT4 represses tumor proliferation

Figure 5 SIRT4 has tumor suppressive function

(A and B) Growth curves of WT and SIRT4 KO MEFs (n = 3) cultured in standard media (A) or media supplemented with BPTES (10 μM) (B). Data are means ±SD.

(C and D) Growth curves of Vector and SIRT4-OE HeLa cells (n = 3) cultured in standard media (C) or media supplemented with BPTES (10 μM) (D). Data are means ±SD.

(E) Focus formation assays with transformed WT and SIRT4 KO MEFs (left). Cells were cultured with normal medium or medium without glucose or glutamine for 10 days and stained with crystal violet. The number of colonies was counted (right) (n =3 samples of each condition). n.d., not determined.

(F) Focus formation assays with transformed KO MEFs reconstituted with SIRT4 or a catalytic mutant of SIRT4 (n = 3). Cells were cultured for 8 days and stained with crystal violet.

(G) Contact inhibited cell growth of transformed WT and SIRT4 KO MEFs cultured in the presence of DMSO or BPTES (10 μM) for 14 days (left). The number of colonies was counted (right). Data are means ±SEM. n.s., not significant. *p < 0.05, **p < 0.005. See also Figure S5.

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SIRT4 represses tumor formation in vivo

To investigate SIRT4 function in human cancers, we examined changes in SIRT4 expression. SIRT4 mRNA level was reduced in several human cancers, such as small cell lung carcinoma (Garber et al., 2001), gastric cancer (Wang et al., 2012), bladder carcinoma (Blaveri et al., 2005), breast cancer (TCGA) and leukemia (Choi et al., 2007) (Figure 6A). Of note, lower SIRT4 expression associated with shorter time to death in lung tumor patients (Shedden et al., 2008) (Figure 6B). Overall the expression data is consistent with the model that SIRT4 may play a tumor suppressive role in human cancers.

Figure 6 SIRT4 is a mitochondrial tumor suppressor

SIRT4 regulates glutamine metabolism in lung tissue

To test further the biological relevance of this pathway in lung, we examined whether SIRT4 is induced in vivo after exposure to DNA damaging IR treatment. Remarkably, Sirt4 was significantly induced in lung tissue after IR exposure (Figure 7A). We next examined whether IR repressed glutamine metabolism in vivo, as observed in cell culture by examining GDH activity in lung tissue from WT and SIRT4 KO mice with or without IR exposure. GDH activity was elevated in lung tissue extracts from SIRT4 KO mice compared with WT lung tissue (Figure 7B). Importantly, GDH activity was significantly decreased in lung tissue from WT mice after IR exposure, whereas not in lung tissue from KO mice (Figure 7C). Thus, these findings recapitulate our cellular studies and are in line with the model that SIRT4 induction with DNA damage limits mitochondrial glutamine metabolism and utilization.

SIRT4 inhibits mitochondria glutamine metabolism in vivo

SIRT4 inhibits mitochondria glutamine metabolism in vivo

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Figure 7 SIRT4 inhibits mitochondria glutamine metabolism in vivo

To assess whether the functions of SIRT4 can be reproduced in these lung tumors, cells derived from SIRT4 KO lung tumors were reconstituted with wild type SIRT4 (Figure S7A). As expected, SIRT4 reconstitution reduced glutamine uptake, but not glucose uptake (Figures 7D and 7E) and repressed proliferation (Figure S7B) of lung tumor cells.

Here, we report that SIRT4 has an important role in cellular metabolic response to DNA damage by regulating mitochondrial glutamine metabolism with important implication for the DDR and tumorigenesis. First, we discovered that DNA damage represses cellular glutamine metabolism (Figure 1). Next, we found that SIRT4 is induced by genotoxic stress (Figure 2) and is required for the repression of mitochondrial glutamine metabolism (Figure 3). This metabolic response contributes to the control of cell cycle progression and the maintenance of genomic integrity in response to DNA damage (Figure 4). Loss of SIRT4 increased glutamine-dependent tumor cell proliferation and tumorigenesis (Figure 5). In mice, SIRT4 loss resulted in spontaneous tumor development (Figure 6). We demonstrate that SIRT4 is induced in normal lung tissue in response to DNA damage where it represses GDH activity. Finally, the glutamine metabolism-genomic fidelity axis is recapitulated in lung tumor cells derived from SIRT4 KO mice via SIRT4 reconstitution (Figure 7). Our studies therefore uncover SIRT4 as a important regulator of cellular metabolic response to DNA damage that coordinates repression of glutamine metabolism, genomic stability and tumor suppression.

The DDR is a highly orchestrated and well-studied signaling response that detects and repairs DNA damage. Upon sensing DNA damage, the ATM/ATR protein kinases are activated to phosphorylate target proteins, leading to cell cycle arrest, DNA repair, transcriptional regulation and initiation of apoptosis (Ciccia and Elledge, 2010Su, 2006). Dysregulation of this pathway is frequently observed in many tumors. Emerging evidence has suggested that cell metabolism also plays key roles downstream of the DDR-induced pathways.

 

7.8.9 Mitochondrial sirtuins and metabolic homeostasis

Pirinen E1Lo Sasso GAuwerx J.
Best Pract Res Clin Endocrinol Metab. 2012 Dec; 26(6):759-70. http://dx.doi.org:/10.1016/j.beem.2012.05.001

The maintenance of metabolic homeostasis requires the well-orchestrated network of several pathways of glucose, lipid and amino acid metabolism. Mitochondria integrate these pathways and serve not only as the prime site of cellular energy harvesting but also as the producer of many key metabolic intermediates. The sirtuins are a family of NAD+-dependent enzymes, which have a crucial role in the cellular adaptation to metabolic stress. The mitochondrial sirtuins SIRT3, SIRT4 and SIRT5 together with the nuclear SIRT1 regulate several aspects of mitochondrial physiology by controlling posttranslational modifications of mitochondrial protein and transcription of mitochondrial genes. Here we discuss current knowledge how mitochondrial sirtuins and SIRT1 govern mitochondrial processes involved in different metabolic pathways.

Mitochondria are organelles composed of a matrix enclosed by a double (inner and outer) membrane (1). Major cellular functions, such as nutrient oxidation, nitrogen metabolism, and especially ATP production, take place in the mitochondria. ATP production occurs in a process referred to as oxidative phosphorylation (OXPHOS), which involves electron transport through a chain of protein complexes (I-IV), located in the inner mitochondrial membrane. These complexes carry electrons from electron donors (e.g. NADH) to electron acceptors (e.g. oxygen), generating a chemiosmotic gradient between the mitochondrial intermembrane space and matrix. The energy stored in this gradient is then used by ATP synthase to produce ATP (1). One well-known side effect of the OXPHOS process is the production of reactive oxygen species (ROS) that can generate oxidative damage in biological macromolecules (1). However, to neutralize the harmful effects of ROS, cells have several antioxidant enzymes, including superoxide dismutase, catalase, and peroxidases (1). The sirtuin silent information regulator 2 (Sir2), the founding member of the sirtuin protein family, was identified in 1984 (2). Sir2 was subsequently characterized as important in yeast replicative aging (3) and shown to posses NAD+-dependent histone deacetylase activity (4), suggesting it could play a role as an energy sensor. A family of conserved Sir2-related proteins was subsequently identified. Given their involvement in basic cellular processes and their potential contribution to the pathogenesis of several diseases (5), the sirtuins became a widely studied protein family.

In mammals the sirtuin family consists of seven proteins (SIRT1-SIRT7), which show different functions, structure, and localization. SIRT1 is mostly localized in the nucleus but, under specific physiological conditions, it shuttles to the cytosol (6). Similar to SIRT1, also SIRT6 (7) and SIRT7 (8) are localized in the nucleus. On the contrary, SIRT2 is mainly present in the cytosol and shuttles into the nucleus during G2/M cell cycle transition (9). Finally, SIRT3, SIRT4, and SIRT5, are mitochondrial proteins (10).

The main enzymatic activity catalyzed by the sirtuins is NAD+-dependent deacetylation, as known for the progenitor Sir2 (4,11). Along with histones also many transcription factors and enzymes were identified as targets for deacetylation by the sirtuins. Remarkably, mammalian sirtuins show additional interesting enzymatic activities. SIRT4 has an important ADP-ribosyltransferase activity (12), while SIRT6 can both deacetylate and ADP-ribosylate proteins (13,14). Moreover, SIRT5 was recently shown to demalonylate and desuccinylate proteins (15,16), in particular the urea cycle enzyme carbamoyl phosphate synthetase 1 (CPS1) (16). The (patho-)physiological context in which the seven mammalian sirtuins exert their functions, as well as their biochemical characteristics, are extensively discussed in the literature (17,18) and will not be addressed in this review; here we will focus on the emerging roles of the mitochondrial sirtuins, and their involvement in metabolism. Moreover, SIRT1 will be discussed as an important enzyme that indirectly affects mitochondrial physiology.

Sirtuins are regulated at different levels. Their subcellular localization, but also transcriptional regulation, post-translational modifications, and substrate availability, all impact on sirtuin activity. Moreover, nutrients and other molecules could affect directly or indirectly sirtuin activity. As sirtuins are NAD+-dependent enzymes, the availability of NAD+ is perhaps one of the most important mechanisms to regulate their activity. Changes in NAD+ levels occur as the result of modification in both its synthesis or consumption (19). Increase in NAD+ amounts during metabolic stress, as prolonged fasting or caloric restriction (CR) (2022), is well documented and tightly connected with sirtuin activation (4,19). Furthermore, the depletion and or inhibition of poly-ADP-ribose polymerase (PARP) 1 (23) or cADP-ribose synthase 38 (24), two NAD+consuming enzymes, increase SIRT1 action.

Analysis of the SIRT1 promoter region identified several transcription factors involved in up- or down-regulation of SIRT1 expression. FOXO1 (25), peroxisome proliferator-activated receptors (PPAR) α/β (26,27), and cAMP response element-binding (28) induce SIRT1 transcription, while PPARγ (29), hypermethylated in cancer 1 (30), PARP2 (31), and carbohydrate response element-binding protein (28) repress SIRT1 transcription. Of note, SIRT1 is also under the negative control of miRNAs, like miR34a (32) and miR199a (33). Furthermore, the SIRT1 protein contains several phosphorylation sites that are targeted by several kinases (34,35), which may tag the SIRT1 protein so that it only exerts activity towards specific targets (36,37). The beneficial effects driven by the SIRT1 activation – discussed below- led the development of small molecules modulators of SIRT1. Of note, resveratrol, a natural plant polyphenol, was shown to increase SIRT1 activity (38), most likely indirectly (22,39,40), inducing lifespan in a range of species ranging from yeast (38) to high-fat diet fed mice (41). The beneficial effect of SIRT1 activation by resveratrol on lifespan, may involve enhanced mitochondrial function and metabolic control documented both in mice (42) and humans (43). Subsequently, several powerful synthetic SIRT1 agonists have been identified (e.g. SRT1720 (44)), which, analogously to resveratrol, improve mitochondrial function and metabolic diseases (45). The precise mechanism of action of these compounds is still under debate; in fact, it may well be that part of their action is mediated by AMP-activated protein kinase (AMPK) activation (21,22,46), as resveratrol was shown to inhibit ATP synthesis by directly inhibiting ATP synthase in the mitochondrial respiratory chain (47), leading to an energy stress with subsequent activation of AMPK. However, at least in β-cells, resveratrol-mediated SIRT1 activation and AMPK activation seem to regulate glucose response in the opposite direction, pointing to the existence of alternative molecular targets (48).

Another hypothesis to explain the pleitropic effects of resveratrol suggests it inhibits cAMP-degrading phosphodiesterase 4 (PDE4), resulting in the cAMP-dependent activation of exchange proteins activated by cyclic AMP (Epac1) (40). The consequent Epac1-mediated increase of intracellular Ca2+ levels may then activate of CamKKβ-AMPK pathway (40), which ultimately will result in an increase in NAD+ levels and SIRT1 activation (21). Interestingly, also PDE4 inhibitors reproduce some of the metabolic benefits of resveratrol representing yet another putative way to activate SIRT1.

The regulation of the activity of the mitochondrial sirtuins is at present poorly understood. SIRT3 expression is induced in white adipose (WAT) and brown adipose tissues upon CR (49), while it is down-regulated in the liver of high-fat fed mice (50). SIRT3 activity changes also in the muscle after fasting (51) and chronic contraction (52). All these processes are associated with increase (20,53) or decrease (50) in NAD+ levels. From a transcriptional point of view, SIRT3 gene expression in brown adipocytes seems under the control of peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) -estrogen-related receptor α (ERRα) axis, and this effect is crucial for full brown adipocyte differentiation (54,55). SIRT4 expression is reported to be reduced during CR (12), while the impact of resveratrol on SIRT4 is still under debate (56). Finally, upon ethanol exposure, SIRT5 gene expression was shown to be decreased together with the NAD+levels (57), probably explaining the protein hyperacetylation caused by alcohol exposure (58).

Metabolic homeostasis

The maintenance of metabolic homeostasis is critical for the survival of all species to sustain body structure and function. Metabolic homeostasis is achieved through complicated interactions between metabolic pathways that govern glucose, lipid and amino acid metabolism. Mitochondria are organelles, which integrate these metabolic pathways by serving a physical site for the production and recycling of metabolic intermediates.

Glucose metabolism

Overview

Glucose homeostasis is regulated through various complex processes including hepatic glucose output, glucose uptake, glucose utilization and storage. The main hormones regulating glucose homeostasis are insulin and glucagon, and the balance between these hormones determines glucose homeostasis. Insulin promotes glucose uptake in peripheral tissues (muscle and WAT), glycolysis and storage of glucose as glycogen in the fed state, while glucagon stimulates hepatic glucose production during fasting. Sirtuins influence many aspects of glucose homeostasis in several tissues such as muscle, WAT, liver and pancreas.

Gluconeogenesis

The body’s ability to synthesise glucose is vital in order to provide an uninterrupted supply of glucose to the brain and survive during starvation. Gluconeogenesis is a cytosolic process, in which glucose is formed from non-carbohydrate sources, such as amino acids, lactate, the glycerol portion of fats and tricarboxylic acid (59) cycle intermediates, during energy demand. This process, which occurs mainly in liver and kidney, shares some enzymes with glycolysis but it employs phosphoenolpyruvate carboxykinase, fructose-1,6-bisphosphatase and glucose-6-phosphatase to control the flow of metabolites towards glucose production. These three enzymes are stimulated by glucagon, epinephrine and glucocorticoids, whereas their activity is suppressed by insulin.

The role of mitochondrial sirtuins in the control of gluconeogenesis is not well established. SIRT3 is suggested to induce fasting-dependent hepatic glucose production from amino acids by deacetylating and activating the mitochondrial conversion of glutamate into the TCA cycle intermediate α-ketoglutarate, via the enzyme glutamate dehydrogenase (GDH) (Fig. 1A) (60,61). As SIRT3−/− mice do not display changes in GDH activity (62), the mechanism requires further clarification. In contrast to SIRT3, SIRT4 inhibits GDH via ADP-ribosylation under basal dietary conditions (Fig. 1A-B) (12). Conversely, SIRT4 activity is suppressed during CR resulting in activation of GDH, which fuels the TCA cycle and possibly also gluconeogenesis (12). Therefore, mitochondrial sirtuins may function to support gluconeogenesis during energy limitation, but further research is required to understand the exact roles of mitochondrial sirtuins in gluconeogenesis.

Summary of mitochondrial sirtuins’ role in mitochondrial pathways

Summary of mitochondrial sirtuins’ role in mitochondrial pathways

Figure 1 Summary of mitochondrial sirtuins’ role in mitochondrial pathways

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Glucose utilization

 Lipid metabolism

Urea metabolism

The recent discoveries in the biology of mitochondria have shed light on the metabolic regulatory roles of the sirtuin family. To maintain proper metabolic homeostasis, sirtuins sense cellular NAD+ levels, which reflect the nutritional status of the cells, and translate this information to adapt the activity of mitochondrial processes via posttranslational modifications and transcriptional regulation. SIRT1 and SIRT3 function to stimulate proper energy production via FAO and SIRT3 also protects from oxidative stress and ammonia accumulation during nutrient deprivation. SIRT4 seems to play role in the regulation of gluconeogenesis, insulin secretion and fatty acid utilization during times of energy limitation, while SIRT5 detoxifies excess ammonia that can accumulate during fasting. However, we are only at the beginning of our understanding of the roles of the mitochondrial sirtuins, SIRT3, SIRT4 and SIRT5 in complex metabolic processes. In the coming years, further research should identify and verify novel sirtuin targets in vivo and in vitro. We need also to elucidate the regulation and tissue-specific functions of these mitochondrial sirtuins, as well as to understand the potential crosstalk and synchrony between the different sirtuins in different subcellular compartments. Ultimately, the understanding of mitochondrial sirtuin functions may open new possibilities, not only for treatment of cancer and metabolic diseases characterized by mitochondrial dysfunction, but also for disease prevention and health maintenance.

7.8.10 Mitochondrial sirtuins

Huang JY1Hirschey MDShimazu THo LVerdin E.
Biochim Biophys Acta. 2010 Aug; 1804(8):1645-51. http://dx.doi.org:/10.1016/j.bbapap.2009.12.021

Sirtuins have emerged as important proteins in aging, stress resistance and metabolic regulation. Three sirtuins, SIRT3, 4 and 5, are located within the mitochondrial matrix. SIRT3 and SIRT5 are NAD(+)-dependent deacetylases that remove acetyl groups from acetyllysine-modified proteins and yield 2′-O-acetyl-ADP-ribose and nicotinamide. SIRT4 can transfer the ADP-ribose group from NAD(+) onto acceptor proteins. Recent findings reveal that a large fraction of mitochondrial proteins are acetylated and that mitochondrial protein acetylation is modulated by nutritional status. This and the identification of targets for SIRT3, 4 and 5 support the model that mitochondrial sirtuins are metabolic sensors that modulate the activity of metabolic enzymes via protein deacetylation or mono-ADP-ribosylation. Here, we review and discuss recent progress in the study of mitochondrial sirtuins and their targets.

mitochondrial sirtuins

mitochondrial sirtuins

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mitochondrial sirtuins
Fig.1 .NAD+ -dependent deacetylation of sirtuins. The two step catalytic reaction mechanism. In this diagram ADPR = acetyl-ADP-ribose, NAM = nicotinamide, 1-O-AADPR = 1-O-acetyl ADP-ribose and βNAD = beta nicotinamide adenine dinucleotide.

Table 1 Shows subcellular localization, substrates and functions of different types of sirtuins.

Fig.2. Sirt3 regulated pathways in mitochondrial metabolism. Schematic diagram demonstrating the different roles of Sirt3 in the regulation of the main metabolic pathways of mitochondria.In this diagram LCAD = long-chain acyl-CoA dehydrogenase, ACeS2 = acetyl coenzyme synthetase 2, Mn SOD = manganese superoxide dismutase, CypD = cyclophilin D, ICDH2 = isocitrate dehydrogenase 2, OTC = ornithine transcarbomylase,TCA = tricaboxylic acid, ROS = reactive oxygen species, mPTP = membrane permeability transition pore, I–V = respiratory chain complex I–V

Fig. 3.(A) Schematic diagram showing different roles of Sirt4 in the regulation of various metabolic pathways. The diagram shows the Sirt4 regulated decrease in insulin level and the increase in availability of ATP inside mitochondria via upregulation of insulin degrading enzyme (IDE) and adenine translocator (ANT). The diagram also shows the Sirt4 regulated decrease in the efficiency of fatty acid oxidation and tricarboxylic acid cycle (TCA) via inhibition of glutamate dehydrogenase (GDH) and malonyl CoA decarboxylase (MCoAD). (B) Schematic diagram indicating the different roles of Sirt5 in regulation of various metabolic pathways. Sirt5 regulates urea production, fatty acid oxidation, tricarboxylic acid cycle (TCA), glycolysis, reactive oxygen species (ROS) metabolism, purine metabolism via regulating carbamoyl phosphate synthetase (CPS), hydroxyl-coenzyme A dehydrogenase (HADH), pyruvate dehydrogenase (PDH), pyruvate kinase (PK), succinate dehydrogenase(SDH) andurate oxidase (UO) respectively

Conclusion and future perspectives

Sirtuins are highly conserved NAD+-dependent protein deacetylases or ADP ribosyl transferases involved in many cellular processes including genome stability, cell survival, oxidative stress responses, metabolism, and aging. Mitochondrial sirtuins, Sirt3, Sirt4 and Sirt5 are important energy sensors and thus can be regarded as master regulators of mitochondrial metabolism. But it is still not known whether specific sirtuins can only function within particular metabolic pathways or two or more sirtuins could affect the same pathways. One of the mitochondrial sirtuins, Sirt3 is a major mitochondrial deacetylase that plays a pivotal role in the acetylation based regulation of numerous mitochondrial proteins. However, the question how mitochondrial proteins become acetylated is still unsolved and the identity of mitochondrial acetyltransferases is mysterious. Although the predominant function of the sirtuins is NAD+ dependent lysine deacetylation, but along with this major function another less characterized activity of these sirtuins includes ADP ribosylation which is mainly done by Sirt4. Moreover, in the case when the mitochondrial sirtuins exhibit both deacetylase and ADP ribosyl transferase activity, the conditions that determine the relative contribution of both of these activities in same or different metabolic pathways require further investigation. Sirt5 another mitochondrial sirtuin, was a puzzle until the recent finding as it possesses unique demalonylase and desuccinylase activities. However, most of the malonylated or succinylated proteins are important metabolic enzymes but as the significance of lysine malonylation and succinylation is still unknown thus it would be interesting to know how lysine malonylation and succinylation alter the functions of various metabolic enzymes. The mitochondrial sirtuins Sirt3, Sirt4 and Sirt5 serve as critical junctions and are required to exert many of the beneficial effect in mitochondrial metabolism. The emerging multidimensional role of mitochondrial sirtuins in regulation of mitochondrial metabolism and bioenergetics may have far-reaching consequences for many diseases associated with mitochondrial dysfunctions. However it is very important to fully elucidate the functions of mitochondrial sirtuins in different tissues to achieve the goal of therapeutic intervention in different metabolic diseases. Although several proteomic studies have provided detailed information that how mitochondrial sirtuin driven modification takes place on various targets in response to different environmental conditions, still the role of sirtuins in mitochondrial physiology and human diseases requires further exploration. Hopefully the progress in the field of sirtuin biology will soon provide insight into the therapeutic applications for targeting mitochondrial sirtuins by bioactive compounds to treat various human age-related diseases.

References

Ahn B.H.,et al.,2008. A role for the mitochondrial deacetylase Sirt3 in regulating energy homeostasis. Proc. Natl. Acad. Sci. U. S. A. 105 (38), 14447–14452. http://dx.doi.org/10.1073/pnas.0803790105.

Ahuja N.,et al., 2007. Regulation of insulin secretion by SIRT4, a mitochondrial ADP ribosyltransferase. J. Biol. Chem. 282 (46), 33583–33592. http://dx.doi.org/10.1074/jbc.M705488200.

Allison, S.J., Milner, J., 2007. SIRT3 is pro-apoptotic and participates in distinct basal apoptotic pathways. Cell Cycle 6, 2669–2677. http://dx.doi.org/10.4161/cc.6.21.4866.

Ashraf, N., et al., 2006. Altered sirtuin expression is associated with node-positive breast cancer. Br. J. Cancer 95, 1056–1061. http://dx.doi.org/10.1038/sj.bjc.6603384.

Bao, J.,et al.,2010. SIRT3 is regulated by nutrient excess and modulates hepatic susceptibility to lipotoxicity. Free Radic. Biol. Med. 49, 1230–1237.

Beal, M.F., 2005. Less stress, longer life. Nat. Med. 11 (6), 598–599. http://dx.doi.org/10.1038/nm0605-598.

Bell, E.L., Guarente,L., 2011. The SirT3 divining rod points to oxidative stress. Mol.Cell 42 (5), 561–568. http://dx.doi.org/10.1016/j.molcel.2011.05.008
(Review).

Bell,E.L., Emerling,B.M., Ricoult,S.J.H., Guarente,L., 2011. SirT3 suppresses hypoxia inducible factor 1α and tumor growth by inhibiting mitochondrial ROS production. Oncogene 30, 2986–2996. http://dx.doi.org/10.1038/onc.2011.37.

Bellizzi,D.,Rose,G.,Cavalcante,P.,Covello,G.,et al., 2005. A novel VNTR enhancer within the SIRT3 gene, a human homologue of SIR2, is associated with survival at oldest ages. Genomics 85, 258–263.
http://dx.doi.org/10.1016/j.ygeno.2004.11.003.

7.8.11 Sirtuin regulation of mitochondria: energy production, apoptosis, and signaling

Verdin E1Hirschey MDFinley LWHaigis MC.
Trends Biochem Sci. 2010 Dec; 35(12):669-75.
http://dx.doi.org:/10.1016/j.tibs.2010.07.003

Sirtuins are a highly conserved family of proteins whose activity can prolong the lifespan of model organisms such as yeast, worms and flies. Mammals contain seven sirtuins (SIRT1-7) that modulate distinct metabolic and stress response pathways. Three sirtuins, SIRT3, SIRT4 and SIRT5, are located in the mitochondria, dynamic organelles that function as the primary site of oxidative metabolism and play crucial roles in apoptosis and intracellular signaling. Recent findings have shed light on how the mitochondrial sirtuins function in the control of basic mitochondrial biology, including energy production, metabolism, apoptosis and intracellular signaling.

Mitochondria play critical roles in energy production, metabolism, apoptosis, and intracellular signaling [13]. These highly dynamic organelles have the ability to change their function, morphology and number in response to physiological conditions and stressors such as diet, exercise, temperature, and hormones [4]. Proper mitochondrial function is crucial for maintenance of metabolic homeostasis and activation of appropriate stress responses. Not surprisingly, changes in mitochondrial number and activity are implicated in aging and age-related diseases, including diabetes, neurodegenerative diseases, and cancer [1]. Despite the important link between mitochondrial dysfunction and human diseases, in most cases, the molecular causes for dysfunction have not been identified and remain poorly understood.

One of the principal bioenergetic functions of mitochondria is to generate ATP through the process of oxidative phosphorylation (OXPHOS), which occurs in the inner-mitochondrial membrane. Mitochondria are unique bi-membrane organelles that contain their own circular genome (mtDNA) encoding 13 protein subunits involved in electron transport. The remainder of the estimated 1000-1500 mitochondrial proteins are encoded by the nuclear genome and imported into mitochondria from the cytoplasm [56]. These imported proteins can be found either in the matrix, associated with inner or outer mitochondrial membranes or in the inner membrane space (Figure 1). Dozens of nuclear-encoded protein subunits form complexes with the mtDNA-encoded subunits to form electron transport complexes I-IV and ATP synthase, again highlighting the need for precise coordination between these two genomes. The transcriptional coactivator PGC-1α, a master regulator of mitochondrial biogenesis and function, is responsive to a variety of metabolic stresses, ensuring that the number and capacity of mitochondria keeps pace with the energetic demands of tissues [7].

Network of mitochondrial sirtuins

Network of mitochondrial sirtuins

http://www.ncbi.nlm.nih.gov/pmc/articles/instance/2992946/bin/nihms239607f1.gif

Network of mitochondrial sirtuins. Mitochondria can metabolize fuels, such as fatty acids, amino acids, and pyruvate, derived from glucose. Electrons pass through electron transport complexes (I-IV; red) generating a proton gradient, which is used to drive ATP synthase (AS; red) to generate ATP. SIRT3 (gold) binds complexes I and II, regulating cellular energy levels in the cell [4355]. Moreover, SIRT3 binds and deacetylates acetyl-CoA synthetase 2 (AceCS2) [3940] and glutamate dehydrogenase (GDH) [3347], thereby activating their enzymatic activities. SIRT3 also binds and activates long-chain acyl-CoA dehydrogenase (LCAD) [46]. SIRT4 (light purple) binds and represses GDH activity via ADP-ribosylation [21]. In the rate-limiting step of the urea cycle, SIRT5 (light blue) deacetylates and activates carbamoyl phosphate synthetase 1 (CPS1) [4849].

As high-energy electrons derived from glucose, amino acids or fatty acids fuels are passed through a series of protein complexes (I-IV), their energy is used to pump protons from the mitochondrial matrix through the inner membrane into the inner-membrane space, generating a proton gradient known as the mitochondrial membrane potential (Dψm) (Figure 1). Ultimately, the electrons reduce oxygen to form water, and the protons flow down their gradient through ATP synthase, driving the formation of ATP from ADP. Protons can also flow through uncoupling proteins (UCPs), dissipating their potential energy as heat. Reactive oxygen species (ROS) are a normal side-product of the respiration process [18]. In addition, an increase in Dψm, whether caused by impaired OXPHOS or by an overabundance of nutrients relative to ADP, will result in aberrant electron migration in the electron transport chain and elevated ROS production [1]. ROS react with lipids, protein and DNA, generating oxidative damage. Consequently, cells have evolved robust mechanisms to guard against an increase in oxidative stress accompanying ROS production [9].

Mitochondria are the primary site of ROS production within the cell, and increased oxidative stress is proposed to be one of the causes of mammalian aging [1210]. Major mitochondrial age-related changes are observed in multiple tissues and include decreased Dψm, increased ROS production and an increase in oxidative damage to mtDNA, proteins, and lipids [1114]. As a result, mitochondrial bioenergetic changes that occur with aging have been extensively reviewed [1517].

Silent information regulator (SIR) 2 protein and its orthologs in other species, termed sirtuins, promote an increased lifespan in model organisms such as yeast, worms and flies. Mammals contain seven sirtuins (SIRT1–7) that are characterized by an evolutionary conserved sirtuin core domain [1819]. This domain contains the catalytic activity and invariant amino acid residues involved in binding NAD+, a metabolic co-substrate. All sirtuins exhibit two major enzymatic activities in vitro: NAD+-dependent protein deacetylase activity and ADP-ribosyltransferase activity. Except for SIRT4, well-defined acetylated substrates have been identified for the other sirtuins. So far, only ADP-ribosyltransferase activity has been described for SIRT4 [2021]. Thus, these enzymes couple their biochemical and biological functions to an organism’s energetic state via their dependency on NAD+. A decade of research, largely focused on SIRT1, has revealed that mammalian sirtuins regulate metabolism and cellular survival. In brief, SIRT1–7 target distinct acetylated protein substrates and are localized in distinct subcellular compartments. SIRT1, SIRT6 and SIRT7 are found in nucleus, SIRT2 is primarily cytosolic and SIRT3, 4 and 5 are found in the mitochondria. The mitochondrial-only localization of SIRT3 is controversial and other groups have reported non-mitochondrial localization of this sirtuin [2223]. The biology and biochemistry of the seven mammalian sirtuins have been extensively discussed in the literature [2426] and is not the topic of this review. Instead, we focus on the mitochondrial sirtuins, their substrates, and their impact on mitochondrial biology.

The mitochondrial sirtuins, SIRT3–5 [212729], participate in the regulation of ATP production, metabolism, apoptosis and cell signaling. Unlike SIRT1, a 100 kDa protein, the mitochondrial sirtuins are small, ranging from 30–40 kDa. Thus, their amino acid sequence consists mostly of an N-terminal mitochondrial targeting sequence and the sirtuin core domain, with small flanking regions. Whereas, SIRT3 and SIRT5 function as NAD+-dependent deacetylases on well defined substrates, SIRT4 has no identified acetylated substrate and only shows ADP-ribosyltransferase activity. It is likely, however, that SIRT4 possesses substrate-specific NAD+-dependent deacetylase activity, as has been demonstrated for SIRT6 [30,31]. The three-dimensional structures for the core domains of human SIRT3 and human SIRT5 have been solved and reveal remarkable structural conservation with other sirtuins, such as the ancestral yeast protein and human SIRT2 (Figure 2) [3234]. Given its sequence conservation with the other sirtuins [18], it is likely that SIRT4 adopts a similar three-dimensional conformation.

Figure 2 Structure and alignment of sirtuins

Role of mitochondrial sirtuins in metabolism and energy production

The NAD+ dependence of sirtuins provided the first clue that these enzymes function as metabolic sensors. For instance, sirtuin activity can increase when NAD+ levels are abundant, such as times of nutrient deprivation. In line with this model, mass spectrometry studies have revealed that metabolic proteins, such as tricarboxylic acid (TCA) cycle enzymes, fatty acid oxidation enzymes and subunits of oxidative phosphorylation complexes are acetylated in response to metabolic stress [3537].

Fatty acid oxidation

Consistent with the hypothesis that nutrient stress alters sirtuin activity, a recent report identified significant metabolic abnormalities in Sirt3-/- mice during fasting [38]. In this study, hepatic SIRT3 protein expression increased during fasting, suggesting that both its levels and enzymatic activity are elevated during nutrient deprivation. SIRT3 activates hepatic lipid catabolism via deacetylation of long-chain acyl-CoA dehydrogenase (LCAD), a central enzyme in the fatty acid oxidation pathway. Sirt3-/- mice have diminished fatty acid oxidation, develop fatty liver, have low ATP production, and show a defect in thermogenesis and hypoglycemia during a cold test [38].

Surprisingly, many of the phenotypes observed in Sirt3-/- mice were also observed in mice lacking acetyl-CoA synthetase 2 (AceCS2), a previously identified substrate of SIRT3 [3940]. For example, fasting ATP levels were reduced by 50% in skeletal muscle of AceCS2-/- mice, in comparison to wild type (WT) mice. As a result, fasted AceCS2-/- mice were hypothermic and had reduced capacity for exercise. By converting acetate into acetyl CoA, AceCS2 provides an alternate energy source during times of metabolic challenges, such as thermogenesis or fasting. Interestingly, Acadl-deficient mice (Acadl encodes LCAD) also show cold intolerance, reduced ATP, and hypoglycemia under fasting conditions [41]. These overlapping phenotypes between Sirt3-/-AceCS2-/- and Acadl-/- mice indicate that the regulation of LCAD and AceCS2 acetylation by SIRT3 represents an important adaptive signal during the fasting response (Figure 2).

Electron transport chain

Of all mitochondrial proteins, oxidative phosphorylation complexes are among the most heavily acetylated. One study reported that 511 lysine residues in complexes I-IV and ATP synthase are modified by acetylation [37], hinting that a mitochondrial sirtuin might deacetylate these residues. Indeed, SIRT3 interacts with and deacetylates complex I subunits (including NDUFA9) [42], succinate dehydrogenase (complex II) [43]. SIRT3 has also been shown to bind ATP synthase in a proteomic analysis [44]. SIRT3 also regulates mitochondrial translation, a process which can impact electron transport [45]. Mice lacking SIRT3 demonstrate reduced ATP levels in many tissues [42 46]; however, additional work is required to determine if reduced ATP levels in Sirt3-/- mice is a direct result of OX PHOS hyperacetylation or an indirect effect, via decreased fatty acid oxidation, or a combination of both effects.

Less is known about the roles of SIRT4 and SIRT5 in electron transport. SIRT4 binds adenine nucleotide translocator (ANT), which transports ATP into the cytosol and ADP into the mitochondrial matrix, thereby providing a substrate for ATP synthase [20]. SIRT5 physically interacts with cytochrome C. The biological significance of these interactions, however, remains unknown [21].

TCA cycle

Enzymes for the TCA cycle (also called the Kreb’s cycle) are located in the mitochondrial matrix; this compartmentalization provides a way for cells to utilize metabolites from carbohydrates, fats and proteins. Numerous TCA cycle enzymes are modified by acetylation, although the functional consequences of acetylation have been examined for only a few of these proteins. SIRT3 interacts with several TCA cycle enzymes, including succinate dehydrogenase (SDH, see above [43]) and isocitrate dehydrogenase 2 (ICDH2) [33]. ICDH2 catalyzes the irreversible oxidative decarboxylation of isocitrate to form alpha-ketoglutarate and CO2, while converting NAD+ to NADH. Although the biological significance of these interactions is not yet known, it seems possible that SIRT3 might regulate flux through the TCA cycle.

Role of mitochondrial sirtuins in signaling

During cellular stress or damage, mitochondria release a variety of signals to the cytosol and the nucleus to alert the cell of changes in mitochondrial function. In response, the nucleus generates transcriptional changes to activate a stress response or repair the damage. For example, mitochondrial biogenesis requires a sophisticated transcriptional program capable of responding to the energetic demands of the cell by coordinating expression of both nuclear and mitochondrial encoded genes [4]. Unlike anterograde transcriptional control of mitochondria from nuclear transcription regulators such as PGC-1α, the retrograde signaling pathway, from the mitochondria to the nucleus is poorly understood in mammals. Although there is no evidence directly linking sirtuins to a mammalian retrograde signaling pathway, changes in mitochondrial sirtuin activity could influence signals transmitted from the mitochondria. Interestingly, the nuclear sirtuin SIRT1 deacetylates and activates PGC-1α, a key factor in the transcriptional regulation of genes involved in fatty acid oxidation and oxidative phosphorylation (Figure 3) [5051]. Thus, mitochondrial and nuclear sirtuins might exist in a signaling communication loop to control metabolism.

mitochondria-at-nexus-of-cellular-signaling-nihms239607f3

mitochondria-at-nexus-of-cellular-signaling-nihms239607f3

http://www.ncbi.nlm.nih.gov/pmc/articles/instance/2992946/bin/nihms239607f3.gif

Mitochondria at nexus of cellular signaling. Mitochondria and mitochondrial sirtuins play a central role in intra- and extra-cellular signaling. Circulating fatty acids and acetate provide whole body energy homeostasis. The mitochondrial metabolites NAD+, NADH, ATP, Ca2+, ROS, ketone bodies, and acetyl-CoA participate in intracellular signaling.

Numerous signaling pathways are activated by changes in mitochondrial release of metabolites and molecules, such as Ca2+, ATP, NAD+, NADH, nitric oxide (NO), and ROS (Figure 3). Of these, Ca2+ is the best studied as a mitochondrial messenger. Mitochondria are important regulators of Ca2+ storage and homeostasis, and mitochondrial Ca2+ uptake is directly tied to the membrane potential of the organelle. Membrane potential serves as a gauge of mitochondrial function: disruption of OXPHOS, interruption in the supply or catabolism of nutrients or loss of structural integrity generally result in a fall in membrane potential, and, in turn, decreased mitochondrial Ca2+ uptake. Subsequent increases in cytosolic free Ca2+ will activate calcineurin and several Ca2+-dependent kinases [52] and affect a wide variety of transcription factors to produce appropriate cell-specific transcriptional responses [53]. Through regulation of nutrient oxidation and electron transport or yet to be identified target(s), mitochondrial sirtuins could influence mAlthough the effect of sirtuins on intracellular calcium signaling has not been studied directly, sirtuin effects on ATP production have been shown. ANT facilitates the exchange of mitochondrial ATP with cytosolic ADP. As a result the cytosolic ATP:ADP ratio reflects changes in mitochondrial energy production. A fall in ATP production activates AMP-activated protein kinase (AMPK), which directly stimulates mitochondrial energy production, inhibits protein synthesis through regulation of mammalian target of rapamycin (mTOR), and influences mitochondrial transcriptional programs [54]. SIRT3 regulates ATP levels in a variety of tissues, suggesting that its activity could have an important role in ATP-mediated retrograde signaling [46,55]. Indeed, recent studies have shown that SIRT3 regulates AMPK activation [5658]. Furthermore, SIRT4 interacts with ANT [20], raising the possibility that SIRT4 activity also influences the ATP:ADP ratio or membrane potential and modulates important mitochondrial signals.

NAD+ and NADH levels are intimately connected with mitochondrial energy production and regulate mitochondrial sirtuin activity. Unlike NAD+, however, NADH is not a sirtuin co-substrate. Indeed, changes in the NAD+:NADH ratio can change the redox state of the cell and alter the activity of enzymes such as poly-ADP-ribose polymerases and sirtuins, with subsequent effects on signaling cascades and gene expression [5961]. Changes in mitochondrial sirtuin activity could change the balance of these metabolites within the mitochondria. For example, fatty acid oxidation reduces NAD+ to NADH, which is oxidized back to NAD+ by OXPHOS. However, it is unclear whether changes in NAD+/NADH can be transmitted outside the organelle. The inner mitochondrial membrane is impermeable to NAD+ and NADH; however, the mitochondrial malate-aspartate shuttle could transfer reducing equivalents across the mitochondrial membranes.

Mitochondrial sirtuin control of apoptosis

Apoptosis is a cellular process of programmed cell death. Mitochondria play an important role in apoptosis by the activation of mitochondrial outer membrane permeabilization, which represents the irrevocable point of no return in committing a cell to death. Outer membrane permeabilization leads to the release of caspase-activating molecules, caspase-independent death effectors, and disruption of ATP production. Despite the central role for mitochondria in the control of apoptosis, surprisingly little is known about how mitochondrial sirtuins participate in apoptotic programs. SIRT3 plays a pro-apoptotic role in both BCL2-53- and JNK-regulated apoptosis [63]. Additionally, cells lacking SIRT3 show decreased stress-induced apoptosis, lending further support for a pro-apoptotic role for SIRT3 [62]. Furthermore, recent work points to a tumor suppressive role for SIRT3: SIRT3 levels are decreased in human breast cancers and Sirt3 null mice develop mammary tumors after 12 months [62]. The mechanism for the tumor suppressive function of SIRT3 is incompletely understood, but involves repression of ROS and protection against DNA damage [62]. In conflicting studies, SIRT3 has been shown to be anti-apoptotic. For example, in the cellular response to DNA damage when mitochondrial NAD+ levels fall below critical levels, SIRT3 and SIRT4 display anti-apoptotic activity, protecting cells from death [64]. SIRT3 has also been shown to be cardioprotective, in part by activation of ROS clearance genes [65]. In future studies, it will be important to elucidate the balance achieved by SIRT3 between stress resistance (anti-apoptosis) and tumor suppression (pro-apoptosis). Additionally, the role of SIRT4 and SIRT5 in regulating metabolism suggests that these mitochondrial sirtuins could also contribute to apoptosis in tumor suppressive or stress resistant manners.

Concluding remarks

An elegant coordination of metabolism by mitochondrial sirtuins is emerging where SIRT3, SIRT4 and SIRT5 serve at critical junctions in mitochondrial metabolism by acting as switches to facilitate energy production during nutrient adaptation and stress. Rather than satisfy, these studies lead to more questions. How important are changes in global mitochondrial acetylation to mitochondrial biology and is acetylation status a readout for sirtuin activity? What are other substrates for SIRT4 and SIRT5? What molecular factors dictate substrate specificity for mitochondrial sirtuins? Moreover, further studies will provide insight into the therapeutic applications for targeting mitochondrial sirtuins to treat human diseases. It is clear that many discoveries have yet to be made in this exciting area of biology.

Body of review in energetic metabolic pathways in malignant T cells

Antigen stimulation of T cell receptor (TCR) signaling to nuclear factor (NF)-B is required for T cell proliferation and differentiation of effector cells.
The TCR-to-NF-B pathway is generally viewed as a linear sequence of events in which TCR engagement triggers a cytoplasmic cascade of protein-protein interactions and post-translational modifications, ultimately culminating in the nuclear translocation of NF-B.
Activation of effect or T cells leads to increased glucose uptake, glycolysis, and lipid synthesis to support growth and proliferation.
Activated T cells were identified with CD7, CD5, CD3, CD2, CD4, CD8 and CD45RO. Simultaneously, the expression of CD95 and its ligand causes apoptotic cells death by paracrine or autocrine mechanism, and during inflammation, IL1-β and interferon-1α. The receptor glucose, Glut 1, is expressed at a low level in naive T cells, and rapidly induced by Myc following T cell receptor (TCR) activation. Glut1 trafficking is also highly regulated, with Glut1 protein remaining in intracellular vesicles until T cell activation.

Dr. Aurel,
Targu Jiu

  1. sjwilliamspa

    Wouldn’t then the preferred target be mTORC instead of Sirtuins if mTORC represses Sirtuin activity?

  2. The answer may not be so simple, perhaps a conundrum.

    In conflicting studies, SIRT3 has been shown to be anti-apoptotic. For example, in the cellular response to DNA damage when mitochondrial NAD+ levels fall below critical levels, SIRT3 and SIRT4 display anti-apoptotic activity, protecting cells from death [64].

    For anti-cancer activity, apoptosis is a desired effect. This reminds me of the problem 15 years ago with the drug that would be effective against sepsis, the best paper of the year in NEJM. It failed.

    We tend to not appeciate the intricacies of biological interactions and fail to see bypass reactions. Pleotropy comes up again and again. The seminal work from Britton Chances lab on the NAD+/NADH ratio have been overlooked.

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Mitochondrial Isocitrate Dehydrogenase and Variants

Writer and Curator: Larry H. Bernstein, MD, FCAP 

2.1.4      Mitochondrial Isocitrate Dehydrogenase (IDH) and variants

2.1.4.1 Accumulation of 2-hydroxyglutarate is not a biomarker for malignant progression of IDH-mutated low grade gliomas

Juratli TA, Peitzsch M, Geiger K, Schackert G, Eisenhofer G, Krex D.
Neuro Oncol. 2013 Jun;15(6):682-90
http://dx.doi.org:/10.1093/neuonc/not006

Low-grade gliomas (LGG) occur in the cerebral hemispheres and represent 10%–15% of all astrocytic brain tumors.1 Despite long-term survival in many patients, 50%–75% of patients with LGG eventually die of either progression of a low-grade tumor or transformation to a malignant glioma.2 The time to progression can vary from a few months to several years,35 and the median survival among patients with LGG ranges from 5 to 10 years.6,7 Among several risk factors, only age, histology, tumor location, and Karnofsky performance index have generally been accepted as prognostic factors for patients with LGG.8,9 As a prognostic molecular marker, only 1p19q codeletion was identified as such in pure oligodendrogliomas. However, this association was not seen in either astrocytomas or oligoastrocytomas.10

Somatic mutations in human cytosolic isocitrate dehydrogenases 1 (IDH1) were first described in 2008 in ∼12% of glioblastomas11 and later in acute myeloid leukemia, in which the reported mutations were missense and specific for a single R132 residue.11,12 Some gliomas lacking cytosolic IDH1 mutations were later observed to have mutations in IDH2, the mitochondrial homolog of IDH1.12 IDH mutations are the most commonly mutated genes in many types of gliomas, with incidences of up to 75% in grade II and grade III gliomas.13,14 Further frequent mutations in patients with LGG were recently identified, including inactivating alterations in alpha thalassemia/mental retardation syndrome X-linked (ATRX), inactivating mutations in 2 suppressor genes, homolog of Drosophila capicua (CIC) and far-upstream binding protein 1 (FUBP1), in about 70% of grade II gliomas and 57% of sGBM.1517 The association between ATRX mutations with IDHmutations and the association between CIC/FUBP1 mutations and IDH mutations and 1p/19q loss are especially common among the grade II-III gliomas and remarkably homogeneous in terms of genetic alterations and clinical characteristics.16

It was thought that IDH mutations might be a prognostic factor in LGG, predicting a prolonged survival from the beginning of the disease.1823 However, this assumption, as shown in our and other earlier studies, had to be corrected because survival among patients who have LGG with IDH mutations is only improved after transformation to secondary high-grade gliomas.18,19,24 Furthermore, it had already been demonstrated that an IDH mutation is not a biomarker for further malignant transformation in LGG.18 IDH1 and IDH2 catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG) and reduce NADP to NADPH.25 The mutations inactivate the standard enzymatic activity of IDH112 and confer novel activity on IDH1 for conversion of α-KG and NADPH to 2-hydroxyglutarate (2HG) and NADP+, supporting the evidence thatIDH1 and 2 are proto-oncogenes. This gain of function causes an accumulation of 2HG in glioma and acute myeloid leukemia samples.26,27 The 2HG levels in cancers with IDH mutations are found to be consistently elevated by 10–100-fold, compared with levels in samples lacking mutations of IDH1 or IDH2.26,28Nevertheless, how exactly the production or accumulation of 2HG by mutant IDH might drive cancer development is not well understood.

In the present study, we postulate that intratumoral 2HG could be a useful biomarker that predicts the malignant transformation of WHO grade II LGG. We therefore screened for IDH mutations in patients with LGG and measured the accumulation of 2HG in 2 populations of patients, patients with LGG with and without malignant transformation, with use of liquid chromatography–tandem mass spectrometry (LC-MS/MS). Furthermore, we compared the concentrations of 2HG in LGG and their consecutive secondary glioblastomas (sGBM) to evaluate changes in metabolite levels during the malignant progression.

Objectives: To determine whether accumulation of 2-hydroxyglutarate in IDH-mutated low-grade gliomas (LGG; WHO grade II) correlates with their malignant transformation and to evaluate changes in metabolite levels during malignant progression. Methods: Samples from 54 patients were screened for IDH mutations: 17 patients with LGG without malignant transformation, 18 patients with both LGG and their consecutive secondary glioblastomas (sGBM; n = 36), 2 additional patients with sGBM, 10 patients with primary glioblastomas (pGBM), and 7 patients without gliomas. The cellular tricarboxylic acid cycle metabolites, citrate, isocitrate, 2-hydroxyglutarate, α-ketoglutarate, fumarate, and succinate were profiled by liquid chromatography-tandem mass spectrometry. Ratios of 2-hydroxyglutarate/isocitrate were used to evaluate differences in 2-hydroxyglutarate accumulation in tumors from LGG and sGBM groups, compared with pGBM and nonglioma groups. Results: IDH1 mutations were detected in 27 (77.1%) of 37 patients with LGG. In addition, in patients with LGG with malignant progression (n = 18), 17 patients were IDH1 mutated with a stable mutation status during their malignant progression. None of the patients with pGBM or nonglioma tumors had an IDH mutation. Increased 2-hydroxyglutarate/isocitrate ratios were seen in patients with IDH1-mutated LGG and sGBM, in comparison with those with IDH1-nonmutated LGG, pGBM, and nonglioma groups. However, no differences in intratumoral 2-hydroxyglutarate/isocitrate ratios were found between patients with LGG with and without malignant transformation. Furthermore, in patients with paired samples of LGG and their consecutive sGBM, the 2-hydroxyglutarate/isocitrate ratios did not differ between both tumor stages. Conclusion: Although intratumoral 2-hydroxyglutarate accumulation provides a marker for the presence of IDH mutations, the metabolite is not a useful biomarker for identifying malignant transformation or evaluating malignant progression.

LC-MS/MS Analysis of Tricarboxylic Acid Cycle (TCA) Metabolites

Instrumentation included an AB Sciex QTRAP 5500 triple quadruple mass spectrometer coupled to a high-performance liquid chromatography (HPLC) system from Shimadzu containing a binary pump system, an autosampler, and a column oven. Targeted analyses of citrate, isocitrate, α-ketoglutarate (α-KG), succinate, fumarate (Sigma-Aldrich), and 2-hydroxyglutarate (2HG; SiChem GmbH) were performed in multiple reaction monitoring (MRM) scan mode with use of negative electrospray ionization (-ESI). Expected mass/charge ratios (m/z), assumed as [M-H+], were m/z 190.9, m/z 191.0, m/z 145.0, m/z 116.9, m/z 114.8, and m/z 147.0 for citrate, isocitrate, α-KG, succinate, fumarate, and 2HG, respectively. For quantification, ratios of analytes and respective stable isotope-labeled internal standards (IS) (Table 2) were used. For quantification of isocitrate and 2HG, stable isotope-labeled succinate was used as IS because of unavailability of labeled analogs. MRM transitions are summarized in Table 2.

IDH1 Mutation and Outcome

An IDH1 mutation was detected in 27 of 35 patients with LGG (77.1%), in 10 of 17 patients in LGG1 (59%), and in 17 of 18 patients in LGG2 (95%). In all cases, IDH1 mutations were found on R132. IDH2mutations were not detected in any of the patients. The IDH1 mutation status was stable during progression from LGG to sGBM in all patients in LGG2. None of the patients with pGBM or nonglioma had an IDH mutation. Patients with LGG with an IDH1 mutation had a median PFS of 3.3 years, which was comparable to that among patients with wild-type LGG (2.8 years; P > .05). Furthermore, the OS among patients with LGG with an IDH1 mutation was not statistically different at 13.0 years compared with that among patients with LGG without an IDH1 mutation, who had an OS of 9.3 years (P = .66).

LC-MS/MS Profiling of TCA Metabolites

TCA metabolites, citrate, isocitrate, α-ketoglutarate, succinate, fumarate, and 2-hydroxyglutarate were measured in glioma samples with and without an IDH1 mutation, in samples identified as primary GBM, and in nonglioma brain tumor specimens (Fig. 1). No differences in citrate, isocitrate, α-KG, succinate, and fumarate concentrations were found when comparing all of the latter groups. Concentrations of 2HG, a side product in IDH1-mutated gliomas, were 20–34-fold higher in IDH1-mutated gliomas (0.64–0.81 µmol/g), compared with non–IDH1-mutated LGG1 (P ≤ .001). No differences were observed between IDH1-mutated gliomas and IDH1-nonmutated LGG2 and sGBM, caused by strongly elevated 2HG levels in either 1 or 2 samples in these groups, respectively. Furthermore, in IDH1-mutated gliomas, 2HG concentrations were a mean of 20 times higher than in pGBM and nongliomas (P ≤ .001) (Fig. 1). No differences were observed between the single groups of IDH1-mutated gliomas LGG1, LGG2, and sGBM in relation to 2HG concentration.

Fig. 1.  Dot-box and whisker plots show concentration ranges for TCA metabolites measured in IDH1-nonmutated (IDH1wt) and IDH1-mutated (IDH1mut) LGG and sGBM and in pGBM and nonglioma tumor specimens

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To detect possible differences among the IDH1-mutated LGG1, LGG2, and sGBM, the α-KG/isocitrate and 2HG/isocitrate ratios were used in additional tests. Therefore, the direct precursor-product relation would correct for all differences possibly expected during pre-analytical processing. To prove this, analyte ratios ofIDH1-mutated and nonmutated gliomas were compared. IDH1-mutated gliomas showed a 2HG/isocitrate ratio that was 13 times higher (P ≤ .001) (Fig. 2A), which corresponds to a lower accumulation of 2HG inIDH1-nonmutated gliomas. α-KG/isocitrate ratios were determined to be approximately 10-fold higher inIDH1-mutated gliomas than in IDH1-nonmutated gliomas (P = .005) (Fig. 2B), which also implies lower accumulation of α-KG in IDH1-nonmutated gliomas.

2-hydroxyglutarate-to-isocitrate-ratios

2-hydroxyglutarate-to-isocitrate-ratios

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661092/bin/not00602.jpg

Fig. 2.  2-Hydroxyglutarate to isocitrate ratios (A) and α-ketoglutarate to isocitrate ratios (B) for IDH1-nonmutated (IDH1wt) and IDH1-mutated (IDH1mut) gliomas (LGG and sGBM); boxes span the 25th and 75th percentiles with median, and whiskers represent the 10th and 90th percentiles with points as outliers. Abbreviations: LGG, low-grade gliomas; sGBM, secondary glioblastomas.

2HG/isocitrate and α-KG/isocitrate ratios, respectively, were calculated in all 8 specimen groups (Fig. 3). In addition to the differences in 2HG/isocitrate ratios of IDH1-mutated and nonmutated gliomas (Fig. 2A), the ratios in IDH1-mutated gliomas were 4–9 times higher, compared with those in pGBM (P ≤ .001), and 3–6 times higher, compared with those in non-glioma tumor specimens, which was not statistically significant (Fig. 3A). In detail, ratios of 2HG and isocitrate were established to be 13, 9.4, and 22 times higher in IDH1-mutated LGG1, LGG2, and their consecutive sGBM, respectively, than in IDH1-nonmutated LGG1 (Fig. 3A). No significant differences were observed between IDH1-mutated gliomas and IDH1-nonmutated LGG2 and sGBM. The comparison of 2HG/isocitrate ratios between IDH1-nonmutated gliomas and IDH1-mutated LGG2 and sGBM showed no statistically significant differences. However, a trend toward higher ratios inIDH1-mutated LGG1/2 was seen. Furthermore, no differences could be determined by comparing 2HG/isocitrate ratios measured in the groups of IDH1-mutated LGG1 and LGG2. Although 2HG/isocitrate ratios in IDH1-mutated secondary glioblastomas are 1.7 and 2.3 times higher than in the LGG1 and LGG2 groups, respectively, no statistically significant differences were observed.   Fig. 3.

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The absence of a straight trend to higher 2HG/isocitrate ratios during malignant progression is shown by paired analysis of IDH1-mutated LGG2 and their consecutive sGBM (Fig. 3C). Similar findings were observed using the α-KG/isocitrate ratios. Although significant differences were found, with ratios approximately 10 times higher in IDH1-mutated glioblastomas than in IDH1-nonmutated glioblastomas (Fig. 2B), it was not possible to differentiate among the 3 IDH1-mutated glioblastoma groups LGG1, LGG2, and their consecutive sGBM with use of this analyte ratio (Fig. 3B and D).

On the basis of a comprehensive analysis of cellular TCA metabolites from several cohorts of patients with glioma and nonglioma, our study provides evidence that the level of 2HG accumulation is not suitable as an early biomarker for distinguishing patients with LGG in relation to their course of malignancy. To our knowledge, this is the first report of a paired analysis of 2HG levels in LGG and their consecutive sGBM showing stable 2HG accumulation during malignant progression. This fact assumes that malignant transformation of IDH-mutated LGG appears to be independent of their intracellular 2HG accumulation. Considering these results, we could not stratify patients with LGG into subgroups with distinct survival.

2.1.4.2 An Inhibitor of Mutant IDH1 Delays Growth and Promotes Differentiation of Glioma Cells

Rohle D1, Popovici-Muller J, Palaskas N, Turcan S, Grommes C, et al.
Science. 2013 May 3; 340(6132):626-30
http://dx.doi.org:/10.1126/science.1236062

The recent discovery of mutations in metabolic enzymes has rekindled interest in harnessing the altered metabolism of cancer cells for cancer therapy. One potential drug target is isocitrate dehydrogenase 1 (IDH1), which is mutated in multiple human cancers. Here, we examine the role of mutant IDH1 in fully transformed cells with endogenous IDH1 mutations. A selective R132H-IDH1 inhibitor (AGI-5198) identified through a high-throughput screen blocked, in a dose-dependent manner, the ability of the mutant enzyme (mIDH1) to produce R-2-hydroxyglutarate (R-2HG). Under conditions of near-complete R-2HG inhibition, the mIDH1 inhibitor induced demethylation of histone H3K9me3 and expression of genes associated with gliogenic differentiation. Blockade of mIDH1 impaired the growth of IDH1-mutant–but not IDH1-wild-type–glioma cells without appreciable changes in genome-wide DNA methylation. These data suggest that mIDH1 may promote glioma growth through mechanisms beyond its well-characterized epigenetic effects.

Somatic mutations in the metabolic enzyme isocitrate dehydrogenase (IDH) have recently been identified in multiple human cancers, including glioma (12), sarcoma (34), acute myeloid leukemia (56), and others. All mutations map to arginine residues in the catalytic pockets of IDH1 (R132) or IDH2 (R140 and R172) and confer on the enzymes a new activity: catalysis of alpha-ketoglutarate (2-OG) to the (R)-enantiomer of 2-hydroxyglutarate (R-2HG) (78). R-2HG is structurally similar to 2-OG and, due to its accumulation to millimolar concentrations in IDH1-mutant tumors, competitively inhibits 2-OG–dependent dioxygenases (9).

The mechanism by which mutant IDH1 contributes to the pathogenesis of human glioma remains incompletely understood. Mutations in IDH1 are found in 50 to 80% of human low-grade (WHO grade II) glioma, a disease that progresses to fatal WHO grade III (anaplastic glioma) and WHO grade IV (glioblastoma) tumors over the course of 3 to 15 years. IDH1 mutations appear to precede the occurrence of other mutations (10) and are associated with a distinctive gene-expression profile (“proneural” signature), DNA hypermethylation [CpG island methylator phenotype (CIMP)], and certain clinicopathological features (1113). When ectopically expressed in immortalized human astrocytes, R132H-IDH1 promotes the growth of these cells in soft agar (14) and induces epigenetic alterations found in IDH1-mutant human gliomas (15,16). However, no tumor formation was observed when R132H-IDH1 was expressed from the endogenousIDH1 locus in several cell types of the murine central nervous system (17).

To explore the role of mutant IDH1 in tumor maintenance, we used a compound that was identified in a high-throughput screen for compounds that inhibit the IDH1-R132H mutant homodimer (fig. S1 and supplementary materials) (18). This compound, subsequently referred to as AGI-5198 (Fig. 1A), potently inhibited mutant IDH1 [R132H-IDH1; half-maximal inhibitory concentration (IC50), 0.07 µM) but not wild-type IDH1 (IC50 > 100 µM) or any of the examined IDH2 isoforms (IC50 > 100 µM) (Fig. 1B). We observed no induction of nonspecific cell death at the highest examined concentration of AGI-5198 (20 µM).

Fig. 1 An R132H-IDH1 inhibitor blocks R-2HG production and soft-agar growth of IDH1-mutant glioma cells

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an-r132h-idh1-inhibitor-blocks-r-2hg-production-and-soft-agar-growth-of-idh1-mutant-glioma-cells

an-r132h-idh1-inhibitor-blocks-r-2hg-production-and-soft-agar-growth-of-idh1-mutant-glioma-cells

(A) Chemical structure of AGI-5198. (B) IC50 of AGI-5198 against different isoforms of IDH1 and IDH2, measured in vitro. (C) Sanger sequencing chromatogram (top) and comparative genomic hybridization profile array (bottom) of TS603 glioma cells. (D) AGI-5198 inhibits R-2HG production in R132H-IDH1 mutant TS603 glioma cells. Cells were treated for 2 days with AGI-5198, and R-2HG was measured in cell pellets. R-2HG concentrations are indicated above each bar (in mM). Error bars, mean ± SEM of triplicates. (E and F) AGI-5198 impairs soft-agar colony formation of (E) IDH1-mutant TS603 glioma cells [*P < 0.05, one-way analysis of variance (ANOVA)] but not (F) IDH1–wild-type glioma cell lines (TS676 and TS516). Error bars, mean ± SEM of triplicates.

We next explored the activity of AGI-5198 in TS603 glioma cells with an endogenous heterozygous R132H-IDH1 mutation, the most common IDH mutation in glioma (2). TS603 cells were derived from a patient with anaplastic oligodendroglioma (WHO grade III) and harbor another pathognomomic lesion for this glioma subtype, namely co-deletion of the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q) (19) (Fig. 1C). Measurements of R-2HG concentrations in pellets of TS603 glioma cells demonstrated dose-dependent inhibition of the mutant IDH1 enzyme by AGI-5198 (Fig. 1D). When added to TS603 glioma cells growing in soft agar, AGI-5198 inhibited colony formation by 40 to 60% (Fig. 1E). AGI-5198 did not impair colony formation of two patient-derived glioma lines that express only the wild-type IDH1allele (TS676 and TS516) (Fig. 1F), further supporting the selectivity of AGI-5198.

After exploratory pharmacokinetic studies in mice (fig. S2), we examined the effects of orally administered AGI-5198 on the growth of human glioma xenografts. When given daily to mice with established R132H-IDH1 glioma xenografts, AGI-5198 [450 mg per kg of weight (mg/kg) per os] caused 50 to 60% growth inhibition (Fig. 2A). Treatment was tolerated well with no signs of toxicity during 3 weeks of daily treatment (fig. S3). Tumors from AGI-5198– treated mice showed reduced staining with an antibody against the Ki-67 protein, a marker used for quantification of tumor cell proliferation in human brain tumors. In contrast, staining with an antibody against cleaved caspase-3 showed no differences between tumors from vehicle and AGI-5198–treated mice (fig. S4), suggesting that the growth-inhibitory effects of AGI-5198 were primarily due to impaired tumor cell proliferation rather than induction of apoptotic cell death. AGI-5198 did not affect the growth of IDH1 wild-type glioma xenografts (Fig. 2B).

Fig. 2 AGI-5198 impairs growth of IDH1-mutant glioma xenografts in mice

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AGI-5198 impairs growth of IDH1-mutant glioma xenografts in mice

AGI-5198 impairs growth of IDH1-mutant glioma xenografts in mice

Given the likely prominent role of R-2HG in the pathogenesis of IDH-mutant human cancers, we investigated whether intratumoral depletion of this metabolite would have similar growth inhibitory effects onR132H-IDH1-mutant glioma cells as AGI-5198. We engineered TS603 sublines in which IDH1–short hairpin RNA (shRNA) targeting sequences were expressed from a doxycycline-inducible cassette. Doxycycline had no effect on IDH1 protein levels in cells expressing the vector control but depleted IDH1 protein levels by 60 to 80% in cells infected with IDH1-shRNA targeting sequences (Fig. 2C). We next injected these cells into the flanks of mice with severe combined immunodeficiency and, after establishment of subcutaneous tumors, randomized the mice to receive either regular chow or doxycycline-containing chow. As predicted from our experiments with AGI-5198, doxycycline impaired the growth of TS603 glioma cells expressing inducible IDH1-shRNAs in soft agar (fig. S5) and in vivo (Fig. 2D) but had no effect on the growth of tumors expressing the vector control (fig. S6). Immunohistochemistry (IHC) with a mutant-specific R132H-IDH1 antibody confirmed depletion of the mutant IDH1 protein in IDH1-shRNA tumors treated with doxycycline. This was associated with an 80 to 90% reduction in intratumoral R-2HG levels, similar to the levels observed in TS603 glioma xenografts treated with AGI-5198 (fig. S7). Knockdown of the IDH1 protein in R132C-IDH1-mutant HT1080 sarcoma cells similarly impaired the growth of these cells in vitro and in vivo (fig. S8).

Fig. 3 AGI-5198 promotes astroglial differentiation in R132H-IDH1  mutant cells
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The gene-expression data suggested that treatment of IDH1-mutant glioma xenografts with AGI-5198 promotes a gene-expression program akin to gliogenic (i.e., astrocytic and oligodendrocytic) differentiation. To examine this question further, we treated TS603 glioma cells ex vivo with AGI-5198 and performed immunofluorescence for glial fibrillary acidic protein (GFAP) and nestin (NES) as markers for astrocytes and undifferentiated neuroprogenitor cells, respectively. .. We investigated whether blockade of mutant IDH1 could restore this ability, and this was indeed the case (Fig. 3D). These results indicate that mIDH1 plays an active role in restricting cellular differentiation potential, and this defect is acutely reversible by blockade of the mutant enzyme.

In the developing central nervous system, gliogenic differentiation is regulated through changes in DNA and histone methylation (24). Mutant IDH1 can affect both epigenetic processes through R-2HG mediated suppression of TET (ten-eleven translocation) methyl cytosine hydroxylases and Jumonji-C domain histone demethylases (JHDMs). We therefore sought to define the epigenetic changes that were associated with the acute growth-inhibitory effects of AGI-5198 in vivo. .. Treatment of mice with AGI-5198 resulted in dose-dependent reduction of intratumoral R-2HG with partial R-2HG reduction at the 150 mg/kg dose (0.85 ± 0.22 mM) and near-complete reduction at the 450 mg/kg dose (0.13 ± 0.03 mM) (Fig. 4A).

Fig. 4 Dose-dependent inhibition of histone methylation in IDH1-mutant gliomas after short term treatment with AGI-5198

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We next examined whether acute pharmacological blockade of the mutant IDH1 enzyme reversed the CIMP, which is strongly associated with IDH1-mutant human gliomas (12). ..  On a genome-wide scale, we observed no statistically significant change in the distribution of β values between AGI-5198– and vehicle-treated tumors (Fig. 4B) (supplementary materials).
We next examined the kinetics of histone demethylation after inhibition of the mutant IDH1 enzyme. The histone demethylases JMJD2A and JMJD2C, which remove bi- and trimethyl marks from H3K9, are significantly more sensitive to inhibition by the R-2HG oncometabolite than other 2-OG–dependent oxygenases (891425). Restoring their enzymatic activity in IDH1-mutant cancer cells would thus be expected to require near-complete inhibition of R-2HG production. Consistent with this prediction, tumors from the 450 mg/kg AGI-5198 cohort showed a marked decrease in H3K9me3 staining, but there was no decrease in H3K9me3 staining in tumors from the 150 mg/kg AGI-5198 cohort (Fig. 4C) (fig. S11). Of note, AGI-5198 did not decrease H3K9 trimethylation in IDH1–wild-type glioma xenografts (fig. S12A) or in normal astrocytes (fig. S12B), demonstrating that the effect of AGI-5198 on histone methylation was not only dose-dependent but also IDH1-mutant selective.

Because the inability to erase repressive H3K9 methylation can be sufficient to impair cellular differentiation of nontransformed cells (16), we examined the TS603 xenograft tumors for changes in the RNA expression of astrocytic (GFAP, AQP4, and ATP1A2) and oligodendrocytic (CNP and NG2) differentiation markers by real-time polymerase chain reaction (RT-PCR). Compared with vehicletreated tumors, we observed an increase in the expression of astroglial differentiation genes only in tumors treated with 450 mg/kg AGI-5198 (Fig. 4D).

In summary, we describe a tool compound (AGI-5198) that impairs the growth of R132H-IDH1-mutant, but not IDH1 wild-type, glioma cells. This data demonstrates an important role of mutant IDH1 in tumor maintenance, in addition to its ability to promote transformation in certain cellular contexts (1426). Effector pathways of mutant IDH remain incompletely understood and may differ between tumor types, reflecting clinical differences between these disorders. Although much attention has been directed toward TET-family methyl cytosine hydroxylases and Jumonji-C domain histone demethylases, the family of 2-OG–dependent dioxygenases includes more than 50 members with diverse functions in collagen maturation, hypoxic sensing, lipid biosynthesis/metabolism, and regulation of gene expression (27).

2.1.4.3 Detection of oncogenic IDH1 mutations using MRS

OC Andronesi, O Rapalino, E Gerstner, A Chi, TT Batchelor, et al.
J Clin Invest. 2013;123(9):3659–3663
http://dx.doi.org:/10.1172/JCI67229

The investigation of metabolic pathways disturbed in isocitrate dehydrogenase (IDH) mutant tumors revealed that the hallmark metabolic alteration is the production of D-2-hydroxyglutarate (D-2HG). The biological impact of D-2HG strongly suggests that high levels of this metabolite may play a central role in propagating downstream the effects of mutant IDH, leading to malignant transformation of cells. Hence, D-2HG may be an ideal biomarker for both diagnosing and monitoring treatment response targeting IDH mutations. Magnetic resonance spectroscopy (MRS) is well suited to the task of noninvasive D-2HG detection, and there has been much interest in developing such methods. Here, we review recent efforts to translate methodology using MRS to reliably measure in vivo D-2HG into clinical research.

Recurrent heterozygous somatic mutations of the isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) genes were recently found by genome-wide sequencing to be highly frequent (50%–80%) in human grade II–IV gliomas (12). IDH mutations are also often observed in several other cancers, including acute myeloid leukemia (3), central/periosteal chondrosarcoma and enchondroma (4), and intrahepatic cholangiocarcinoma (5). The identification of frequent IDH mutations in multiple cancers suggests that this pathway is involved in oncogenesis. Indeed, increasing evidence demonstrates that IDH mutations alter downstream epigenetic and genetic cellular signal transduction pathways in tumors (67). In gliomas, IDH1 mutations appear to define a distinct clinical subset of tumors, as these patients have a 2- to 4-fold longer median survival compared with patients with wild-type IDH1 gliomas (8). IDH1 mutations are especially common in secondary glioblastoma (GBM) arising from lower-grade gliomas, arguing that these mutations are early driver events in this disease (9). Despite aggressive therapy with surgery, radiation, and cytotoxic chemotherapy, average survival of patients with GBM is less than 2 years, and less than 10% of patients survive 5 years or more (10).

The discovery of cancer-related IDH1 mutations has raised hopes that this pathway can be targeted for therapeutic benefit (1112). Methods that can rapidly and noninvasively identify patients for clinical trials and determine the pharmacodynamic effect of candidate agents in patients enrolled in trials are particularly important to guide and accelerate the translation of these treatments from bench to bedside. Magnetic resonance spectroscopy (MRS) can play an important role in clinical and translational research because IDH mutated tumor cells have such a distinct molecular phenotype (13,14).

The family of IDH enzymes includes three isoforms: IDH1, which localizes in peroxisomes and cytoplasm, and IDH2 and IDH3, which localize in mitochondria as part of the tricarboxylic acid cycle (11). All three wild-type enzymes catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (αKG), using the cofactor NADP+ (IDH1 and IDH2) or NAD+(IDH3) as the electron acceptor. To date, only mutations of IDH1 and IDH2 have been identified in human cancers (11), and only one allele is mutated. In gliomas, about 90% of IDH mutations involve a substitution in IDH1 in which arginine 132 (R132) from the catalytic site is replaced by a histidine (IDH1 R132H), known as the canonical IDH1 mutation (8). A number of noncanonical mutations such as IDH1 R132C, IDH1 R132S, IDH1 R132L, and IDH1 R132G are less frequently present. Arginine R172 in IDH2 is the corresponding residue to R132 in IDH1, and the most common mutation is IDH2 R172K. In addition to IDH2 R172K, IDH2 R140Q has also been observed in acute myeloid leukemia. Although most IDH1 mutations occur at R132, a small number of mutations producing D-2-hydroxyglutarate (D-2HG) occur at R100, G97, and Y139 (15). However, only a single residue is mutated in either IDH1 or IDH2 in a given tumor.

IDH mutations result in a very high accumulation of the oncometabolite D-2HG in the range of 5- to 35-mM levels, which is 2–3 orders of magnitude higher than D-2HG levels in tumors with wild-type IDH or in healthy tissue (13). All IDH1 G97, R100, R132, and Y139 and IDH2 R140 and R172 mutations confer a neomorphic activity to the IDH1/2 enzymes, switching their activity toward the reduction of αKG to D-2HG, using NADPH as a cofactor (15). The gain of function conferred by these mutations is possible because in each tumor cell a copy of the wild-type allele exists to supply the αKG substrate and NADPH cofactor for the mutated allele.

A cause and effect relationship between IDH mutation and tumorigenesis is probable, and D-2HG appears to play a pivotal role as the relay agent. Evidence is mounting that high levels of D-2HG alter the biology of tumor cells toward malignancy by influencing the activity of enzymes critical for regulating the metabolic (14) and epigenetic state of cells (671618). D-2HG may act as an oncometabolite via competitive inhibition of αKG-dependent dioxygenases (16). This includes inhibition of histone demethylases and 5-methlycytosine hydroxylases (e.g., TET2), leading to genome-wide alterations in histone and DNA hypermethylation as well as inhibition of hydroxylases, resulting in upregulation of HIF-1 (19). The effects of D-2HG have been shown to be reversible in leukemic transformation (18), which gives further evidence that treatments that lower D-2HG could be a valid therapeutic approach for IDH-mutant tumors. In addition to increased D-2HG, widespread metabolic disturbances of the cellular metabolome have been measured in cells with IDH mutations, including changes in amino acid concentration (increased levels of glycine, serine, threonine, among others, and decreased levels of aspartate and glutamate), N-acetylated amino acids (N-acetylaspartate, N-acetylserine, N-acetylthreonine), glutathione derivatives, choline metabolites, and TCA cycle intermediates (fumarate, malate) (14). These metabolic changes might be exploited for therapy. For example, IDH mutations cause a depletion of NADPH, which lowers the reductive capabilities of tumor cells (20) and perhaps makes them more susceptible to treatments that create free radicals (e.g., radiation) (21).

In vivo MRS of D-2HG in IDH mutant tumors

D-2HG may be an optimal biomarker for tumors with IDH mutations, as it ideally fulfills several important requirements: (a) there is virtually no normal D-2HG background — in cells without IDH mutations, D-2HG is produced as an error product of normal metabolism and is only present at trace levels; (b) 99% of tumors with IDH mutations have increased levels of D-2HG by several orders of magnitude; (c) the only other known cause of elevated 2HG is hydroxyglutaric aciduria (in this case, high L-2HG caused by a mutation in 2HG dehydrogenase), which is a rare inborn error of metabolism that presents with a different clinical phenotype and marked developmental anomalies in early childhood. Hence, tumors displaying increased levels of D-2HG are unlikely to represent false-positive cases for IDH mutations. Furthermore, this raises the possibility that D-2HG levels could also be used to quantify and predict the efficacy of drugs targeting mutant IDH1 for antitumor therapy (1115). In fact, it is hard to find a similar example of another tumor biomarker metabolite that is so well supported by the underlying biology.

The high levels of D-2HG observed in IDH1-mutant gliomas are amenable to detection by in vivo MRS. Given that the detection threshold of in vivo MRS is around 1 mM (1 μmol/g, wet tissue), D-2HG should be measurable only in situations in which it accumulates due to IDH1 mutations. Conversely, D-2HG is not expected to be detectable in tumors in which IDH1 is not mutated or in healthy tissues. In addition, ex vivo MRS measurements of intact biopsies (22) or extracts reach higher sensitivity 0.1–0.01 mM (0.1–0.01 μmol/g) and can be used as a cheaper and faster alternative to mass spectrometry.

Recently, reliable detection of D-2HG using in vivo 1H MRS was demonstrated in glioma patients (2930). Andronesi et al. reported the unambiguous detection of D-2HG in mutant IDH1 glioma in vivo using 2D correlation spectroscopy (COSY) and J-difference spectroscopy (29). In 2D COSY the overlapping signals are resolved along a second orthogonal chemical shift dimension (3132), and in the case of D-2HG, the cross-peaks resulting from the scalar coupling of Hα-Hβ protons show up in a region that is free of the contribution of other metabolites in both healthy and wild-type tumors. While 2D COSY retains all the metabolites in the spectrum, J-difference spectroscopy (2533) takes the opposite approach instead by focusing on the metabolite of interest, such as D-2HG, and selectively applying a narrow-band radiofrequency pulse to selectively refocus the Hα-Hβ scalar coupling evolution, then removing the contribution of overlapping metabolites. In this case a 1D difference spectrum with the Hα signal of D-2HG is detected at 4.02 ppm. Both methods have strengths and weaknesses: 2D COSY has the highest resolving power to disentangle overlapping metabolites, but has less sensitivity and quantification is more complex; J-difference spectroscopy has increased sensitivity, and quantification is straightforward, but it is susceptible to subtraction errors.

In Table 1, a comparison is made among the published methods for D-2HG detection. Results selected from the literature are shown in Figure 1. Besides the approaches discussed thus far, other methods are available in the in vivo MRS armamentarium that could be perhaps explored for reliable detection of 2D-HG, such as multiple-quantum filtering sequences (3435) and a variety of 2D spectroscopic methods (3639).

Table 1 Summary of in vivo 1H MRS methods used in the literature for detection of D-2HG in patients with mutant IDH glioma

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Figure 1 In vivo D-2HG measurements: (A) J-difference spectroscopy with MEGA-LASER sequence in a patient with GBM with mutant IDH1. Adapted with permission from Science Translational Medicine (29). (B) Spectral editing with PRESS sequence of TE 97 ms (TE1: 32 ms, TE2: 65 ms) in a patient with mutant IDH1 oligodendroglioma. Adapted with permission from Nature Medicine (30). (C) Spectra acquired with PRESS sequence of TE 30 ms in a patient with mutant IDH1 anaplastic astrocytoma. Adapted with permission from Journal of Neuro-Oncology (24). Cho, choline; Cre, creatine; Gln, glutamine; Glu, glutamate; Lac, lactate; MM, macromolecules; NAA, N-acetyl- aspartate.

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Ex vivo MRS of D-2HG in tumors with IDH mutations

The panoply of methods and ability of ex vivo MRS (50) to detect D-2HG in patient samples is far superior to in vivo MRS because the above list of limitations and artifacts is not of concern.

Metabolic profiling of intact tumor biopsies as small as 1 mg can be performed with high-resolution magic angle spinning (HRMAS) (5153). HRMAS preserves the integrity of the samples that can be further analyzed with immunohistochemistry, genomics, or other metabolic profiling tools such as mass spectrometry. Detection of D-2HG in mutant IDH1 glioma was confirmed by ex vivo HRMAS experiments (295455). In addition to D-2HG, ex vivo HRMAS studies can detect quantitative and qualitative changes for a large number of metabolites in IDH mutated tumors (5455).

The example of IDH1 mutations is a perfect illustration of the rapid pace of progress brought to the medical sciences by the power and advances of modern technology: genome-wide sequencing, metabolomics, and imaging.

In vivo MRS has the unique ability to noninvasively probe IDH mutations by measuring the endogenously produced oncometabolite D-2HG. As an imaging-based technique, it has the benefit of posing minimal risk to the patients, can be performed repeatedly as many times as necessary, and can probe tumor heterogeneity without disturbing the internal milieu. To date, in vivo MRS is the only imaging method that is specific to IDH mutations — existing PET or SPECT radiotracers are not specific (5657), IDH-targeted agents for in vivo molecular imaging do not yet exist, and the prohibitive cost of radiotracers will likely limit their clinical development.
2.1.4.4 Hypoxia promotes IDH-dependent carboxylation of α-KG to citrate to support cell growth and viability

DR Wise, PS Ward, JES Shay, JR Cross, Joshua J Grube, et al.
PNAS | Dec 6, 2011; 108(49):19611–19616
http://www.pnas.org/cgi/doi/10.1073/pnas.1117773108

Citrate is a critical metabolite required to support both mitochondrial bioenergetics and cytosolic macromolecular synthesis. When cells proliferate under normoxic conditions, glucose provides the acetyl-CoA that condenses with oxaloacetate to support citrate production. Tricarboxylic acid (TCA) cycle anaplerosis is maintained primarily by glutamine. Here we report that some hypoxic cells are able to maintain cell proliferation despite a profound reduction in glucose-dependent citrate production. In these hypoxic cells, glutamine becomes a major source of citrate. Glutamine-derived α-ketoglutarate is reductively carboxylated by the NADPH-linked mitochondrial isocitrate dehydrogenase (IDH2) to form isocitrate, which can then be isomerized to citrate. The increased IDH2-dependent carboxylation of glutamine-derived α-ketoglutarate in hypoxia is associated with a concomitantincreased synthesisof2-hydroxyglutarate (2HG) in cells with wild-type IDH1 and IDH2. When either starved of glutamine or rendered IDH2-deficient by RNAi, hypoxic cells areunable toproliferate.The reductive carboxylation ofglutamine is part of the metabolic reprogramming associated with hypoxia-inducible factor 1 (HIF1), as constitutive activation of HIF1 recapitulates the preferential reductive metabolism of glutamine derived α-ketoglutarate even in normoxic conditions. These data support a role for glutamine carboxylation in maintaining citrate synthesis and cell growth under hypoxic conditions.

Citrate plays a critical role at the center of cancer cell metabolism. It provides the cell with a source of carbon for fatty acid and cholesterol synthesis (1). The breakdown of citrate by ATP-citrate lyase is a primary source of acetyl-CoA for protein acetylation (2). Metabolism of cytosolic citrate by aconitase and IDH1 can also provide the cell with a source of NADPH for redox regulation and anabolic synthesis. Mammalian cells depend on the catabolism of glucose and glutamine to fuel proliferation (3). In cancer cells cultured at atmospheric oxygen tension (21% O2), glucose and glutamine have both been shown to contribute to the cellular citrate pool, with glutamine providing the major source of the four-carbon molecule oxaloacetate and glucose providing the major source of the two-carbon molecule acetyl-CoA (4, 5). The condensation of oxaloacetate and acetyl-CoA via citrate synthase generates the 6 carbon citrate molecule. However, both the conversion of glucose-derived pyruvate to acetyl-CoA by pyruvate dehydrogenase (PDH) and the conversion of glutamine to oxaloacetate through the TCA cycle depend on NAD+, which can be compromised under hypoxic conditions. This raises the question of how cells that can proliferate in hypoxia continue to synthesize the citrate required for macromolecular synthesis.

This question is particularly important given that many cancers and stem/progenitor cells can continue proliferating in the setting of limited oxygen availability (6, 7). Louis Pasteur first highlighted the impact of hypoxia on nutrient metabolism based on his observation that hypoxic yeast cells preferred to convert glucose into lactic acid rather than burning it in an oxidative fashion. The molecular basis forthis shift in mammalian cells has been linked to the activity of the transcription factor HIF1 (8–10). Stabilization of the labile HIF1α subunit occurs in hypoxia. It can also occur in normoxia through several mechanisms including loss of the von Hippel-Lindau tumor suppressor (VHL), a common occurrence in renal carcinoma(11). Although hypoxia and/or HIF1α stabilization is a common feature of multiple cancers, to date the source of citrate in the setting of hypoxia or HIF activation has not been determined. Here, we study the sources of hypoxic citrate synthesis in a glioblastoma cell line that proliferates in profound hypoxia (0.5% O2). Glucose uptake and conversion to lactic acid increased in hypoxia. However, glucose conversion into citrate dramatically declined. Glutamine consumption remained constant in hypoxia, and hypoxic cells were addicted to the use of glutamine in hypoxia as a source of α-ketoglutarate. Glutamine provided the major carbon source for citrate synthesis during hypoxia. However, the TCA cycle-dependent conversion of glutamine into citric acid was significantly suppressed. In contrast, there was a relative increase in glutamine-dependent citrate production in hypoxia that resulted from carboxylation of α-ketoglutarate. This reductive synthesis required the presence of mitochondrial isocitrate dehydrogenase 2 (IDH2). In confirmation of the reverse flux through IDH2, the increased reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia was associated with increased synthesis of 2HG. Finally, constitutive HIF1α-expressing cells also demonstrated significant reductive carboxylation-dependent synthesis of citrate in normoxia and a relative defect in the oxidative conversion of glutamine into citrate. Collectively, the data demonstrate that mitochondrial glutaminemetabolismcanbereroutedthroughIDH2-dependent citrate synthesis in support of hypoxic cell growth.

Some Cancer Cells Can Proliferate at 0.5% O2 Despite a Sharp Decline in Glucose-Dependent Citrate Synthesis. At 21% O2, cancer cells have been shown to synthesize citrate by condensing glucose-derived acetyl-CoA with glutamine-derived oxaloacetate through the activity of the canonical TCA cycle enzyme citrate synthase (4). In contrast, less is known regarding the synthesis of citrate by cells that can continue proliferating in hypoxia. The glioblastoma cellline SF188 is able to proliferate at 0.5% O2 (Fig.1A),a level of hypoxia that is sufficient to stabilize HIF1α (Fig. 1B) and predicted to limit respiration (12, 13). Consistent with previous observations in hypoxic cells, we found that SF188 cells demonstrated increased lactate production when incubated in hypoxia
(Fig. 1C), and the ratio of lactate produced to glucose consumed increased demonstrating an increase in the rate of anaerobic glycolysis. When glucose-derived carbon in the form of pyruvate is converted to lactate, it is diverted away from subsequent metabolism that can contribute to citrate production. However, we observed that SF188 cells incubated in hypoxia maintain their intracellular citrate to ∼75% of the level maintained under normoxia (Fig. 1D). This prompted an investigation of how proliferating cells maintain citrate production under hypoxia. Increased glucose uptake and glycolytic metabolism are critical elements of the metabolic response to hypoxia. To evaluate the contributions made by glucose to the citrate pool under normoxia or hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 10 mM [U-13C] glucose. Following a 4-h labeling period, cellular metabolites were extracted and analyzed for isotopic enrichment.

Fig. 1. SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis. (A) SF188 cells were plated in complete medium equilibrated with 21% O2 (Normoxia) or 0.5% O2 (Hypoxia), total viable cells were counted 24 h and 48 h later (Day 1 and Day 2), and population doublings were calculated. Data are the mean ± SEM of four independent experiments. (B) Western blot demonstrates stabilized HIF1α protein in cells cultured in hypoxia compared with normoxia. (C) Cells were grown in normoxia or hypoxia for 24 h, after which culture medium was collected. Medium glucose and lactate levels were measured and compared with the levels in fresh medium. (D) Cells were cultured for 24 h as in C. Intracellular metabolism was then quenched with 80% MeOH prechilled to −80 °C that was spiked with a 13C-labeled citrate as an internal standard. Metabolites were then extracted, and intracellular citrate levels were analyzed with GC-MS and normalized to cell number. Data for C and D are the mean ± SEM of three independent experiments. (E) Model depicting the pathway for cit+2 production from [U-13C] glucose. Glucose uniformly 13Clabeled will generate pyruvate+3. Pyruvate+3 can be oxidatively decarboxylated by PDH to produce acetyl-CoA+2, which can condense with unlabeled oxaloacetate to produce cit+2. (F) Cells were cultured for 24 h as in C and D, followed by an additional 4 h of culture in glucose-deficient medium supplemented with 10 mM [U-13C]glucose. Intracellular metabolites were then extracted, and 13C-enrichment in cellular citrate was analyzed by GCMS and normalized to the total citrate pool size. Data are the mean ± SD of three independent cultures from a representative of two independent experiments. *P < 0.05, ***P < 0.001

Fig. 2. Glutamine carbon is required for hypoxic cell viability and contributes to increased citrate production through reductive carboxylation relative to oxidative metabolism in hypoxia. (A) SF188 cells were cultured for 24 h in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia). Culture medium was then removed from cells and analyzed for glutamine levels which were compared with the glutamine levels in fresh medium. Data are the mean ± SEM of three independent experiments. (B) The requirement for glutamine to maintain hypoxic cell viability can be satisfied by α-ketoglutarate. Cells were cultured in complete medium equilibrated with 0.5% O2 for 24 h, followed by an additional 48 h at 0.5% O2 in either complete medium (+Gln), glutamine-deficient medium (−Gln), or glutamine-deficient medium supplemented with 7 mM dimethyl α-ketoglutarate (−Gln +αKG). All medium was preconditioned in 0.5% O2. Cell viability was determined by trypan blue dye exclusion. Data are the mean and range from two independent experiments. (C) Model depicting the pathways for cit+4 and cit+5 production from [U-13C]glutamine (glutamine+5). Glutamine+5 is catabolized to α-ketoglutarate+5, which can then contribute to citrate production by two divergent pathways. Oxidative metabolism produces oxaloacetate+4, which can condense with unlabeled acetyl-CoA to produce cit+4. Alternatively, reductive carboxylation produces isocitrate+5, which can isomerize to cit+5. (D) Glutamine contributes to citrate production through increased reductive carboxylation relative to oxidative metabolism in hypoxic proliferating cancer cells. Cells were cultured for 24 h as in A, followed by 4 h of culture in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in cellular citrate was quantitated with GC-MS. Data are the mean ± SD of three independent cultures from a representative of three independent experiments. **P < 0.01.

Fig. 3. Cancer cells maintain production of other metabolites in addition to citrate through reductive carboxylation in hypoxia. (A) SF188 cells were cultured in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia) for 24 h. Intracellular metabolism was then quenched with 80% MeOH prechilled to −80 °C that was spiked with a 13C-labeled citrate as an internal standard. Metabolites were extracted, and intracellular aspartate (asp), malate (mal), and fumarate (fum) levels were analyzed with GC-MS. Data are the mean± SEM of three independent experiments. (B) Model for the generation of aspartate, malate, and fumarate isotopomers from [U-13C] glutamine (glutamine+5). Glutamine+5 is catabolized to α-ketoglutarate+5. Oxidative metabolism of α-ketoglutarate+5 produces fumarate+4, malate+4, and oxaloacetate (OAA)+4 (OAA+ 4 is in equilibrium with aspartate+4 via transamination). Alternatively, α-ketoglutarate+5 can be reductively carboxylated to generate isocitrate+5 and citrate+5. Cleavage of citrate+5 in the cytosol by ATP-citrate lyase (ACL) will produce oxaloacetate+3 (in equilibrium with aspartate+3). Oxaloacetate+3 can be metabolized to malate+3 and fumarate+3. (C) SF188 cells were cultured for 24 h as in A, and then cultured for an additional 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C] glutamine. 13C enrichment in cellular aspartate, malate, and fumarate was determined by GC-MS and normalized to the relevant metabolite total pool size. Data shown are the mean ± SD of three independent cultures from a representative of three independent experiments. **P < 0.01, ***P < 0.001.

Glutamine Carbon Metabolism Is Required for Viability in Hypoxia. In addition to glucose, we have previously reported that glutamine can contribute to citrate production during cell growth under normoxic conditions (4). Surprisingly, under hypoxic conditions, we observed that SF188 cells retained their high rate of glutamine consumption (Fig. 2A). Moreover, hypoxic cells cultured in glutamine-deficient medium displayed a significant loss of viability (Fig. 2B). In normoxia, the requirement for glutamine to maintain viability of SF188 cells can be satisfied by α-ketoglutarate, the downstream metabolite of glutamine that is devoid of nitrogenous groups (14). α-ketoglutarate cannot fulfill glutamine’s roles as a nitrogen source for nonessential amino acid synthesis or as an amide donor for nucleotide or hexosamine synthesis, but can be metabolized through the oxidative TCA cycle to regenerate oxaloacetate, and subsequently condense with glucose-derived acetyl-CoA to produce citrate. To test whether the restoration of carbon from glutamine metabolism in the form of α-ketoglutarate could rescue the viability defect of glutamine-starved SF188 cells even under hypoxia, SF188 cells incubated in hypoxia were cultured in glutamine-deficient medium supplemented with a cell-penetrant form of α-ketoglutarate (dimethyl α-ketoglutarate). The addition of dimethyl α-ketoglutarate rescued the defect in cell viability observed upon glutamine withdrawal (Fig. 2B). These data demonstrate that, even under hypoxic conditions, when the ability of glutamine to replenish oxaloacetate through oxidative TCA cycle metabolism is diminished, SF188 cells retain their requirement for glutamine as the carbon backbone for α-ketoglutarate. This result raised the possibility that glutamine could be the carbon source for citrate production through an alternative, nonoxidative, pathway in hypoxia.

Cells Proliferating in Hypoxia Preferentially Produce Citrate Through Reductive Carboxylation Rather than Oxidative Metabolism. To distinguish the pathways by which glutamine carbon contributes to citrate production in normoxia and hypoxia, SF188 cells were incubated in normoxia or hypoxia and cultured in medium containing 4 mM [U-13C] glutamine. After 4 h of labeling, intracellular metabolites were extracted and analyzed by GC-MS. In normoxia,the cit+4 pool constituted the majority of the enriched citrate in the cell. Cit+4 arises from the oxidative metabolism of glutamine-derived α-ketoglutarate+5 to oxaloacetate+4 and its subsequent condensation with unenriched, glucose-derived acetyl-CoA (Fig.2C and D). Cit+5 constituted a significantly smaller pool than cit+4 in normoxia. Conversely, in hypoxia, cit+5 constituted the majority of the enriched citrate in the cell. Cit+5 arises from the reductive carboxylation of glutamine-derived α-ketoglutarate+5 to isocitrate+5, followed by the isomerization of isocitrate+5 to cit+5 by aconitase. The contribution of cit+4 to the total citrate pool was significantly lower in hypoxia than normoxia, and the accumulation of other enriched citrate species in hypoxia remained low. These data support the role of glutamine as a carbon source for citrate production in normoxia and hypoxia.

Cells Proliferating in Hypoxia Maintain Levels of Additional Metabolites Through Reductive Carboxylation. Previous work has documented that, in normoxic conditions, SF188 cells use glutamine as the primary anaplerotic substrate, maintaining the pool sizes of TCA cycle intermediates through oxidative metabolism (4). Surprisingly, we found that, when incubated in hypoxia, SF188 cells largely maintained their levels of aspartate (in equilibrium with oxaloacetate), malate, and fumarate (Fig. 3A). To distinguish how glutamine carbon contributes to these metabolites in normoxia and hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 4 mM [U-13C] glutamine. After a 4-h labeling period, metabolites were extracted and the intracellular pools of aspartate, malate, and fumarate were analyzed by GC-MS. In normoxia, the majority of the enriched intracellular asparatate, malate, and fumarate were the +4 species, which arise through oxidative metabolism of glutamine-derived α-ketoglutarate (Fig. 3 B and C). The +3 species, which can be derived from the citrate generated by the reductive carboxylation of glutamine derived α-ketoglutarate, constituted a significantly lower percentage of the total aspartate, malate, and fumarate pools. By contrast, in hypoxia, the +3 species constituted a larger percentage of the total aspartate, malate, and fumarate pools than they did in normoxia. These data demonstrate that, in addition to citrate, hypoxic cells preferentially synthesize oxaloacetate, malate, and fumarate through the pathway of reductive carboxylation rather than the oxidative TCA cycle.

IDH2 Is Critical in Hypoxia for Reductive Metabolism of Glutamine and for Cell Proliferation.We hypothesized that the relative increase in reductive carboxylation we observed in hypoxia could arise from the suppression of α-ketoglutarate oxidation through the TCA cycle. Consistent with this, we found that α-ketoglutarate levels increased in SF188 cells following 24 h in hypoxia (Fig. 4A). Surprisingly, we also found that levels of the closely related metabolite 2-hydroxyglutarate (2HG) increased in hypoxia, concomitant with the increase in α-ketoglutarate under these conditions. 2HG can arise from the noncarboxylating reduction of α-ketoglutarate (Fig. 4B). Recent work has found that specific cancer-associated mutations in the active sites of either IDH1 or IDH2 lead to a 10- to 100-fold enhancement in this activity facilitating 2HG production (15–17), but SF188 cells lack IDH1/2 mutations. However, 2HG levels are also substantially elevated in the inborn error of metabolism 2HG aciduria, and the majority of patients with this disease lack IDH1/2 mutations. As 2HG has been demonstrated to arise in these patients from mitochondrial α-ketoglutarate (18), we hypothesized that both the increased reductive carboxylation of glutamine-derived α-ketoglutarate to citrate and the increased 2HG accumulation we observed in hypoxia could arise from increased reductive metabolism by wild-type IDH2 in the mitochondria.

Fig. 4. Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2. (A) α-ketoglutarate and 2HG increase in hypoxia. SF188 cells were cultured in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia) for 24 h. Intracellular metabolites were then extracted, cell extracts spiked with a 13C-labeled citrate as an internal standard, and intracellular α-ketoglutarate and 2HG levels were analyzed with GC-MS. Data shown are the mean ± SEM of three independent experiments. (B) Model for reductive metabolism from glutamine-derived α-ketoglutarate. Glutamine+5 is catabolized to α-ketoglutarate+5. Carboxylation of α-ketoglutarate+5 followed by reduction of the carboxylated intermediate (reductive carboxylation) will produce isocitrate+5, which can then isomerize to cit+5. In contrast, reductive activity on α-ketoglutarate+5 that is uncoupled from carboxylation will produce 2HG+5. (C) IDH2 is required for reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia. SF188 cells transfected with a siRNA against IDH2 (siIDH2) or nontargeting negative control (siCTRL) were cultured for 2 d in complete medium equilibrated with 0.5% O2.(Upper) Cells were then cultured at 0.5% O2 for an additional 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in intracellular citrate and 2HG was determined and normalized to the relevant metabolite total pool size. (Lower) Cells transfected and cultured in parallel at 0.5% O2 were counted by hemocytometer (excluding nonviable cells with trypan blue staining) or harvested for protein to assess IDH2 expression by Western blot. Data shown for GC-MS and cell counts are the mean ± SD of three independent cultures from a representative experiment. **P < 0.01, ***P < 0.001.

Reprogramming of Metabolism by HIF1 in the Absence of Hypoxia Is Sufficient to Induce Increased Citrate Synthesis by Reductive Carboxylation Relative to Oxidative Metabolism. The relative increase in the reductive metabolism of glutamine-derived α-ketoglutarate at 0.5% O2 may be explained by the decreased ability to carry out oxidative NAD+-dependent reactions as respiration is inhibited (12, 13). However, a shift to preferential reductive glutamine metabolism could also result from the active reprogramming of cellular metabolism by HIF1 (8–10), which inhibits the generation of mitochondrial acetyl-CoA necessary for the synthesis of citrate by oxidative glucose and glutamine metabolism (Fig. 5A). To better understand the role of HIF1 in reductive glutamine metabolism, we used VHL-deficient RCC4 cells, which display constitutive expression of HIF1α under normoxia (Fig. 5B).

Fig. 5. Reprogramming of metabolism by HIF1 in the absence of hypoxia is sufficient to induce reductive carboxylation of glutamine-derived α-ketoglutarate. (A) Model depicting how HIF1 signaling’s inhibition of pyruvate dehydrogenase (PDH) activity and promotion of lactate dehydrogenase-A (LDH-A) activity can block the generation of mitochondrial acetyl-CoA from glucose-derived pyruvate, thereby favoring citrate synthesis from reductive carboxylation of glutamine-derived α-ketoglutarate. (B) Western blot demonstrating HIF1α protein in RCC4 VHL−/− cells in normoxia with a nontargeting shRNA (shCTRL), and the decrease in HIF1α protein in RCC4 VHL−/− cells stably expressing HIF1α shRNA (shHIF1α). (C) HIF1-induced reprogramming of glutamine metabolism. Cells from B at 21% O2 were cultured for 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. Intracellular metabolites were then extracted, and 13C enrichment in cellular citrate was determined by GC-MS. Data shown are the mean ± SD of three independent cultures from a representative of three independent experiments. ***P < 0.001.

Compared with glucose metabolism, much less is known regarding how glutamine metabolism is altered under hypoxia. It has also remained unclear how hypoxic cells can maintain the citrate production necessary for macromolecular biosynthesis. In this report, we demonstrate that in contrast to cells at 21% O2, where citrate is predominantly synthesized through oxidative metabolism of both glucose and glutamine, reductive carboxylation of glutamine carbon becomes the major pathway of citrate synthesis in cells that can effectively proliferate at 0.5% O2. Moreover, we show that in these hypoxic cells, reductive carboxylation of glutamine-derived α-ketoglutarate is dependent on mitochondrial IDH2. Although others have previously suggested the existence of reductive carboxylation in cancer cells (19, 20), these studies failed to demonstrate the intracellular localization or specific IDH isoform responsible for the reductive carboxylation flux. Recently, we identified IDH2 as an isoform that contributes to reductive carboxylation in cancer cells incubated at 21% O2 (16), but remaining unclear were the physiological importance and regulation of this pathway relative to oxidative metabolism, as well as the conditions where this reductive pathway might be advantageous for proliferating cells. Here we report that IDH2-mediated reductive carboxylation of glutamine-derived α-ketoglutarate to citrate is an important feature of cells proliferating in hypoxia. Moreover, the reliance on reductive glutamine metabolism can be recapitulated in normoxia by constitutive HIF1 activation in cells with loss of VHL. The mitochondrial NADPH/NADP+ ratio required to fuel the reductive reaction through IDH2 can arise from the increased NADH/NAD+ ratio existing in the mitochondria under hypoxic conditions (21, 22), with the transfer of electrons from NADH to NADP+ to generate NADPH occurring through the activity of the mitochondrial transhydrogenase (23).

In further support of the increased mitochondrial reductive glutamine metabolism that we observe in hypoxia, we report here that incubation in hypoxia can lead to elevated 2HG levels in cells lacking IDH1/2 mutations. 2HG production from glutamine-derived α-ketoglutarate significantly decreased with knockdown of IDH2, supporting the conclusion that 2HG is produced in hypoxia by enhanced reverse flux of α-ketoglutarate through IDH2in a truncated, noncarboxylating reductive reaction. However,other mechanisms may also contribute to 2HG elevation in hypoxia. These include diminished oxidative activity and/or enhanced reductive activity of the 2HG dehydrogenase, a mitochondrial enzyme that normally functions to oxidize 2HG back to α-ketoglutarate (25). The level of 2HG elevation we observe in hypoxic cells is associated with a concomitant increase in α-ketoglutarate, and is modest relative to that observed in cancers with IDH1/2 gain-of-function mutations. Nonetheless, 2HG elevation resulting from hypoxia in cells with wild-type IDH1/2 may hold promise as a cellular or serum biomarker for tissues undergoing chronic hypoxia and/or excessive glutamine metabolism.

2.1.4.5 IDH mutation impairs histone demethylation and results in a block to cell differentiation.

C Lu, PS Ward, GS Kapoor, D Rohle, S Turcan, et al.
Nature 483, 474–478 (22 Mar 2012)
http://dx.doi.org:/10.1038/nature10860

Recurrent mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 have been identified in gliomas, acute myeloid leukaemias (AML) and chondrosarcomas, and share a novel enzymatic property of producing 2-hydroxyglutarate (2HG) from α-ketoglutarate1, 2, 3, 4, 5, 6. Here we report that 2HG-producing IDH mutants can prevent the histone demethylation that is required for lineage-specific progenitor cells to differentiate into terminally differentiated cells. In tumour samples from glioma patients, IDH mutations were associated with a distinct gene expression profile enriched for genes expressed in neural progenitor cells, and this was associated with increased histone methylation. To test whether the ability of IDH mutants to promote histone methylation contributes to a block in cell differentiation in non-transformed cells, we tested the effect of neomorphic IDH mutants on adipocyte differentiation in vitro. Introduction of either mutant IDH or cell-permeable 2HG was associated with repression of the inducible expression of lineage-specific differentiation genes and a block to differentiation. This correlated with a significant increase in repressive histone methylation marks without observable changes in promoter DNA methylation. Gliomas were found to have elevated levels of similar histone repressive marks. Stable transfection of a 2HG-producing mutant IDH into immortalized astrocytes resulted in progressive accumulation of histone methylation. Of the marks examined, increased H3K9 methylation reproducibly preceded a rise in DNA methylation as cells were passaged in culture. Furthermore, we found that the 2HG-inhibitable H3K9 demethylase KDM4C was induced during adipocyte differentiation, and that RNA-interference suppression of KDM4C was sufficient to block differentiation. Together these data demonstrate that 2HG can inhibit histone demethylation and that inhibition of histone demethylation can be sufficient to block the differentiation of non-transformed cells.

Figure 1: IDH mutations are associated with dysregulation of glial differentiation and global histone methylation.

http://www.nature.com/nature/journal/v483/n7390/carousel/nature10860-f1.2.jpg

Figure 2: Differentiation arrest induced by mutant IDH or 2HG is associated with increased global and promoter-specific H3K9 and H3K27 methylation.

http://www.nature.com/nature/journal/v483/n7390/carousel/nature10860-f2.2.jpg

Figure 3: IDH mutation induces histone methylation increase in CNS-derived cells and can alter cell lineage gene expression.

http://www.nature.com/nature/journal/v483/n7390/carousel/nature10860-f3.2.jpg
2.1.4.6 Isocitrate dehydrogenase mutations in leukemia

McKenney AS, Levine RL.
J Clin Invest. 2013 Sep; 123(9):3672-7
http://dx.doi.org:/1172/JCI67266

Recent genome-wide discovery studies have identified a spectrum of mutations in different malignancies and have led to the elucidation of novel pathways that contribute to oncogenic transformation. The discovery of mutations in the genes encoding isocitrate dehydrogenase (IDH) has uncovered a critical role for altered metabolism in oncogenesis, and the neomorphic, oncogenic function of IDH mutations affects several epigenetic and gene regulatory pathways. Here we discuss the relevance of IDH mutations to leukemia pathogenesis, therapy, and outcome and how mutations in IDH1 and IDH2 affect the leukemia epigenome, hematopoietic differentiation, and clinical outcome.

Mutations in isocitrate dehydrogenase (IDH) have been identified in a spectrum of human malignancies. Mutations in IDH1 were first identified in an exome resequencing analysis of patients with colorectal cancer (1). Shortly thereafter, recurrent IDH1 and IDH2 mutations were found in patients with glioma, most commonly in patients who present with lower-grade gliomas (2). IDH1 mutations were subsequently discovered in patients with acute myeloid leukemia (AML) through whole genome sequencing (3), which was followed by the identification of somatic IDH2 mutations in patients with AML (46). Further studies revealed that IDH mutations induce a neomorphic function to produce the oncometabolite 2-hydroxyglutarate (2HG) (78), which can inhibit many cellular processes (910). In particular, the ability of 2HG to alter the epigenetic landscape makes IDH a prototypical target for prognostic studies and drug targeting in leukemias.

IDH proteins catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (αKG, also known as 2-oxoglutarate). IDH3 primarily functions as the allosterically regulated, rate-limiting enzymatic step in the TCA cycle, while the other two isoforms, which are mutated in cancer, utilize this catalytic process in additional contexts including metabolism and glucose sensing (IDH1) and regulation of oxidative respiration (IDH2) (1112). Loss-of-function mutations in other TCA cycle components have previously been identified in other types of cancer, specifically in mutations in fumarate hydratase (FH) and succinate dehydrogenase (SDH). As such, many hypothesized that IDH1/2 mutations would result in loss of metabolic activity, and indeed, enzymatic studies confirmed that the mutant protein’s ability to perform its native function is markedly attenuated, as measured by reduced production of αKG or NADPH (1314).

However, the genetic data relating to these mutations were more consistent with gain-of-function mutation: all of the observed alterations are somatic, heterozygous mutations that occur at highly conserved positions, which appear to be functionally equivalent between different isoforms. This discrepancy was resolved when metabolic profiling showed that the IDH1 mutant protein catalyzes a neomorphic reaction that converts αKG to 2HG. 2HG can be detected at high levels in gliomas harboring these mutations (4), and the accumulation of 2HG was further found to be common to oncogenic IDH mutations (8). This finding indicated that 2HG may serve as a potential functional biomarker of IDH mutation, and later, metabolomics analysis of 2HG content in patient samples led to the identification of IDH2 mutations in leukemias (6). IDH mutant proteins have been proposed to form a heterodimer with the remaining wild-type IDH isoform (7814), which is consistent with genetic data showing retention of the wild-type allele in IDH-mutant cancers.

The discovery of the neomorphic function of IDH opened the doors for true investigation into the implications of these mutations and the resultant intracellular accumulation of 2HG. 2HG is thought to competitively inhibit the activity of a broad spectrum of αKG-dependent enzymes with known and postulated roles in oncogenic transformation. Some targets, such as the prolyl 4-hydroxylases, have unclear implications in leukemia pathogenesis. However, the recent demonstration that alterations in epigenetic factors occur in the majority of acute leukemias led to investigations of the effects of 2HG on the jumonji C domain histone-modifying enzymes and the newly characterized tet methylcytosine dioxygenase (TET) family of methylcytosine hydroxylases. Importantly, expression of IDH or exposure to chemically modified, cell-permeable 2HG affects hematopoietic differentiation, likely due to changes in epigenetic regulation that induce reversible alterations in differentiation states (15).

TET1 was initially discovered as a binding partner of mixed-lineage leukemia (MLL) in patients with MLL-translocated AML (1617). However, the function of the TET gene family and its role in leukemogenesis remained unknown until TET1 was shown to catalyze αKG-dependent addition of a hydroxyl group to methylated cytosines (18), which precedes DNA demethylation and results in altered epigenetic control (10,1824). TET enzymes have further been shown to catalyze conversion of 5-methylcytosine (5mC) to 5-formylcytosine (5fC) or 5-carboxylcytosine (5cC) (2526). These data suggest that loss of TET2 enzymatic function can lead to aberrant cytosine methylation and epigenetic silencing in malignant settings. TET2mutations were initially found in array-comparative genomic hybridization and genome-wide SNP arrays, which identified microdeletions containing this gene in a patient with myeloproliferative neoplasm (MPN) and myelodysplastic syndrome (MDS) (27). This discovery was followed by the identification of somatic missense, nonsense, and frameshift TET2 mutations in patients with MDS, MPN, AML, and other myeloid malignancies (2730). Most TET2 alleles result in nonsense/frameshift mutations, which result in loss of TET2 catalytic function (31), consistent with a tumor suppressor function in myeloid malignancies.

When 2HG was hypothesized to affect specific enzymatic processes in oncogenesis, AML patients were observed to harbor IDH1/2 and TET mutations in a mutually exclusive manner (9). Of note, exploration into the functional relationship between these mutant IDH proteins and the function of TET2 ultimately suggested a role for 2HG in inhibiting TET enzymatic function. IDH- or TET2-mutant patient samples are characterized by increased global hypermethylation of DNA and transcriptional silencing of genes with hypermethylated promoters. Expression of these IDH-mutant alleles in experimental models was further observed to result in increased methylation, reduced hydroxymethylation, and impaired TET2 function (9). Finally, in biochemical assays, 2HG was shown to directly inhibit TET2 as well as other αKG-dependent enzymes (10). These data demonstrate that a key feature of IDH1/2 mutations in hematopoietic cells is to impair TET2 function and disrupt DNA methylation (​Figure1).

Figure 1 Normal IDH functions to convert isocitrate to αKG in the Krebs cycle.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3754251/bin/JCI67266.f1.gif

mutations have been observed with IDH1_2 mutations leukemias

mutations have been observed with IDH1_2 mutations leukemias

Many mutations have been observed in conjunction with IDH1/2 mutations in different types of leukemia.

In de novo adult AML, these mutations should be observed in the context of other prognostic indicators such as CEBPA, NPM1, and DNMT3A mutation. In AML that progresses from MPN, IDH1/2 mutations can be examined separately from the mutations responsible for MPN (such as JAK2 or MPL mutations) using paired pre- and post-transformation samples. Evidence supports a role for IDH1/2 hotspot mutations in leukemic transformation.

http://www.ncbi.nlm.nih.gov/pmc/articles/instance/3754251/bin/JCI67266.f2.gif

Conditional loss of Tet2 expression in mice results in a chronic myelomonocytic leukemia (CMML) phenotype and in increased hematopoietic self-renewal in vivo (32). Of note, in vitro systems have shown that TET2 silencing and expression of IDH1/2 mutant alleles leads to impaired hematopoietic differentiation and expansion of stem/progenitor cells (9). More recently, IDH1 (R132H) conditional knockin mice with hematopoietic-specific recombination were analyzed and found to have myeloid expansion, although they did not develop overt AML. This suggests that IDH mutations by themselves cannot promote overt transformation, and that additional genetic, epigenetic, and/or microenvironmental factors are needed to cooperate with mutant IDH alleles to promote hematologic malignancies. The hematopoietic defects included increased numbers of hematopoietic stem cells and myeloid progenitor cells, and a DNA methylation signature that was similar to observed patterns in primary AML patients with IDH1 mutations (33). While many models of IDH-mutant leukemia have shown potential, future models that incorporate the complexity seen in human patients are needed, as discussed below. More recently, the effects of IDH1/2 mutations on hematopoietic cell lines were replicated using exogenously applied 2HG, which was rendered permeable to the cell membrane by esterification. The Kaelin group used this system to dissect the role of 2HG in the αKG-dependent pathways that may be affected in IDH mutation, and to show that the effects are reversible (34). Tools such as these will help advance our understanding of the biology of IDH mutations and, by extension, the potential therapies that may affect mutant IDH and the downstream pathways. Indeed, given the recent description of mutant-selective IDH1/2 inhibitors (3437), the development of genetically accurate models of IDH mutant–mediated leukemogenesis will be critical to evaluate the effects of targeted therapies in mice with AML and subsequently in the clinical context.

2.1.4.7 The Common Feature of Leukemia-Associated IDH1 and IDH2 Mutations – a Neomorphic Enzyme Activity Converting α-Ketoglutarate to 2-Hydroxyglutarate

PS Ward, J Patel, DR Wise, O Abdel-Wahab, BD Bennett, HA Coller, et al.
Cancer Cell 2010 Mar 16; 17(3):225–234
http://dx.doi.org/10.1016/j.ccr.2010.01.020

Highlights

  • All IDH mutations reported in cancer share a common neomorphic enzymatic activity
  • Both wild-type IDH1 and IDH2 are required for cell proliferation
  • IDH2 R140Q mutations occur in 9% of AML cases
  • Overall, IDH2 mutations appear more common than IDH1 mutations in AML

 

Summary

The somatic mutations in cytosolic isocitrate dehydrogenase 1 (IDH1) observed in gliomas can lead to the production of 2-hydroxyglutarate (2HG). Here, we report that tumor 2HG is elevated in a high percentage of patients with cytogenetically normal acute myeloid leukemia (AML). Surprisingly, less than half of cases with elevated 2HG possessed IDH1 mutations. The remaining cases with elevated 2HG had mutations in IDH2, the mitochondrial homolog of IDH1. These data demonstrate that a shared feature of all cancer-associated IDH mutations is production of the oncometabolite 2HG. Furthermore, AML patients with IDH mutations display a significantly reduced number of other well characterized AML-associated mutations and/or associated chromosomal abnormalities, potentially implicating IDH mutation in a distinct mechanism of AML pathogenesis.

Significance

Most cancer-associated enzyme mutations result in either catalytic inactivation or constitutive activation. Here we report that the common feature of IDH1 and IDH2 mutations observed in AML and glioma is the acquisition of an enzymatic activity not shared by either wild-type enzyme. The product of this neomorphic enzyme activity can be readily detected in tumor samples, and we show that tumor metabolite analysis can identify patients with tumor-associated IDH mutations. Using this method, we discovered a 2HG-producing IDH2 mutation, IDH2 R140Q, that was present in 9% of serial AML samples. Overall, IDH1 and IDH2 mutations were observed in over 23% of AML patients.

Mutations in human cytosolic isocitrate dehydrogenase I (IDH1) occur somatically in > 70% of grade II-III gliomas and secondary glioblastomas, and in 8.5% of acute myeloid leukemias (AML) (Mardis et al., 2009 and Yan et al., 2009). Mutations have also been reported in cancers of the colon and prostate (Kang et al., 2009 and Sjoblom et al., 2006). To date, all reported IDH1 mutations result in an amino acid substitution at a single arginine residue in the enzyme’s active site, R132. A subset of intermediate grade gliomas lacking mutations in IDH1 has been found to harbor mutations in IDH2, the mitochondrial homolog of IDH1. The IDH2 mutations that have been identified in gliomas occur at the analogous residue to IDH1 R132, IDH2 R172. Both IDH1 R132 and IDH2 R172 mutants lack the wild-type enzyme’s ability to convert isocitrate to α-ketoglutarate (Yan et al., 2009). To date, all reported IDH1 or IDH2 mutations are heterozygous, with the cancer cells retaining one wild-type copy of the relevant IDH1 or IDH2 allele. No patient has been reported with both an IDH1 and IDH2 mutation. These data argue against the IDH mutations resulting in a simple loss of function.

Normally both cytosolic IDH1 and mitochondrial IDH2 exist as homodimers within their respective cellular compartments, and the mutant proteins retain the ability to bind to their respective wild-type partner. Therefore, it has been proposed that mutant IDH1 can act as a dominant negative against wild-type IDH1 function, resulting in a decrease in cytosolic α-ketoglutarate levels and leading to an indirect activation of the HIF-1α pathway (Zhao et al., 2009). However, recent work has provided an alternative explanation. The R132H IDH1 mutation observed in gliomas was found to display a gain of function for the NADPH-dependent reduction of α-ketoglutarate to R(–)-2-hydroxyglutarate (2HG) ( Dang et al., 2009). This in vitro activity was confirmed when 2HG was found to be elevated in IDH1-mutated gliomas. Whether this neomorphic activity is a common feature shared by IDH2 mutations was not determined.

IDH1 R132 mutations identical to those reported to produce 2HG in gliomas were recently reported in AML (Mardis et al., 2009). These IDH1 R132 mutations were observed in 8.5% of AML patients studied, and a significantly higher percentage of mutation was observed in the subset of patients whose tumors lacked cytogenetic abnormalities. IDH2 R172 mutations were not observed in this study. However, during efforts to confirm and extend these findings, we found an IDH2 R172K mutation in an AML sample obtained from a 77-year-old woman. This finding confirmed that both IDH1 and IDH2 mutations can occur in AML and prompted us to more comprehensively investigate the role of IDH2 in AML.

The present study was undertaken to see if IDH2 mutations might share the same neomorphic activity as recently reported for glioma-associated IDH1 R132 mutations. We also determined whether tumor-associated 2HG elevation could prospectively identify AML patients with mutations in IDH. To investigate the lack of reduction to homozygosity for either IDH1 or IDH2 mutations in tumor samples, the ability of wild-type IDH1 and/or IDH2 to contribute to cell proliferation was examined.

IDH2 Is Mutated in AML

A recent study employing a whole-genome sequencing strategy in an AML patient resulted in the identification of somatic IDH1 mutations in AML (Mardis et al., 2009). Based on the report that IDH2 mutations were also observed in the other major tumor type in which IDH1 mutations were implicated (Yan et al., 2009), we sequenced the IDH2 gene in a set of de-identified AML DNA samples. Several cases with IDH2 R172 mutations were identified. In the initial case, the IDH2 mutation found, R172K, was the same mutation reported in glioma samples. It has been recently reported that cancer-associated IDH1 R132 mutants display a loss-of-function for the use of isocitrate as substrate, with a concomitant gain-of-function for the reduction of α-ketoglutarate to 2HG (Dang et al., 2009). This prompted us to determine if the recurrent R172K mutation in IDH2 observed in both gliomas and leukemias might also display the same neomorphic activity. In IDH1, the role of R132 in determining IDH1 enzymatic activity is consistent with the stabilizing charge interaction of its guanidinium moiety with the β-carboxyl group of isocitrate (Figure 1A). This β-carboxyl is critical for IDH’s ability to catalyze the interconversion of isocitrate and α-ketoglutarate, with the overall reaction occurring in two steps through a β-carboxyl-containing intermediate (Ehrlich and Colman, 1976). Proceeding in the oxidative direction, this β-carboxyl remains on the substrate throughout the IDH reaction until the final decarboxylating step which produces α-ketoglutarate.

IDH1 R132 and IDH2 R172 Are Analogous Residues

IDH1 R132 and IDH2 R172 Are Analogous Residues

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Figure 1. IDH1 R132 and IDH2 R172 Are Analogous Residues that Both Interact with the β-Carboxyl of Isocitrate

(A) Active site of crystallized human IDH1 with isocitrate.

(B) Active site of human IDH2 with isocitrate, modeled based on the highly homologous and crystallized pig IDH2 structure. For (A) and (B), carbon 6 of isocitrate containing the β-carboxyl is highlighted in cyan, with remaining isocitrate carbons shown in yellow. Carbon atoms of amino acids (green), amines (blue), and oxygens (red) are also shown. Hydrogen atoms are omitted from the figure for clarity. Dashed lines depict interactions < 3.1 Å, corresponding to hydrogen and ionic bonds. Residues coming from the other monomer of the IDH dimer are denoted with a prime (′) symbol.

To understand how R172 mutations in IDH2 might relate to the R132 mutations in IDH1 characterized for gliomas, we modeled human IDH2 based on the pig IDH2 structure containing bound isocitrate (Ceccarelli et al., 2002). Human and pig IDH2 protein share over 97% identity and all active site residues are identical. The active site of human IDH2 was structurally aligned with human IDH1 (Figure 1). Similar to IDH1, in the active site of IDH2 the isocitrate substrate is stabilized by multiple charge interactions throughout the binding pocket. Moreover, like R132 in IDH1, the analogous R172 in IDH2 is predicted to interact strongly with the β-carboxyl of isocitrate. This raised the possibility that cancer-associated IDH2 mutations at R172 might affect enzymatic interconversion of isocitrate and α-ketoglutarate similarly to IDH1 mutations at R132.

Mutation of IDH2 R172K Enhances α-Ketoglutarate-Dependent NADPH Consumption

To test whether cancer-associated IDH2 R172K mutations shared the gain of function in α-ketoglutarate reduction observed for IDH1 R132 mutations (Dang et al., 2009), we overexpressed wild-type or R172K mutant IDH2 in cells with endogenous wild-type IDH2 expression, and then assessed isocitrate-dependent NADPH production and α-ketoglutarate-dependent NADPH consumption in cell lysates. As reported previously (Yan et al., 2009), extracts from cells expressing the R172K mutant IDH2 did not display isocitrate-dependent NADPH production above the levels observed in extracts from vector-transfected cells. In contrast, extracts from cells expressing a comparable amount of wild-type IDH2 markedly increased isocitrate-dependent NADPH production (Figure 2A). However, when these same extracts were tested for NADPH consumption in the presence of α-ketoglutarate, R172K mutant IDH2 expression was found to correlate with a significant enhancement to α-ketoglutarate-dependent NADPH consumption. Vector-transfected cell lysates did not demonstrate this activity (Figure 2B). Although not nearly to the same degree as with the mutant enzyme, wild-type IDH2 overexpression also reproducibly enhanced α-ketoglutarate-dependent NADPH consumption under these conditions.

Expression of R172K Mutant IDH2 Results in Enhanced α-Ketoglutarate-Dependent Consumption of NADPH

Expression of R172K Mutant IDH2 Results in Enhanced α-Ketoglutarate-Dependent Consumption of NADPH

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Figure 2. Expression of R172K Mutant IDH2 Results in Enhanced α-Ketoglutarate-Dependent Consumption of NADPH

(A) 293T cells transfected with wild-type or R172K mutant IDH2, or empty vector, were lysed and subsequently assayed for their ability to generate NADPH from NADP+ in the presence of 0.1 mM isocitrate.

(B) The same cell lysates described in (A) were assayed for their consumption of NADPH in the presence of 0.5 mM α-ketoglutarate. Data for (A) and (B) are each representative of three independent experiments. Data are presented as the mean and standard error of the mean (SEM) from three independent measurements at the indicated time points.

(C) Expression of wild-type and R172K mutant IDH2 was confirmed by western blotting of the lysates assayed in (A) and (B). Reprobing of the same blot with IDH1 antibody as a control is also shown.

Mutation of IDH2 R172K Results in Elevated 2HG Levels

R172K mutant IDH2 lacks the guanidinium moiety in residue 172 that normally stabilizes β-carboxyl addition in the interconversion of α-ketoglutarate and isocitrate. Yet R172K mutant IDH2 exhibited enhanced α-ketoglutarate-dependent NADPH consumption in cell lysates (Figure 2B). A similar enhancement of α-ketoglutarate-dependent NADPH consumption has been reported for R132 mutations in IDH1, resulting in conversion of α-ketoglutarate to 2HG (Dang et al., 2009). To determine whether cells expressing IDH2 R172K shared this property, we expressed IDH2 wild-type or IDH2 R172K in cells. The accumulation of organic acids, including 2HG, both within cells and in culture medium of the transfectants was then assessed by gas-chromatography mass spectrometry (GC-MS) after MTBSTFA derivatization of the organic acid pool. We observed a metabolite peak eluting at 32.5 min on GC-MS that was of minimal intensity in the culture medium of IDH2-wild-type-expressing cells, but that in the medium of IDH2-R172K-expressing cells had a markedly higher intensity approximating that of the glutamate signal (Figures 3A and 3B). Mass spectra of this metabolite peak fit that predicted for MTBSTFA-derivatized 2HG, and the peak’s identity as 2HG was additionally confirmed by matching its mass spectra with that obtained by derivatization of commercial 2HG standards (Figure 3C). Similar results were obtained when the intracellular organic acid pool was analyzed. IDH2 R172K expressing cells were found to have an approximately 100-fold increase in the intracellular levels of 2HG compared with the levels detected in vector-transfected and IDH2-wild-type-overexpressing cells (Figure 3D). Consistent with previous work, IDH1-R132H-expressing cells analyzed in the same experiment had comparable accumulation of 2HG in both cells and in culture medium. 2HG accumulation was not observed in cells overexpressing IDH1 wild-type (data not shown).

Figure 3. Expression of R172K Mutant IDH2 Elevates 2HG Levels within Cells and in Culture Medium

(A and B) 293T cells transfected with IDH2 wild-type (A) or IDH2 R172K (B) were provided fresh culture medium the day after transfection. Twenty-four hours later, the medium was collected, from which organic acids were extracted, purified, and derivatized with MTBSTFA. Shown are representative gas chromatographs for the derivatized organic acids eluting between 30 to 34 min, including aspartate (Asp) and glutamate (Glu). The arrows indicate the expected elution time of 32.5 min for MTBSTFA-derivatized 2HG, based on similar derivatization of a commercial R(-)-2HG standard. Metabolite abundance refers to GC-MS signal intensity.

(C) Mass spectrum of the metabolite peak eluting at 32.5 min in (B), confirming its identity as MTBSTFA-derivatized 2HG. The structure of this derivative is shown in the inset, with the tert-butyl dimethylsilyl groups added during derivatization highlighted in green. m/e indicates the mass (in atomic mass units) to charge ratio for fragments generated by electron impact ionization.

(D) Cells were transfected as in (A) and (B), and after 48 hr intracellular metabolites were extracted, purified, MTBSTFA-derivatized, and analyzed by GC-MS. Shown is the quantitation of 2HG signal intensity relative to glutamate for a representative experiment. See also Figure S1.

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Mutant IDH2 Produces the (R) Enantiomer of 2HG

Cancer-associated mutants of IDH1 produce the (R) enantiomer of 2HG ( Dang et al., 2009). To determine the chirality of the 2HG produced by mutant IDH2 and to compare it with that produced by R132H mutant IDH1, we used a two-step derivatization method to distinguish the stereoisomers of 2HG by GC-MS: an esterification step with R-(−)-2-butanolic HCl, followed by acetylation of the 2-hydroxyl with acetic anhydride ( Kamerling et al., 1981). Test of this method on commercial S(+)-2HG and R(−)-2HG standards demonstrated clear separation of the (S) and (R) enantiomers, and mass spectra of the metabolite peaks confirmed their identity as the O-acetylated di-(−)-2-butyl esters of 2HG (see Figures S1A and S1B available online). By this method, we confirmed the chirality of the 2HG found in cells expressing either R132H mutant IDH1 or R172K mutant IDH2 corresponded exclusively to the (R) enantiomer ( Figures S1C and S1D).

Leukemic Cells Bearing Heterozygous R172K IDH2 Mutations Accumulate 2HG

IDH2 Is Critical for Proliferating Cells and Contributes to the Conversion of α-Ketoglutarate into Citrate in the Mitochondria

A peculiar feature of the IDH-mutated cancers described to date is their lack of reduction to homozygosity. All tumors with IDH mutations retain one IDH wild-type allele. To address this issue we examined whether wild-type IDH1 and/or IDH2 might play a role in either cell survival or proliferation. Consistent with this possibility, we found that siRNA knockdown of either IDH1 or IDH2 can significantly reduce the proliferative capacity of a cancer cell line expressing both wild-type IDH1 and IDH2 ( Figure 4A).

Both IDH1 and IDH2 Are Critical for Cell Proliferation

Both IDH1 and IDH2 Are Critical for Cell Proliferation

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Figure 4. Both IDH1 and IDH2 Are Critical for Cell Proliferation

(A) SF188 cells were treated with either of two unique siRNA oligonucleotides against IDH1 (siIDH1-A and siIDH1-B), either of two unique siRNA oligonucleotides against IDH2 (siIDH2-A and siIDH2-B), or control siRNA (siCTRL), and total viable cells were counted 5 days later. Data are the mean ± SEM of four independent experiments. In each case, both pairs of siIDH nucleotides gave comparable results. A representative western blot from one of the experiments, probed with antibody specific for either IDH1 or IDH2 as indicated, is shown on the right-hand side.

(B) Model depicting the pathways for citrate +4 (blue) and citrate +5 (red) formation in proliferating cells from [13C-U]-L-glutamine (glutamine +5).

(C) Cells were treated with two unique siRNA oligonucleotides against IDH2 or control siRNA, labeled with [13C-U]-L-glutamine, and then assessed for isotopic enrichment in citrate by LC-MS. Citrate +5 and Citrate +4 refer to citrate with five or four 13C-enriched atoms, respectively. Reduced expression of IDH2 from the two unique oligonucleotides was confirmed by western blot. Blotting with actin antibody is shown as a loading control.

(D) Cells were treated with two unique siRNA oligonucleotides against IDH3 (siIDH3-A and siIDH3-B) or control siRNA, and then labeled and assessed for isotopic citrate enrichment by GC-MS. Shown are representative data from three independent experiments. Reduced expression of IDH3 from the two unique oligonucleotides was confirmed by western blot. In (C) and (D), data are presented as mean and standard deviation of three replicates per experimental group.

The genetic analysis of these tumor samples revealed two neomorphic IDH mutations that produce 2HG. Among the IDH1 mutations, tumors with IDH1 R132C or IDH1 R132G accumulated 2HG. This result is not unexpected, as a number of mutations of R132 to other residues have also been shown to accumulate 2HG in glioma samples (Dang et al., 2009).

The other neomorphic allele was unexpected. All five of the IDH2 mutations producing 2HG in this sample set contained the same mutation, R140Q. As shown in Figure 1, both R140 in IDH2 and R100 in IDH1 are predicted to interact with the β-carboxyl of isocitrate. Additional modeling revealed that despite the reduced ability to bind isocitrate, the R140Q mutant IDH2 is predicted to maintain its ability to bind and orient α-ketoglutarate in the active site (Figure 6). This potentially explains the ability of cells with this neomorph to accumulate 2HG in vivo. As shown in Figure 5, samples containing IDH2 R140Q mutations were found to have accumulated 2HG to levels 10-fold to 100-fold greater than the highest levels detected in IDH wild-type samples.

Figure 5. Primary Human AML Samples with IDH1 or IDH2 Mutations Display Marked Elevations of 2HG

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Structural Modeling of R140Q Mutant IDH2

Structural Modeling of R140Q Mutant IDH2

Figure 6.  Structural Modeling of R140Q Mutant IDH2

(A) Active site of human wild-type IDH2 with isocitrate replaced by α-ketoglutarate (α-KG). R140 is well positioned to interact with the β-carboxyl group that is added as a branch off carbon 3 when α-ketoglutarate is reductively carboxylated to isocitrate.

(B) Active site of R140Q mutant IDH2 complexed with α-ketoglutarate, demonstrating the loss of proximity to the substrate in the R140Q mutant. This eliminates the charge interaction from residue 140 that stabilizes the addition of the β-carboxyl required to convert α-ketoglutarate to isocitrate.

IDH2 Mutations Are More Common Than IDH1 Mutations in AML

  • Neomorphic Enzymatic Activity to Produce 2HG Is the Shared Feature of IDH1 and IDH2 Mutations
  • 2HG as a Screening and Diagnostic Marker
  • Maintaining At Least One IDH1 and IDH2 Wild-Type Allele May Be Essential for Transformed Cells
  • 2HG as an Oncometabolite

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Voluntary and Involuntary S- Insufficiency

Writer and Curator: Larry H Bernstein, MD, FCAP 

Transthyretin and the Stressful Condition

Introduction

This article is written among a series of articles concerned with stress, obesity, diet and exercise, as well as altitude and deep water diving for extended periods, and their effects.  There is a reason that I focus on transthyretin (TTR), although much can be said about micronutients and vitamins, and fat soluble vitamins in particular, and iron intake during pregnancy.    While the importance of vitamins and iron are well accepted, the metabolic basis for their activities is not fully understood.  In the case of a single amino acid, methionine, it is hugely important because of the role it plays in sulfur metabolism, the sulfhydryl group being essential for coenzyme A, cytochrome c, and for disulfide bonds.  The distribution of sulfur, like the distribution of iodine, is not uniform across geographic regions.  In addition, the content of sulfur found in plant sources is not comparable to that in animal protein.  There have been previous articles at this site on TTR, amyloid and sepsis.

Transthyretin and Lean Body Mass in Stable and Stressed State

https://pharmaceuticalintelligence.com/2013/12/01/transthyretin-and-lean-body-mass-in-stable-and-stressed-state/

A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

https://pharmaceuticalintelligence.com/2012/12/03/a-second-look-at-the-transthyretin-nutrition-inflammatory-conundrum/

Stabilizers that prevent transthyretin-mediated cardiomyocyte amyloidotic toxicity

https://pharmaceuticalintelligence.com/2013/12/02/stabilizers-that-prevent-transthyretin-mediated-cardiomyocyte-amyloidotic-toxicity/

Thyroid Function and Disorders

https://pharmaceuticalintelligence.com/2015/02/05/thyroid-function-and-disorders/

Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com

https://pharmaceuticalintelligence.com/2014/09/01/compilation-of-references-in-leaders-in-pharmaceutical-intelligence-about-proteomics-metabolomics-signaling-pathways-and-cell-regulation-2/

Malnutrition in India, high newborn death rate and stunting of children age under five years

https://pharmaceuticalintelligence.com/2014/07/15/malnutrition-in-india-high-newborn-death-rate-and-stunting-of-children-age-under-five-years/

Vegan Diet is Sulfur Deficient and Heart Unhealthy

https://pharmaceuticalintelligence.com/2013/11/17/vegan-diet-is-sulfur-deficient-and-heart-unhealthy/

How Methionine Imbalance with Sulfur-Insufficiency Leads to Hyperhomocysteinemia

https://pharmaceuticalintelligence.com/2013/04/04/sulfur-deficiency-leads_to_hyperhomocysteinemia/

Amyloidosis with Cardiomyopathy

https://pharmaceuticalintelligence.com/2013/03/31/amyloidosis-with-cardiomyopathy/

Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

https://pharmaceuticalintelligence.com/2012/10/22/advances-in-separations-technology-for-the-omics-and-clarification-of-therapeutic-targets/

Sepsis, Multi-organ Dysfunction Syndrome, and Septic Shock: A Conundrum of Signaling Pathways Cascading Out of Control

https://pharmaceuticalintelligence.com/2012/10/13/sepsis-multi-organ-dysfunction-syndrome-and-septic-shock-a-conundrum-of-signaling-pathways-cascading-out-of-control/

Automated Inferential Diagnosis of SIRS, sepsis, septic shock

https://pharmaceuticalintelligence.com/2012/08/01/automated-inferential-diagnosis-of-sirs-sepsis-septic-shock/

Transthyretin and the Systemic Inflammatory Response 

Transthyretin has been widely used as a biomarker for identifying protein-energy malnutrition (PEM) and for monitoring the improvement of nutritional status after implementing a nutritional intervention by enteral feeding or by parenteral infusion. This has occurred because transthyretin (TTR) has a rapid removal from the circulation in 48 hours and it is readily measured by immunometric assay. Nevertheless, concerns have been raised about the use of TTR in the ICU setting, which prompts a review of the actual benefit of using this test in a number of settings. TTR is easily followed in the underweight and the high risk populations in an ambulatory setting, which has a significant background risk of chronic diseases.  It is sensitive to the systemic inflammatory response syndrom (SIRS), and needs to be understood in the context of acute illness to be used effectively. There are a number of physiologic changes associated with SIRS and the injury/repair process that will affect TTR and will be put in context in this review. The most important point is that in the context of an ICU setting, the contribution of TTR is significant in a complex milieu.  copyright @ Bentham Publishers Ltd. 2009.

Transthyretin as a marker to predict outcome in critically ill patients.
Arun Devakonda, Liziamma George, Suhail Raoof, Adebayo Esan, Anthony Saleh, Larry H. Bernstein.
Clin Biochem Oct 2008; 41(14-15): 1126-1130

A determination of TTR level is an objective method od measuring protein catabolic loss of severly ill patients and numerous studies show that TTR levels correlate with patient outcomes of non-critically ill patients. We evaluated whether TTR level correlates with the prevalence of PEM in the ICUand evaluated serum TTR level as an indicator of the effectiveness of nutrition support and the prognosis in critically ill patients.

TTR showed excellent concordance with patients classified with PEM or at high malnutrition risk, and followed for 7 days, it is a measure of the metabolic burden. TTR levels did not respond early to nutrition support because of the delayed return to anabolic status. It is particularly helpful in removing interpretation bias, and it is an excellent measure of the systemic inflammatory response concurrent with a preexisting state of chronic inanition.

 The Stressful Condition as a Nutritionally Dependent Adaptive Dichotomy

Yves Ingenbleek and Larry Bernstein
Nutrition 1999;15(4):305-320 PII S0899-9007(99)00009-X

The injured body manifests a cascade of cytokine-induced metabolic events aimed at developing defense mechanisms and tissue repair. Rising concentrations of counterregulatory hormones work in concert with cytokines to generate overall insulin and insulin-like growth factor 1 (IGF-1), postreceptor resistance and energy requirements grounded on lipid dependency. Dalient features are self-sustained hypercortisolemia persisting as long as cytokines are oversecreted and down-regulation of the hypothalamo-pituitary-thyroid axis stabilized at low basal levels. Inhibition of thyroxine 5’deiodinating activity (5’DA) accounts for the depressed T3 values associated with the sparing of both N and energy-consuming processes. Both the liver and damaged territories adapt to stressful signals along up-regulated pathways disconnected from the central and peripheral control systems. Cytokines stimulate 5’DA and suppress the synthesis of TTR, causing the drop of retinol-binding protein (RBP) and the leakage of increased amounts of T4 and retinol in free form. TTR and RBP thus work as prohormonal reservoirs of precursor molecules which need to be converted into bioactive derivatives (T3 and retinoic acids) to reach transcriptional efficiency. The converting steps (5’DA and cellular retinol-binding protein-1) are activated to T4 and retinol, themselves operating as limiting factors to positive feedback loops. …The suicidal behavior of TBG, CBG, and IGFBP-3 allows the occurrence of peak endocrine and mitogenic influences at the site of inflammation. The production rate of TTR by the liver is the main determinant of both the hepatic release and blood transport of holoRBP, which explains why poor nutritional status concomitantly impairs thyroid- and retinoid-dependent acute phase responses, hindering the stressed body to appropriately face the survival crisis.  …
abbreviations: TBG, thyroxine-binding globulain; CBG, cortisol-binding globulin; IGFBP-3, insulin growth factor binding protein-3; TTR, transthyretin; RBP, retionol-binding protein.

Why Should Plasma Transthyretin Become a Routine Screening Tool in Elderly Persons? 

Yves Ingenbleek.
J Nutrition, Health & Aging 2009.

The homotetrameric TTR molecule (55 kDa as MM) was first identified in cerebrospinal fluid (CSF).  The initial name of prealbumin (PA)  was assigned based on the electrophoretic migration anodal to albumin. PA was soon recognized as a specific binding protein for thyroid hormone. and also of plasma retinol through the mediation of the small retinol-binding protein (RBP, 21 kDa as MM), which has a circulating half-life half that of TTR (24 h vs 48 h).

There exist at least 3 goos reasons why TTR should become a routine medical screening test in elderly persons.  The first id grounded on the assessment of protein nutritional status that is frequently compromized and may become a life threatening condition.  TTR was proposed as a marker of protein-energy malnutrition (PEM) in 1972. As a result of protein and energy deprivation, TTR hepatic synthesis is suppressed whereas all plasma indispensable amino acids (IAAs) manifest declining trends with the sole exception of methionine (Met) whose concentration usually remains unmodified. By comparison with ALB and transferrin (TF) plasma values, TTR did reveal a much higher degree of reactivity to changes in protein status that has been attributed to its shorter biological half-life and to its unusual tryptophan richness. The predictive ability of outcome offered by TTR is independent of that provided by ALB and TF. Uncomplicated PEM primarily affects the size of body nitrogen (N) pools, allowing reduced protein syntheses to levels compatible with survival.  These adaptiver changes are faithfully identified by the serial measurement of TTR whose reliability has never been disputed in protein-depleted states. On the contrary, the nutritional relevance of TTR has been controverted in acute and chronic inflammatory conditions due to the cytokine-induced transcriptional blockade of liver synthesis which is an obligatory step occurring independently from the prevailing nutritional status. Although PEM and stress ful disorders refer to distinct pathogenic mechanisms, their combined inhibitory effects on TTR liber production fueled a long-lasting strife regarding a poor specificity.  Recent body compositional studies have contributed to disentagling these intermingled morbidities, showing that evolutionary patterns displayed by plasma TTR are closely correlated with the fluctuations of lean body mass (LBM).

The second reason follows from advances describing the unexpected relationship established between TTR and homocysteine (Hcy), a S-containing AA not found in customary diets but resulting from the endogenous transmethylation of dietary methionine.  Hcy may be recycled to Met along a remethylation pathway (RM) or irreversibly degraded throughout the transsulfuration (TS) cascade to relase sulfaturia as end-product. Hcy is thus situated at the crossrad of RM and TS pathways which are in equilibrium keeping plasma Met values unaltered.  Three dietary water soluble B viatamins are implicated in the regulation of the Hcy-Met cycle. Folates (vit B9) are the most powerful agent, working as a supplier of the methyl group required for the RM process whereas cobalamines (vit B12) and pyridoxine (vit B6) operate as cofactors of Met-synthase and cystathionine-β-synthase.  Met synthase promotes the RM pathway whereas the rate-limiting CβS governs the TS degradative cascade. Dietary deficiency in any of the 3 vitamins may upregulate Hcy plasma values, an acquied biochemiucal anomaly increasingly encountered in aged populations.

The third reason refers to recent and fascinating data recorded in neurobiology and emphasizing the specific properties of TTR in the prevention of brain deterioration. TTR participates directly in the maintenance of memory and normal cognitive processes during the aging process by acting on the retinoid signaling pathway.  Moreover, TTR may bind amyloid β peptide in vitro, preventing its transformation into toxic amyloid fibrils and amyloid plaques.  TTR works as a limiting factor for the plasma transport of retinoid, which in turn operates as a limiting determinant of both physiologically active retinoic acid (RA) derivatives, implying that any fluctuation in protein status might well entail corresponding  alterations in cellular bioavailability of retinoid compounds.  Under normal aging circumstances, the concentration of retinoid compounds declines in cerebral tissues together with the downregulation of RA receptor expression. In animal models, depletion of RAs causes the deposition of amyloid-β peptides, favoring the formation of amyloid plaques.

Prealbumin and Nutritional Evaluation

Larry Bernstein, Walter Pleban
Nutrition Apr 1996; 12(4):255-259.
http://nutritionjrnl.com/article/S0899-9007(96)90852-7

We compressed 16-test-pattern classes of albumin (ALB), cholesterol (CHOL), and total protein (TPR) in 545 chemistry profiles to 4 classes by conveerting decision values to a number code to sep