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Glypican-1 identifies cancer exosomes

Larry H. Bernstein, MD, FCAP, Curator

LPBI

Glypican-1 identifies cancer exosomes and detects early pancreatic cancer

Sonia A. MeloLinda B. LueckeChristoph KahlertAgustin F. FernandezSeth T. GammonJudith Kaye, et al.

Nature (09 July 2015); 523: 177–182     http://dx.doi.org:/10.1038/nature14581

Most cells shed so-called extracellular vesicles or exosomes consisting of proteins and nucleic acids enclosed in phospholipid bilayers. Exosomes derived from cancer cells can be isolated.

Exosomes are lipid-bilayer-enclosed extracellular vesicles that contain proteins and nucleic acids. They are secreted by all cells and circulate in the blood. Specific detection and isolation of cancer-cell-derived exosomes in the circulation is currently lacking. Using mass spectrometry analyses, we identify a cell surface proteoglycan, glypican-1 (GPC1), specifically enriched on cancer-cell-derived exosomes. GPC1+ circulating exosomes (crExos) were monitored and isolated using flow cytometry from the serum of patients and mice with cancer. GPC1+ crExos were detected in the serum of patients with pancreatic cancer with absolute specificity and sensitivity, distinguishing healthy subjects and patients with a benign pancreatic disease from patients with early- and late-stage pancreatic cancer. Levels of GPC1+ crExos correlate with tumour burden and the survival of pre- and post-surgical patients. GPC1+ crExos from patients and from mice with spontaneous pancreatic tumours carry specific KRAS mutations, and reliably detect pancreatic intraepithelial lesions in mice despite negative signals by magnetic resonance imaging. GPC1+ crExos may serve as a potential non-invasive diagnostic and screening tool to detect early stages of pancreatic cancer to facilitate possible curative surgical therapy.

Figure 1: GPC1 is present on cancer exosomes.

GPC1 is present on cancer exosomes.

a, Venn diagram of proteins from NIH/3T3 (blue), MCF10A (red), HDF (green), E10 (yellow) and MDA-MB-231 (purple) exosomes. In total, 48 proteins were exclusively detected in MDA-MB-231 exosomes (n = 3 protein samples,…

Figure 2: GPC1+ crExos are a non-invasive biomarker for pancreatic cancer.

GPC1+ crExos are a non-invasive biomarker for pancreatic cancer.

a, Percentage of GPC1+crExo beads in healthy donors, patients with breast cancer and patients with PDAC (analysis of variance (ANOVA), post-hoc Tamhane T2, ****P < 0.0001). b, Frequency ofKRAS mutation in 47 tumours…

Figure 3: Levels of circulating GPC1+exosomes inform pancreatic cancer resection outcome.

Levels of circulating GPC1+ exosomes inform pancreatic cancer resection outcome.

a, Longitudinal blood collection pre- and post-operatively (day 7). b, Percentage of GPC1+crExo beads from patients with BPD (n = 4), PCPL (n = 4) or PDAC (n = 29) (paired two-tailed Student’s t-test, **P < 0.01, ****P < 0.0001). Data a…

Cancer: Diagnosis by extracellular vesicles

Nature (09 July 2015); 523: 161–162.   http://dx.doi.org:/10.1038/nature14626

The detection of a single molecule anchored to circulating extracellular vesicles allows late-stage pancreatic cancer to be identified from just one drop of a patient’s blood. See Article p.177

ReferencesAuthor information

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Oxidative stress inhibits distant metastasis by human melanoma cells

Elena PiskounovaMichalis AgathocleousMalea M. MurphyZeping HuSara E. HuddlestunZhiyu Zhao, et al.

Nature 14 Oct 2015      http://dx.doi.org:/10.1038/nature15726

Solid cancer cells commonly enter the blood and disseminate systemically, but are highly inefficient at forming distant metastases for poorly understood reasons. Here we studied human melanomas that differed in their metastasis histories in patients and in their capacity to metastasize in NOD-SCID-Il2rg−/− (NSG) mice. We show that melanomas had high frequencies of cells that formed subcutaneous tumours, but much lower percentages of cells that formed tumours after intravenous or intrasplenic transplantation, particularly among inefficiently metastasizing melanomas. Melanoma cells in the blood and visceral organs experienced oxidative stress not observed in established subcutaneous tumours. Successfully metastasizing melanomas underwent reversible metabolic changes during metastasis that increased their capacity to withstand oxidative stress, including increased dependence on NADPH-generating enzymes in the folate pathway. Antioxidants promoted distant metastasis in NSG mice. Folate pathway inhibition using low-dose methotrexate, ALDH1L2 knockdown, or MTHFD1 knockdown inhibited distant metastasis without significantly affecting the growth of subcutaneous tumours in the same mice. Oxidative stress thus limits distant metastasis by melanoma cells in vivo.

Lymph node-independent liver metastasis in a model of metastatic colorectal cancer

Ida B. EnquistZinaida GoodAdrian M. JubbGermaine FuhXi WangMelissa R. JunttilaErica L. Jackson & Kevin G. Leong

Nature Communications  26 Mar 2014; 3530(5)    http://dx.doi.org:/10.1038/ncomms4530

Deciphering metastatic routes is critically important as metastasis is a primary cause of cancer mortality. In colorectal cancer (CRC), it is unknown whether liver metastases derive from cancer cells that first colonize intestinal lymph nodes, or whether such metastases can form without prior lymph node involvement. A lack of relevant metastatic CRC models has precluded investigations into metastatic routes. Here we describe a metastatic CRC mouse model and show that liver metastases can manifest without a lymph node metastatic intermediary. Colorectal tumours transplanted onto the colonic mucosa invade and metastasize to specific target organs including the intestinal lymph nodes, liver and lungs. Importantly, this metastatic pattern differs from that observed following caecum implantation, which invariably involves peritoneal carcinomatosis. Anti-angiogenesis inhibits liver metastasis, yet anti-lymphangiogenesis does not impact liver metastasis despite abrogating lymph node metastasis. Our data demonstrate direct hematogenous spread as a dissemination route that contributes to CRC liver malignancy.

Comprehensive models of human primary and metastatic colorectal tumors in immunodeficient and immunocompetent mice by chemokine targeting

Huanhuan Joyce ChenJian SunZhiliang HuangHarry Hou JrMyra ArcillaNikolai RakhilinDaniel J JoeJiahn ChoiPoornima GadamsettyJeff MilsomGovind NandakumarRandy LongmanXi Kathy Zhou, et al.

Nature Biotechnology (2015);  33:656–660    http://dx.doi.org:/10.1038/nbt.3239

Current orthotopic xenograft models of human colorectal cancer (CRC) require surgery and do not robustly form metastases in the liver, the most common site clinically. CCR9 traffics lymphocytes to intestine and colorectum. We engineered use of the chemokine receptor CCR9 in CRC cell lines and patient-derived cells to create primary gastrointestinal (GI) tumors in immunodeficient mice by tail-vein injection rather than surgery. The tumors metastasize inducibly and robustly to the liver. Metastases have higher DKK4 and NOTCH signaling levels and are more chemoresistant than paired subcutaneous xenografts. Using this approach, we generated 17 chemokine-targeted mouse models (CTMMs) that recapitulate the majority of common human somatic CRC mutations. We also show that primary tumors can be modeled in immunocompetent mice by microinjecting CCR9-expressing cancer cell lines into early-stage mouse blastocysts, which induces central immune tolerance. We expect that CTMMs will facilitate investigation of the biology of CRC metastasis and drug screening.

Induction of the intestinal stem cell signature gene SMOC-2 is required for L1-mediated colon cancer progression

A Shvab, G Haase, A Ben-Shmuel, N Gavert, T Brabletz, S Dedhar and A Ben-Ze’ev

Oncogene , (27 April 2015) |       http://dx.doi.org:/10.1038/onc.2015.127

Overactivation of Wnt-β-catenin signaling, including β-catenin-TCF target gene expression, is a hallmark of colorectal cancer (CRC) development. We identified the immunoglobulin family of cell-adhesion receptors member L1 as a β-catenin-TCF target gene preferentially expressed at the invasive edge of human CRC tissue. L1 can confer enhanced motility and liver metastasis when expressed in CRC cells. This ability of L1-mediated metastasis is exerted by a mechanism involving ezrin and the activation of NF-κB target genes. In this study, we identified the secreted modular calcium-binding matricellular protein-2 (SMOC-2) as a gene activated by L1-ezrin-NF-κB signaling. SMOC-2 is also known as an intestinal stem cell signature gene in mice expressing Lgr5 in cells at the bottom of intestinal crypts. The induction of SMOC-2 expression in L1-expressing CRC cells was necessary for the increase in cell motility, proliferation under stress and liver metastasis conferred by L1. SMOC-2 expression induced a more mesenchymal like phenotype in CRC cells, a decrease in E-cadherin and an increase in Snail by signaling that involves integrin-linked kinase (ILK). SMOC-2 was localized at the bottom of normal human colonic crypts and at increased levels in CRC tissue with preferential expression in invasive areas of the tumor. We found an increase in Lgr5 levels in CRC cells overexpressing L1, p65 or SMOC-2, suggesting that L1-mediated CRC progression involves the acquisition of a stem cell-like phenotype, and that SMOC-2 elevation is necessary for L1-mediated induction of more aggressive/invasive CRC properties.

Global analysis of L1-transcriptomes identified IGFBP-2 as a target of ezrin and NF-κB signaling that promotes colon cancer progression

A Ben-Shmuel, A Shvab, N Gavert, T Brabletz and A Ben-Ze’ev

Oncogene 06 Aug 2012; Oncogene  (04 July 2013); 32: 3220-3230 |  http://dx.doi.org:/10.1038/onc.2012.340

L1, a neuronal cell adhesion receptor of the immunoglobulin-like protein family is expressed in invading colorectal cancer (CRC) cells as a target gene of Wnt/β-catenin signaling. Overexpression of L1 in CRC cells enhances cell motility and proliferation, and confers liver metastasis. We recently identified ezrin and the IκB-NF-κB pathway as essential for the biological properties conferred by L1 in CRC cells. Here, we studied the underlying molecular mechanisms and found that L1 enhances ezrin phosphorylation, via Rho-associated protein kinase (ROCK), and is required for L1–ezrin co-localization at the juxtamembrane domain and for enhancing cell motility. Global transcriptomes from L1-expressing CRC cells were compared with transcriptomes from the same cells expressing small hairpin RNA (shRNA) to ezrin. Among the genes whose expression was elevated by L1 and ezrin we identified insulin-like growth factor-binding protein 2 (IGFBP-2) and showed that its increased expression is mediated by an NF-κB-mediated transactivation of the IGFBP-2 gene promoter. Expression of a constitutively activated mutant ezrin (Ezrin567D) could also increase IGFBP-2 levels in CRC cells. Overexpression of IGFBP-2 in CRC cells lacking L1-enhanced cell proliferation (in the absence of serum), cell motility, tumorigenesis and induced liver metastasis, similar to L1 overexpression. Suppression of endogenous IGFBP-2 in L1-transfected cells inhibited these properties conferred by L1. We detected IGFBP-2 in a unique organization at the bottom of human colonic crypts in normal mucosa and at increased levels throughout human CRC tissue samples co-localizing with the phosphorylated p65 subunit of NF-κB. Finally, we found that IGFBP-2 and L1 can form a molecular complex suggesting that L1-mediated signaling by the L1–ezrin–NF-κB pathway, that induces IGFBP-2 expression, has an important role in CRC progression.

 

Exosome Scouts Help Tumors Populate Distant Organs

  • Click Image To Enlarge +
    This image shows exosomes (green) that have infiltrated the whole lung. [Ayuko Hoshino, David Lyden, Weill Cornell Medicine

    When certain types of cancer spread, they seem to prefer particular organs in the body, a choosiness that led Stephen Paget to propose the “seed and soil” hypothesis. This hypothesis, now more than 100 years old, suggests that different organs are somehow more receptive to certain types of cancer, just as different soils seem to allow some seeds, but not others, to find purchase.

    While this hypothesis is as expressive as ever, it still lacks detail. It doesn’t suggest what mechanisms might drive organ-specific metastasis, or organotropic metastasis. The hypothesis, however, is being taken farther by researchers based at Weill Cornell Medicine. These researchers suggest that the old seed-and-soil idea, which sounds as haphazard as the dispersal of seeds by uncultivated plants, could be updated to describe a process that is more directed.

    Essentially, a tumor metastasis may proceed the way settlers cultivate new land. First, scouts and pioneers are dispatched to identify fertile spots and develop basic infrastructure. Then, once the ground is prepared, settlers establish new communities.

    In this scenario, the scouts are tumor exosomes. These exosomes are released by tumors in the millions, and they carry samples of the tumors’ proteins and genetic content. They fuse preferentially with cells at specific locations, and they ensure that recipient organs are prepared to host the tumor cells they represent.

    Most important, this updated view of organotropic metastasis includes a mechanism to explain how exosomes are directed to specific organs. The exosomes, it turns out, are outfitted with particular sets of integrins, proteins that serve as a kind of destination label.

    Supportive findings appeared October 28 in the journal Nature, in an article entitled, “Tumour exosome integrins determine organotropic metastasis.” This article described how the Weill Cornell researchers, in collaboration with scientists from the Memorial Sloan Kettering Cancer center and the Spanish National Cancer Research Centre (CNIO), examined exosomes from mouse and human lung-, liver-, and brain-tropic tumor cells. These exosomes were seen to fuse preferentially with resident cells at their predicted destinations, namely, lung fibroblasts and epithelial cells, liver Kupffer cells, and brain endothelial cells.

    “Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis,” wrote the authors. “Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively.”

    In other words, the study demonstrated the importance of integrins in metastatic nesting by blocking specific integrins in tumors that metastasize to specific organs. For example, when integrins were blocked in breast cancer, metastasis to lungs was reduced. Similarly, when integrins were blocked in pancreatic cancer, metastasis to liver was reduced.

    In addition, the study showed that a tumor could be “tricked” by changing the integrin destination code of its exosomes. For example, a tumor that would normally go to the bones could be directed to the lungs instead.

    “The integrin-specific signature that we identified may have significant value clinically, serving as a prognostic indicator for metastasis to specific organ sites,” said senior author David Lyden, M.D., Ph.D., the Stavros S. Niarchos Professor in Pediatric Cardiology and a professor of pediatrics and of cell and developmental biology at Weill Cornell Medicine. “Instead of waiting for late-stage metastasis, we can now initiate preventative strategies at an earlier point of disease progression with the hope of preventing its spread. This really changes the treatment paradigm.”

     

  • Using CRISPR as a High-Throughput Cancer Screening and Modeling Tool
  • Click Image To Enlarge +
    Using CRISPR/Cas9, scientists created a new high-throughput screening tool for studying the development and progression of liver cancer in mice. [Ernesto del Aguila III, NHGRI]

    A contingent of researchers from the UK, Germany, and Spain have recently developed a novel CRISPR/Cas9 system that they believe can be utilized as a multiplexed screening approach to study and model cancer development in mice. In the current study, the investigators directly mutated genes within adult mouse livers to elucidate their role in cancer development and progression—simultaneously uncovering the gene combinations that coordinate to cause liver cancer.

    “We reasoned that, by targeting mutations directly to adult liver cells using CRISPR/Cas9, we could better study and understand the biology of this important cancer,” explained co-author Mathias Friedrich, Ph.D., research scientist at the Wellcome Trust Sanger Institute. “Other approaches to engineer mutations in mice, such as stem cell manipulation, are limited by the laborious process, the long time frames and large numbers of animals needed. And, our method better mimics important aspects of human cancer biology than many “classic” mouse models: as in most human cancers, the mutations occur in the adult and only affect a few cells”.

    The findings from this study were published online recently in PNAS through an article entitled “CRISPR/Cas9 somatic multiplex-mutagenesis for high-throughput functional cancer genomics in mice.”

    This new approach is rapid, scalable, and extremely efficient, allowing the researchers to examine an array of genes or large regions of the genome concurrently. Moreover, this methodology affords scientists the ability to distinguish between cancer driver mutations and passenger mutations—those that occur as side-effects of cancer development.

    The research team developed a list of up to eighteen genes with known or unknown evidence for their importance in two forms of liver cancer. They then introduced the CRISPR/Cas9 molecules, targeting various combinations of these genes into mice, which subsequently developed liver or bile duct cancer within a few months.

    “Our approach enables us to simultaneously target multiple putative genes in individual cells,” noted co-author Roland Rad, Ph.D., project leader at the Technical University of Munich and the German Cancer Research Center Heidelberg. “We can now rapidly and efficiently screen which genes are cancer-causing and which ones are not. And, we can study how genes work together to cause cancers—a crucial piece of the puzzle we must solve to understand and tackle the disease.”

    The investigators were able to confirm that a set of DNA-binding proteins called ARID (AT-rich interactive domain), influence the organization of chromosomes and are important for liver cancer development. Furthermore, mutations in a second protein, TET2, were found to be causative in bile duct cancer: although TET2 has not been found to be mutated in human biliary cancers, the proteins that it interacts with have been, showing that the CRISPR/Cas9 method can identify human cancer genes that are not mutated, but whose function is disturbed by other events.

    “The new tools of targeting genes in combination and inducing insertions or deletions in chromosomes change our ability to identify new cancer-causing genes and to understand their role in cancer,” stated senior group leader and co-author Allan Bradley, Ph.D., director emeritus from the Sanger Institute. “Our results show that this approach is feasible and productive in liver cancer; we will now continue to study our new findings and try to extend the approach to other cancer types.”

    This CRISPR/Cas9 approach may also be favorable for an in-depth examination of genomic deserts —regions within the human genome that appear to be devoid of genes. Yet, recent data from the ENCODE Project suggests that deserts can be populated, if not by genes, then by DNA regulatory regions that influence the activity of genes.

    “Liver cancer has many DNA alterations in regions lacking genes: we don’t know which of these might be important for the disease,” said Dr. Rad. “However, we could show that it is now possible to delete such regions to systematically determine their role in liver cancer development.”

     

CRISPR Used to Create Mouse Models of Cancer

  • When scientists study the genetics of cancer, they often breed mice strains that carry selected cancer-associated mutations. But cultivating such strains, usually via transgenesis or gene targeting in embryonic stem cells, is often time-consuming and expensive. Could there be a better way—a faster, cheaper way—to create mice strains that carry particular genetic flaws?

    An alternative has been proposed by researchers from MIT. They have shown that the CRISPR gene editing system can introduce cancer-causing mutations into the livers of adult mice. The researchers anticipate that their method will allow for more rapid testing of any single genes or gene combinations that are suspected of being capable of initiating tumor formation in the liver.

    “The sequencing of human tumors has revealed hundreds of oncogenes and tumor suppressor genes in different combinations. The flexibility of this technology, as delivery gets better in the future, will give you a way to pretty rapidly test those combinations,” said Phillip Sharp, Ph.D., a professor at MIT’s Koch Institute for Integrative Cancer Research.

    Dr. Sharp was part of the MIT research team, which was led by Koch Institute director Tyler Jacks, Ph.D. Dr. Jacks noted that the CRISPR technique, which not only provides the ability to delete genes, but also to replace them with altered versions, “really opens up all sorts of new possibilities when you think about the kinds of genes that you would want to mutate in the future.” Both loss of function and gain of function, he explained, are possible.

    The MIT researchers presented their results August 6 in Nature, in an article entitled, “CRISPR-mediated direct mutation of cancer genes in the mouse liver.” It described how cancer models were generated using the CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated proteins) system in vivo in wild-type mice.

    “We used hydrodynamic injection to deliver a CRISPR plasmid DNA expressing Cas9 and single guide RNAs (sgRNAs) to the liver that directly target the tumor suppressor genes Pten and p53 (also known as TP53 and Trp53), alone and in combination,” wrote the authors. “CRISPR-mediated Pten mutation led to elevated Akt phosphorylation and lipid accumulation in hepatocytes, phenocopying the effects of deletion of the gene using Cre–LoxP technology. Simultaneous targeting of Pten and p53 induced liver tumors that mimicked those caused by Cre–loxP-mediated deletion of Pten and p53.”

    Studies of such genetically engineered mice have yielded many important discoveries, but the process, which requires introducing mutations into embryonic stem cells, can take more than a year and costs hundreds of thousands of dollars. Using Cas enzymes targeted to cut snippets of p53 and Pten, the researchers were able to disrupt those two genes in about 3% of liver cells, enough to produce liver tumors within three months.

    With traditional techniques, genetically engineering such models is “a very long process,” commented Dr. Jacks. “And the more genes you’re working with, the longer and more complicated it becomes.

    The researchers also used CRISPR to create a mouse model with an oncogene called beta catenin, which makes cells more likely to become cancerous if additional mutations occur later on. To create this model, the researchers had to cut out the normal version of the gene and replace it with an overactive form, which was successful in about 0.5% of hepatocytes.

    In the Nature article, the authors emphasized that simplified methods of testing the oncogenic properties of candidates in vivo are critical. In particular, they cited the need to somehow evaluate the thousands of candidate cancer genes that are being discovered through next-generation sequencing efforts.

    Already looking forward to refining their method of generating cancer models, the authors suggested that it could attain greater sensitivity if CRISPR/Cas9-mediated mutagenesis could be performed on a “sensitized” background carrying constitutive or conditional mutations in a tumor suppressor gene such as p53. “More efficient delivery techniques, such as adenovirus or adeno-associated virus, more potent sgRNAs, and longer homologous recombination templates,” they wrote, “might also improve the overall efficiency of this method and expand the range of tissue that could be targeted.”

     

 

Bioinformatics beyond Genome Crunching  

Flow Cytometry, Workflow Development, and Other Information Stores Can Become Treasure Troves If You Use the Right IT Tools and Services

  • Click Image To Enlarge +
    Shown here is the FlowJo platform’s visualization of surface activation marker expression (CD38) on live lymphocyte CD8+ T cells. Colors represent all combinations of subsets positive and negative for interferon gamma (IFN?), perforin (Perf), and phosphorylated ERK (pERK).

    Advances in bioinformatics are no longer limited to just crunching through genomic and exosomic data. Bioinformatics, a discipline at the interface between biotechnology and information technology, also has lessons for flow cytometry and experimental design, as well as database searches, for both internal and external content.

    One company offering variations on traditional genome crunching is DNAnexus. With the advent of the $1,000 genome, researchers find themselves drowning in data. To analyze the terabytes of information, they must contract with an organization to provide the computing power, or they must perform the necessary server installation and maintenance work in house.

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Lymph Node Metastases

Larry H. Bernstein, MD, FCAP, Curator

LPBI

Investigation of the Lack of Angiogenesis in the Formation of Lymph Node Metastases

Journal of the National Cancer Institute

Han-Sin Jeong; Dennis Jones; Shan Liao; Daniel A. Wattson; Cheryl H. Cui; Dan G. Duda; Christopher G. Willett; Rakesh K. Jain; Timothy P. Padera

J Natl Cancer Inst. 2015; 107(9)

http://www.medscape.com/viewarticle/850756

Background: To date, antiangiogenic therapy has failed to improve overall survival in cancer patients when used in the adjuvant setting (local-regional disease with no detectable systemic metastasis). The presence of lymph node metastases worsens prognosis, however their reliance on angiogenesis for growth has not been reported.

Methods: Here, we introduce a novel chronic lymph node window (CLNW) model to facilitate new discoveries in the growth and spread of lymph node metastases. We use the CLNW in multiple models of spontaneous lymphatic metastases in mice to study the vasculature of metastatic lymph nodes (n = 9–12). We further test our results in patient samples (n = 20 colon cancer patients; n = 20 head and neck cancer patients). Finally, we test the ability of antiangiogenic therapy to inhibit metastatic growth in the CLNW. All statistical tests were two-sided.

Results: Using the CLNW, we reveal the surprising lack of sprouting angiogenesis during metastatic growth, despite the presence of hypoxia in some lesions. Treatment with two different antiangiogenic therapies showed no effect on the growth or vascular density of lymph node metastases (day 10: untreated mean = 1.2%, 95% confidence interval [CI] = 0.7% to 1.7%; control mean = 0.7%, 95% CI = 0.1% to 1.3%; DC101 mean = 0.4%, 95% CI = 0.0% to 3.3%; sunitinib mean = 0.5%, 95% CI = 0.0% to 1.0%, analysis of variance P = .34). We confirmed these findings in clinical specimens, including the lack of reduction in blood vessel density in lymph node metastases in patients treated with bevacizumab (no bevacizumab group mean = 257 vessels/mm2, 95% CI = 149 to 365 vessels/mm2; bevacizumab group mean = 327 vessels/mm2, 95% CI = 140 to 514 vessels/mm2P = .78).

Conclusion: We provide preclinical and clinical evidence that sprouting angiogenesis does not occur during the growth of lymph node metastases, and thus reveals a new mechanism of treatment resistance to antiangiogenic therapy in adjuvant settings. The targets of clinically approved angiogenesis inhibitors are not active during early cancer progression in the lymph node, suggesting that inhibitors of sprouting angiogenesis as a class will not be effective in treating lymph node metastases.

Introduction

Although antiangiogenic therapy is standard of care for several advanced (metastatic) cancers, all phase III clinical trials of antiangiogenic therapy to date have failed in the adjuvant setting.[1–4] The presence of lymph node metastases—the most common form of cancer dissemination—dictates treatment decisions,[5,6] however their reliance on angiogenesis for growth has not been reported. Furthermore, observations from preclinical and clinical studies suggest that lymph node metastases and primary tumors can respond differently to the same therapeutic regimen.[7–9] The clinical relevance of lymph node metastases has been the subject of debate for many years. Some argue that the presence of lymph node metastasis only demonstrates the ability of the cancer to metastasize and that disease in the lymph node is inconsequential.[10,11] The strong predictive power of lymph node metastases has led others to hypothesize that cancer cells in the lymph node can exit and spread to distant metastatic sites.[12,13] These advocates argue disease in lymph nodes needs to be treated in order to prevent distant metastasis and ultimately eradicate disease from the patient.[14,15] Likely the answer lies in between, depending where on the spectrum of progression to distant metastasis the cancer is diagnosed.[16]These issues highlight our fundamental lack of understanding of the biology of how metastatic cancer cells grow in a lymph node and affect the overall prognosis for the patient, limiting our ability to discover effective adjuvant therapy to treat lymph node metastases.

We and others have previously shown that antiangiogenic therapy did not stop the seeding or growth of lymph node metastases,[9,17,18] but no mechanism of failure has been determined. Nonsprouting angiogenesis mechanisms to sustain tumor growth, such as vessel co-option and intussusception, have been implicated in the growth of lung, liver, and brain metastases[19] and are thought to play a role in resistance to antiangiogenic therapy.[20] Based on these findings, we hypothesized that early growth of lymph node metastases is not dependent on sprouting angiogenesis.

Although reports show reduced vascular density in lymph node metastases compared with corresponding primary tumors and surrounding normal lymph node,[17,21,22] these data do not describe the degree of angiogenesis or whether the vessels are functional. Here, we introduce a novel model to longitudinally image the formation and growth of metastatic tumors in lymph nodes and reveal the surprising lack of sprouting angiogenesis, despite the presence of hypoxia in some lesions. Treatment with two different therapies designed to target sprouting angiogenesis showed no effect on the growth or vascular density of lymph node metastases in our models. These data are corroborated in clinical specimens and further add to mechanisms for the failure of antiangiogenic treatments in adjuvant settings.[1–4,20]

….

Intravital Multiphoton Microscopy

Intravital multiphoton microscopy was carried out as described previously on a custom-built multiphoton microscope.[25] Details of the imaging equipment, imaging protocols, and image analysis can be found in the Supplementary Methods http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 (available online).

….

Longitudinal Imaging of the Formation of Spontaneous Lymph Node Metastases Using a Novel Chronic Lymph Node Window

Holding back our understanding of the biology of lymph node metastasis is our inability to longitudinally monitor spontaneous lymph node metastases. Inspired by pioneering intravital microscopy of the lymph node,[30–35] we developed a chronic lymph node window (CLNW)—a modification of the mammary fat pad chamber[23,24]—to create a CLNW that allows intravital imaging for up to 14 days with minimal morphological, cellular or biochemical changes in the inguinal lymph node (Figure 1, A and B; Supplementary Figure 1,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online).

Using multiphoton microscopy in the CLNW, we were able to serially image various stages of the growth of spontaneous metastasis in the lymph node from murine SCCVII squamous cell carcinoma[36,37]transduced with green fluorescence protein (SCCVII-GFP) (Figure 1C). Initially, cancer cells remain in or near the subcapsular sinus as individual cells (Figure 1C). Later, small aggregates of a few cancer cells form near the subcapsular sinus, which then grow into metastatic lesions that invade deeper into the lymph node (Figure 1C). This sequence was also observed in syngeneic MCa-P0008 breast cancer and B16F10 melanoma cells lines (Supplementary Figure 2,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online).

Recent genomic studies suggest that metastatic cells within lymph nodes consist of multiple clones.[38,39]To investigate this concept, we transduced SCCVII and SCCVII-GFP cells with a red fluorescence protein (DsRed), producing three different colors of cells (red, green, and red+green) that were mixed in equal proportions to form primary tumors. Single cells of multiple colors disseminated from the multicolor primary tumor and grew in the subcapsular sinus (Figure 1D). The metastatic lesions that subsequently formed contained all three colors with great spatial heterogeneity (Figure 1D), suggesting that lymph node metastases form from multiple cells. These findings were reproduced when using an equal mix of 4T1-DsRed and 4T1-GFP mammary carcinoma cells implanted in the mammary fat pad. In contrast, more than 80% of detected lung metastases from these 4T1 tumors were single color (Figure 1E).

The Role of the Existing Lymph Node Vascular Supply in Supporting the Growth of Lymph Node Metastases

Next, we directly measured for the first time whether angiogenesis is occurring in lymph node metastases by using intravital multiphoton microscopy to make longitudinal measurements in our CLNW. In early stages, metastatic cells resided in the lymph node sinus, away from blood vessels (Figure 2A). These metastatic tumor cells eventually invaded the lymph node cortex, growing closer to functional lymph node blood vessels and presumably utilizing the nutrient supply of these pre-existing vessels (Figure 2A). We found that the tumor cells started to access host lymph node blood vessels when they invaded approximately 50 to 100 μm into the cortex (Figure 2, B and C). Although the tumor invaded deeper into the node (day 6 mean depth = 43 μm, 95% CI = 24 to 61 μm; day 12 mean depth = 131 μm, 95% CI = 71 to 191 μm, P = .01), blood vessels did not invade toward the surface of the lymph node (day 6 mean depth = 52 μm, 95% CI = 49 to 55 μm; day 20 mean depth = 58 μm, 95% CI = 41 to 75 μm,P = .38), as would be expected for tumor-induced sprouting angiogenesis. These data provide the first direct evidence of the lack of sprouting angiogenesis during the growth of metastatic lesions in the lymph node.

Figure 2.

Intravital imaging of lymph node metastases and the native lymph node vasculature. A) Representative time course of images from a single metastatic lymph node, showing cancer cells (SCCVII, green) and blood vessels (TRITC-dextran, red) at three different depths in tissue. The image was created using multiphoton microscopy, and second harmonic generation was used to highlight fibrillar collagen (blue) in the lymph node capsule. The images are created from maximum intensity projections of 25 μm of tissue from inside the lymph node. In day 40 images, the red signal is background signal from the accumulation of TRITC-dextran as a result of the five intravenous injections over the course of the metastatic growth. Yellow arrows identify individual cancer cells. Yellow circles identify areas in which many cancer cells are found in the subcapsular sinus. White arrows identify blood vessels in the metastatic lesion. Purple, green and light blue arrows identify features in the lymph node vasculature that can be used to identify the same region in the mouse over the multiday experiment. White line marks edge of lymph node. Scale bars = 100 μm. B) A vertical image reconstruction showing the tumor cells (SCCVII, green) initially growing above the blood vessels (red). C) Measurements of the maximum depth of tumor cell invasion (SCCVII) and the minimum depth of blood vessels. Data are presented as mean ± 95% confidence interval.

Immunofluorescent staining for CD31 (Figure 3A) showed that the vessel density in lymph nodes with micrometastases from SCCVII tumors (Figure 3B) and macrometastases (lesions greater than 500 microns in one dimension) from 4T1 tumors (Figures 3E; Supplementary Figure 3A,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online) were not increased compared with those of control (from naïve mice with no tumor implantation) and contralateral nodes. The vessel density inside metastatic lesions was lower than the surrounding lymph node tissue (vessel density: SCCVII: metastatic lesion = 1.0%, 95% CI = 0.0% to 2.0%; nontumor area = 7.0%, 95% CI = 1.0% to 13.0%, P = .04; 4T1: metastatic lesion = 4.0%, 95% CI = 1.0% to 7.0%; nontumor area = 10.0%, 95% CI = 5.0% to 15.0%, P = .04) (Figure 3, C and F). To indicate sprouting angiogenesis, Ki67—a marker of cell proliferation—showed no difference in endothelial cell proliferation in micrometastatic lymph nodes (SCCVII) (Figure 3D; Supplementary Figure 4,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online) and a reduction in endothelial cell proliferation in macrometastatic lymph nodes (4T1) (Figure 3G; Supplementary Figure 3B, http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online) in comparison with control and contralateral nodes. Vessel density in the metastatic lesions was not related to lesion size (Supplementary Figure 3C, http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online). These data further indicate that sprouting angiogenesis is not induced in the lymph node at this stage of cancer progression.

Figure 3.

Immunohistochemical analysis of lymph node blood vessels and metastases. A) Representative sections of control (from non–tumor bearing mice), contralateral, and tumor-draining lymph nodes with micrometastases (SCCVII, green). Vessels were stained with CD31 (red) and nuclei with DAPI (blue).Scale bars = 300 μm. B) Quantification of CD31+ area per lymph node area in control, contralateral, and micrometastatic lymph nodes. C) In micrometastatic lymph nodes, quantification of CD31+ area per tissue area comparing tumor areas with nontumor areas. D) Costaining for CD105 and Ki67 measured blood vessel proliferation in micrometastatic lymph nodes. E) Using a different tumor model (4T1) that formed macrometastasis in the lymph node (greater than 500 μm in one direction), we measured CD31+ area in micrometastatic or macrometastatic lymph nodes, compared with control or contralateral nodes. F) The vascular area of macrometastatic lesions was measured in tumor areas and nontumor lymph node tissue. G) Costaining for CD31 and Ki67 measured blood vessel proliferation in macrometastatic lymph nodes. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by one-way analysis of variance with Tukey’s Honestly Significant Difference post hoc test (B, D, E, G) or two-tailed paired Student’s t test (C, F).

In contrast, LYVE-1 staining for lymphatic vessels showed an increase in lymphatic vascular area (vessel density: SCCVII: control = 5.0%, 95% CI = 3.0% to 7.0%; contralateral = 8.0%, 95% CI = 6.0% to 10.0%; metastatic = 10.0%, 95% CI = 6.0% to 14.0%; control vs metastatic P = .03; 4T1: control = 5.0%, 95% CI = 2.0% to 8.0%; contralateral = 9.0%, 95% CI = 6.0% to 12.0%; nonmetastatic tumor draining = 22.0%, 95% CI = 18.0% to 26.0%; metastatic = 4.0%, 95% CI = 1.0% to 7.0%; control vs nonmetastatic tumor draining P < .001) and proliferating lymphatic endothelial cells in draining lymph nodes from SCCVII and 4T1 tumors (Supplementary Figures 5 and 6,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online), consistent with previous reports.[40–43] Interestingly, the lymphatic vascular area was greater in the contralateral and nonmetastatic tumor-draining lymph nodes of 4T1-bearing mice compared with lymph nodes with macrometastatic lesions (P < .001) (Supplementary Figure 6,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online), suggesting that the presence of cancer cells causes the lymphatic vasculature to regress. When compared with lymph nodes from tumor-naïve animals, contralateral lymph nodes show greater lymphatic vascular density (SCCVII: P = .04; 4T1: P < .001), suggesting that contralateral lymph nodes are also affected by the presence of the primary tumor, as others have reported.[44]

Although lesions growing in the subcapsular sinus of the lymph node showed markers for hypoxia (Figure 4, A–D), sprouting angiogenesis was not induced in these lesions and they remained avascular. Metastatic lesions that invaded the lymph node parenchyma where functional nodal blood vessels reside had only focally heterogeneous areas positive for hypoxia markers (Figure 4, A, C, and E). These data suggest that growing metastatic lesions can utilize the existing lymph node vasculature in order to meet their metabolic demand. Whether this demand or hypoxia drives cancer cell invasion of the lymph node remains unknown.

Figure 4.

Hypoxia in lymph node metastases. A) Representative images of pimonidazole staining for hypoxia (green) and perfused lectin staining for functional blood vessels (red) in lymph node metastases from 4T1 mammary carcinoma (cytokeratin, blue). The top panels show a lesion in the subcapsular sinus that is hypoxic and has no perfused blood vessels in the lesion. The bottom panels show a lesion in the parenchyma of the lymph node with perfused blood vessels and no hypoxia. Dashed line shows edge of the lymph node. Scale bars = 100 μm. B) Higher magnification of pimonidazole staining in metastatic lymph node showing colocalization of cytokeratin and pimonidazole. Contralateral lymph node is non–tumor bearing. Dashed line shows edge of the lymph node. Scale bars = 50 μm. C) Quantification of pimonidazole and perfused vessel staining in metastatic lesions in the subcapsular sinus and lymph node parenchyma. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by two-tailed unpaired Student’s t test. D and E) Staining for CAIX, a marker of the cellular response to hypoxia, and CD31-positive blood vessels shows similar results to pimonidazole staining. Dashed line shows the outline of the metastatic lesions. Scale bars = 636 μm.

Hypoxia generally induces the production of vascular endothelial growth factor (VEGF). However, VEGF levels in control, contralateral, and metastatic lymph nodes were not different (4T1: control = 0.3 pg VEGF/mg protein, 95% CI = 0.2 to 0.4 pg VEGF/mg protein; contralateral = 0.4 pg VEGF/mg protein, 95% CI = 0.3 to 0.5 pg VEGF/mg protein; metastatic = 0.5 pg VEGF/mg protein, 95% CI = 0.2 to 0.8 pg VEGF/mg protein; Figure 5A; SCCVII: control = 0.4 pg VEGF/mg protein, 95% CI = 0.3 to 0.5 pg VEGF/mg protein; contralateral = 0.4 pg VEGF/mg protein, 95% CI = 0.3 to 0.5 pg VEGF/mg protein; metastatic = 0.4 pg VEGF/mg protein, 95% CI = 0.3 to 0.5 pg VEGF/mg protein; Figure 5B; and E0771: control = 0.3 pg VEGF/mg protein, 95% CI = 0.2 to 0.4 pg VEGF/mg protein; contralateral = 0.4 pg VEGF/mg protein, 95% CI = 0.3 to 0.5 pg VEGF/mg protein; metastatic = 0.4 pg VEGF/mg protein, 95% CI = 0.3 to 0.5 pg VEGF/mg protein; Figure 5C; all P values > .05 for each ANOVA containing these three lymph nodes types). Furthermore, levels of VEGF-C and VEGF-D were lower in metastatic and nonmetastatic tumor draining lymph nodes when compared with naïve lymph nodes (Supplementary Figure 6, C and D, http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online). Next, we screened for transcriptional changes in sprouting angiogenesis-related genes in lymph nodes with metastasis when compared with naïve lymph nodes. No pro-angiogenesis related genes were upregulated in metastatic lymph nodes, but thrombospondin-1 (Thbs-1) and TIMP-1—both of which are antiangiogenic—were upregulated (Figure 5D). We confirmed no change in Vegf levels (control = 0.24 VEGF/GAPDH, 95% CI = 0.06 to 0.42 VEGF/GAPDH; metastatic = 0.16 VEGF/GAPDH, 95% CI = 0.04 to 0.28 VEGF/GAPDH, P = .37) and the elevation in Thbs-1 in lymph node metastasis by quantitative polymerase chain reaction (qPCR) (control = 0.10 THBS-1/GAPDH, 95% CI = 0.05 to 0.15 THBS-1/GAPDH; metastatic = 0.38 THBS-1/GAPDH, 95% CI = 0.23 to 0.53 THBS-1/GAPDH; P = .001) (Figure 5E). Thrombospondin-1 (TSP-1) was specifically located surrounding the blood vessels of control, contralateral, and metastatic lymph nodes (Figure 5F), further defining the nonangiogenic phenotype associated with these vessels. Taken together, these data describe an environment lacking prosprouting angiogenesis stimuli and abundant in antiangiogenesis molecules, suggesting metastatic lesions in the lymph node do not induce nor rely upon sprouting angiogenesis during their early growth.

Figure 5.

Molecular signature of quiescent lymph node vasculature. A-C) Levels of vascular endothelial growth factor (VEGF) protein were measured in metastatic lymph nodes containing 4T1 (A), SCCVII (B), or E0771 (C) and compared with control and contralateral lymph nodes. D) Quantitative polymerase chain reaction (qPCR) transcriptional array for angiogenesis-related genes compared the transcriptional profile of a diaeresis lymph node to a tumor-bearing lymph node. Differentially transcribed genes were defined as having more than a four-fold change and a P value under .01 when comparing metastatic lymph nodes to diaeresis lymph nodes. E) Confirmation of the qPCR transcriptional array for the Vegf and Thbs1 genes. *P < .05. F) Dual immunofluorescence staining for CD31 (red) and TSP-1 (green) showed distinctive TSP-1 staining surrounding the blood vessels in diaeresis, contralateral, and metastatic lymph nodes. Scale bars = 100μm. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by one-way analysis of variance with Tukey’s Honestly Significant Difference post hoc test (A, B, and C) and two-tailed unpaired Student’s t test (E).

Blood Vessel Density in Metastatic Lymph Nodes From Colon Cancer and Head and Neck Cancer Patients

To confirm these findings in clinical specimens in a cancer where angiogenesis inhibitors have shown efficacy, we stained lymph nodes from 20 colon cancer patients with lymphatic metastasis for CD31 (Figure 6A; Supplementary Figure 7A, http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1available online). These patients did not have metastases on initial staging and went directly for surgical resection with no prior cancer-directed treatments (eg, chemotherapy, radiation therapy). We found that blood vessel densities in metastatic lymph nodes and large metastatic lesions where lymph node tissue was completely replaced with tumor cells were on average lower than those of tumor-negative lymph nodes (nonmetastatic- = 220 blood vessels/mm2, 95% CI = 172 to 268 blood vessels/mm2; metastatic = 135 blood vessels/mm2, 95% CI = 113 to 157 blood vessels/mm2; lymph node replaced by cancer = 104 blood vessels/mm2, 95% CI = 75 to 133 blood vessels/mm2; comparisons of either group of tumor-bearing to nonmetastatic lymph nodes: P < .001) (Figure 6, B and C). Furthermore, the vessel density inside metastatic lesions was statistically significantly lower than in the remaining lymph node tissue (metastatic lesion = 148 blood vessels/mm2, 95% CI = 124 to 172 blood vessels/mm2; nontumor area = 115 blood vessels/mm2, 95% CI = 95 to 135 blood vessels/mm2P = .03) (Figure 6, D and E). Accordingly, TSP-1 staining was also found to associate with lymph node blood vessels and to surround the gland-like structures formed by the cancer cells (Supplementary Figure 7B,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online), further suggesting that these vessels were not undergoing sprouting angiogenesis. Finally, the density of CD31-positive vessels was not dependent on the lesion size in the section, showing that vessel densities of macrometastases (clinically classified as lesions larger than 2mm in one direction[45]]) are the same as in micrometastases (Figure 6F). Blood vessel density and TSP-1 staining in specimens from head and neck cancer patients were similar to those from colon cancer patients (Supplementary Figure 7, C–G,http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online). Taken together, these data from two different patient populations support the concept that the growth of metastatic lesions in the lymph nodes is not dependent upon sprouting angiogenesis.

Figure 6.

Vascular density in metastatic lymph nodes from colon cancer patients. A) Representative images of nonmetastatic (n = 19) and metastatic (n = 39) lymph nodes as well as lymph node tumors in which no normal lymph node tissue remained (n = 9). The sections were stained with CD31 (brown) to identify blood vessels. Scale bars = 200 μm. Images of whole lymph node sections can be found in Supplementary Figure 7 (available online). B) The number of vessels per area as determined by CD31 staining was measured in metastatic lymph nodes and in lymph node tumors in which no normal lymph node tissue remained and compared with nonmetastatic lymph nodes. C) The fraction of lymph node area composed of CD31-positive vessels was similarly measured in metastatic lymph nodes and in lymph node tumors in which no normal lymph node tissue remained and compared with nonmetastatic lymph nodes. *P value was determined by Tukey’s Honestly Significant Difference post hoc test of analysis of variance model. D and E) Within a metastatic lymph node, vascular density (D) and vessel area fraction (E) were measured in the tumor and the nontumor area. * P value was determined by paired Student’s t test.F) Vessel density was not dependent on the lesion size. Data are presented as mean ± 95% confidence interval throughout figure.

Growth of Lymph Node Metastases With Antiangiogenic Treatment

To directly measure the response of lymph node metastases to antiangiogenic therapy in the CLNW, we began treatment when micrometastases were between 100 and 125 μm in diameter (5–10×10–3 mm3)—the stage when we found blood vessels surrounding lymph node metastases—with either a monoclonal VEGF receptor (VEGFR)-2–blocking antibody (DC101, ImClone Systems) or the pan-VEGFR small-molecule tyrosine kinase inhibitor sunitinib. We chose agents with differential mechanisms of VEGF pathway inhibition—monoclonal antibody vs tyrosine kinase inhibitor (TKI)—to understand whether our findings were agent specific. Measuring lymph node blood vessels using the CLNW and longitudinal multiphoton microscopy, the growth of lymph node metastases (Figure 7, A–C) and functional blood vessel volume density remained at similar levels during treatment with either DC101 or sunitinib when compared with untreated controls (vessel density: day 10: untreated = 1.2%, 95% CI = 0.7% to 1.7%; control = 0.7%, 95% CI = 0.1% to 1.3%; DC101 = 0.4%, 95% CI = 0.0% to 3.3%; sunitinib = 0.5%, 95% CI = 0.0% to 1.0%; ANOVA P = .34) (Figure 7D). These direct measurements, supported by previous endpoint studies,[9,17] suggest that inhibitors of sprouting angiogenesis as a class of drugs will not be effective in inhibiting the early phase of lymph node metastasis. In contrast, sunitinib—a pan-VEGF receptor TKI—reduced the elevated lymphatic vessel density found in early metastatic lymph nodes compared with PBS control (Supplementary Figure 8, http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online).

Figure 7.

Antiangiogenic therapy in the early growth of lymph node metastases. A) Representative intravital multiphoton microscopy images of spontaneous lymph node metastases treated with vehicle control, sunitinib, or the blocking monoclonal anti–VEGFR-2 antibody DC101. Tumor cells are shown in green and blood vessels in redScale bars = 200 μm. B) Primary tumors were of equal size at the time treatment began, when the lymph node micrometastases were 5–10×10–3 mm3C) The growth rate of the metastatic tumor in the lymph node was measured during antiangiogenesis therapy. D) The vessel density in metastatic lesions in the lymph node was measured during antiangiogenesis therapy. Biological replicates: untreated n = 15 (C), 12 (D), control (IgG = 2, PBS = 4) n = 6, sunitinib = 6, DC101 = 5. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by one-way analysis of variance with Tukey’s Honestly Significant Difference post hoc test (B and C) and two-tailed unpaired Student’s t test (D and E).

Blood Vessel Density of Lymph Node Metastasis From Patients Treated With Bevacizumab

Finally, we identified rectal cancer patients that received neoadjuvant chemoradiation and bevacizumab and a comparator cohort of rectal cancer patients who received only neoadjuvant chemoradiation, as previously described.[46,47] Despite downstaging of the primary tumor after neoadjuvant therapy, lymph node metastases were often found at the time of surgery and pathological evaluation. Comparing lymph node metastases from 10 patients in each group, we found no difference in the vessel density in lymph node metastases (no bevacizumab group mean = 257 vessels/mm2, 95% CI = 149 to 365 vessels/mm2; bevacizumab group mean = 327 vessels/mm2, 95% CI = 140 to 514 vessels/mm2P = .78) (Figure 8, A and B). The vascular density in the tumor lesions specifically was also not different between the groups (no bevacizumab group mean = 307 blood vessels/mm2, 95% CI = 186 to 428 vessels/mm2; bevacizumab group mean = 318 blood vessels/mm2, 95% CI = 118 to 518 vessels/mm2P = .60) (Figure 8, C and D). Metastatic lymph nodes showed lower vascular density than nonmetastatic nodes after neoadjuvant therapy (Figure 8, A and B), independent of whether bevacizumab was used. Finally, lymphatic vessel density was not different in metastatic and nonmetastatic lymph nodes when comparing patients who received bevacizumab to those who did not (Supplementary Figure 8, D and E, http://jnci.oxfordjournals.org/content/107/9/djv155/suppl/DC1 available online). These data provide the first clinical evidence for the lack of response of lymph node metastasis to antiangiogenic therapy.

Figure 8.

Vascular density in lymph node metastases in rectal cancer patients treated with bevacizumab. The number of CD31+ vessels per area (A) and the fraction of lymph node area composed of CD31+ vessels(B) were measured in nonmetastatic and metastatic lymph nodes in colorectal cancer (CRC) patients that received neoadjuvant chemoradiation (No Bev.) or neoadjuvant chemoradiation with bevacizumab (Bev.).P value was determined by two-tailed unpaired Student’s t test. C and D) Within the tumor area of metastatic lymph nodes, we measured vascular density (C) and vessel area fraction (D) in rectal cancer patients that received neoadjuvant chemoradiation (No Bev.) or neoadjuvant chemoradiation with bevacizumab (Bev.). P value was determined by two-tailed unpaired Student’s t test. Data are presented as mean ± 95% confidence interval.

Discussion

The main concept driving antiangiogenic therapy has been the hypothesis that tumors depend on new blood vessel growth. A critical observation made by longitudinal intravital microscopy in the CLNW is that metastatic lesions did not induce sprouting angiogenesis as they grew, in spite of the presence of hypoxia. Lesions that invaded into the blood vessel–rich lymph node parenchyma showed reduced hypoxia, suggesting that cancer cells survive in the lymph node by utilizing the existing lymph node vascular supply. The lack of VEGF, VEGF-C, and VEGF-D, along with the presence of TSP-1 surrounding lymph node blood vessels, provides a mechanism behind the lack of sprouting angiogenesis observed in lymph node metastases. A limitation of the use of longitudinal intravital microscopy is the limited imaging depth of 300 μm by multiphoton microscopy in the CLNW. To balance this, we used histological techniques, which allow full lymph node depth to be characterized but are limited in their ability to monitor the kinetic changes occurring as metastatic lesions grow in the lymph node. Using these complimentary techniques allowed better characterization of the growth of lymphatic metastases.

Our data show lymph node lymphangiogenesis is an early event in the natural history of cancer progression, in agreement with previous studies.[40,41,43] However, decreased lymphatic vessel density was found in macrometastatic lymph nodes, suggesting that the presence of the cancer cells in the lymph node causes lymphatic vessel regression. Furthermore, bevacizumab did not statistically significantly affect the lymphatic vasculature in patients. These data suggest that late intervention with antiangiogenic or antilymphangiogenic therapies after lymphatic vessel regression has begun in patients will show no effect on lymph node lymphatic vessels.

In patients, the observation that large metastatic lesions do not exhibit increased vascular density relative to those with micrometastases further suggests that sprouting angiogenesis is not required to sustain the growth of lymph node metastases. A limitation of our data is that we estimated lesion size based on the two-dimensional area available in the histological sections, so we are likely underestimating the size of the lesion. An additional limitation of our study is that we cannot rule out the contribution from different modes of new blood vessel formation in lymph node metastasis such as vasculogenesis, intussusception, vessel co-option, vascular mimicry, and tumor cell differentiation into endothelial cells.[20] The mechanisms of these alternative processes are not clearly defined, although VEGF and endothelial proliferation have been shown to contribute to these processes.[48–51] Our preclinical and clinical data, however, show that inhibitors targeting primarily sprouting angiogenesis will not inhibit the growth of metastases in the lymph node.

Predicted by recent genomic data,[38,39,52] we provide direct evidence that lymph node metastasis forms from multiple cells that disseminate from the primary tumor and suggest a fundamental difference in their formation compared with hematogenous metastases. Cancer cells that invade lymphatic vessels travel to the draining lymph node where they enter in locations defined by afferent lymphatic vessels. As such, lymph node metastasis can be reinforced by the continual arrival of new cells as they gain a foothold in their new microenvironment, leading to the spatially heterogeneous lesions imaged here and the genetically heterogeneous lesions documented previously.[38,39,52,53] In contrast, cells that metastasize through the blood spread out to different locations in an organ by the branching vasculature, leading to a higher probability of individually homogenous lesions. One can thus speculate that targeting a single genetic trait, unless ubiquitous in the primary tumor, may not be effective in eradicating lymph node metastases and any subsequent spread to distant sites.[39]

Using multiple spontaneous metastasis models, we show the first direct evidence that sprouting angiogenesis is not required in lymph node lesions during early metastatic growth. The lack of sprouting angiogenesis in lymph node metastases suggests an additional explanation for the poor outcomes of antiangiogenic therapy in adjuvant settings. As the lymph node is able to metabolically support rapid cellular expansion during an active immune response, it seems the existing vasculature of the lymph node is also able to support the growth of a nascent metastasis. Thus, the mechanisms of angiogenesis and the targets of clinically approved drugs are not active during this early step in cancer progression, suggesting that inhibitors of sprouting angiogenesis as a class will not be effective in treating lymph node metastases. Our novel preclinical models provide opportunities to uncover strategies to better control and eradicate disease in lymph nodes in metastatic cancer patients.

Gene Mutation Signals Poor Prognosis for Pancreatic Tumors

College of American Pathologists (CAP) 2015 Meeting

Neil Osterweil
http://www.medscape.com/viewarticle/852457

NASHVILLE, Tennessee — For patients with pancreatic neuroendocrine tumors, the presence of recently identified mutations in two key genes is a prognostic factor for poor outcome, researchers report.

“We found loss of nuclear expression in about 23% of the tumors that we studied, and this loss of expression was associated with worse tumors from the outset,” lead investigator Michelle Heayn, MD, a second-year pathology resident at the University of Pittsburgh Medical Center, told Medscape Medical News.

Pancreatic tumors with neuroendocrine histology frequently respond to chemotherapy and have a more favorable prognosis than the more common pancreatic adenocarcinomas. However, the mutations are associated with worse disease-free and disease-specific survival.

The results of the study were presented here at the College of American Pathologists 2015 Meeting.

The mutations — in the alpha-thalassemia mental retardation syndrome X-linked gene (ATRX) and the death-domain-associated protein gene (DAXX) — cause loss of expression of the proteins coded by ATRX and DAXX, Dr Heayn explained.

We found loss of nuclear expression in about 23% of the tumors that we studied.

To test whether these mutations had any prognostic significance, Dr Heayn and her colleagues used immunolabeling in surgically resected pancreatic neuroendocrine tumors from 303 patients. They then correlated the findings with patient demographics, pathologic features, disease-free survival, and disease-specific survival. Follow-up ranged from 1.6 to 18.8 years.

Of the 303 tumors, 69 (23%) had mutations in one or both genes. Tumors with a gene mutation had a larger mean diameter than tumors with intact gene expression (5.0 vs 2.4 cm), as well as a significantly higher histologic grade, more lymphovascular and perineural invasion, a more advanced T stage, greater lymph node involvement, more synchronous metastases, and more frequent disease recurrence (P < .01 for all comparisons).

In addition, the mutations were associated with shorter mean disease-free survival (5.6 vs 17.2 years;< .01) and shorter mean disease-specific survival (12.5 vs 17.7 years; P = .01).

On multivariate analysis that controlled for patient and tumor factors, the mutations were a significant predictor of shorter disease-free survival (P < .01), independent of tumor size, stage, histology, lymphovascular or perineural invasion, and lymph node status.

Dr Heayn and her colleagues are currently exploring whether there is an association between metastatic pancreatic cancer and these genetic mutations.

Metastatic Pancreatic Cancer

Patients with these mutations in their tumors should be followed more closely for recurrence or disease progression, Dr Heayn said. And in this subset of patients, there is the possibility of new targeted therapies.

These findings are very important, said Safia Salaria, MD, from the Vanderbilt University Medical Center in Nashville.

“There is so much heterogeneity in these tumors, and currently we are just using clinicopathologic features and the WHO-recommended Ki-67 labelling and white count,” she told Medscape Medical News.

“If we have something that can be an adjunct to that — immunohistochemistry to determine the loss of these genes — it’s definitely going to be something that will help us, especially in low-grade tumors,” she explained.

Staining for the expression of the genes could also help pathologists identify patients who are at higher risk for disease recurrence or metastasis but don’t have metastases at the time of primary resection, Dr Salaria said.

Microbiome May Predict Colon Cancer Tumor Mutational Status

Neil Osterweil

http://www.medscape.com/viewarticle/852544

BALTIMORE — Analysis of the microbiome surrounding colon cancer tumors could be used as a noninvasive screening test that is more sensitive and specific than fecal occult blood testing, according to the results of a new study.

“This is something that could be critical in colon cancer, because each tumor may have a different mutational landscape with different genes mutated, and that might have an effect on the microbiome,” said Ran Blekhman, PhD, from the University of Minnesota in Minneapolis.

The results of the study were presented here at the American Society of Human Genetics 2015.

Dr Blekhman and his colleagues looked at the genetic differences between healthy colon cells and tumor cells from adults with colorectal cancer, and found that specific tumor mutations are associated with the presence of specific bacteria in the gut.

For example, in people with an APC gene mutation, there is a strong association between familial adenomatous polyposis, a hereditary cancer syndrome, and an abundance of Fusobacterium, said Dr Blekhman.

He pointed out that his lab is the first to analyze the correlation between specific tumor mutations and the composition of the tumor microbiome.

More Mutations, More Diversity

The investigators used whole-exome sequencing to assess the protein-coding regions of tumors and microbiome profiling to characterize the microbiota in tumor biopsy specimens and normal colon tissue samples from 44 adults with colon cancer.

They found that the more mutations, the more varied the bacterial species in the tumor microbiome.

And for certain genes, there was a correlation between somatic mutations and changes in the abundance of specific microbes.

Other evidence of the correlation between bacteria and tumor was seen at the pathway level.

Loss-of-function mutations were detected in tumor glucose transport pathways and were strongly correlated with higher levels of energy utilization in the microbiome, said Dr Blekhman. This suggests that the tumor and the bacteria in its neighborhood are competing for bodily resources.

The investigators created a risk index that evaluated the correlation between microbes and each of several known tumor driver mutations. The index was able to accurately predict the presence of a loss-of-function mutation in ZFN717, a gene encoding for a zinc finger nuclease, part of a family of enzymes involved in DNA repair.

These findings suggest that it is possible to genetically classify tumors from fecal samples alone. Theoretically, this means that manipulation of the tumor microenvironment could be used to prevent or treat colon cancer, Dr Blekhman explained.

This study addresses, in part, the problem of “hidden heritability,” said Chris Gunter, PhD, from Emory University School of Medicine in Atlanta.

“If you look at cancer-sequencing studies now, they identify something like 10 possible driver mutations. We have not yet managed to predict what all the drivers and passengers will be,” she told Medscape Medical News.

“If this type of work can help us narrow down the list, that should add to our understanding of how cancer develops,” she said.

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Stem Cells and Cancer

Larry H. Bernstein, MD, FCAP, Curator

Leaders in Pharmaceutical Intelligence

Series E. 2; 8.09

Cancer cells programmed back to normal by US scientists

By Sarah Knapton, Science Editor

Scientists have turned cancerous cells back to normal by switching back on the process which stops normal cells from replicating too quickly. Cancer cells could be stopped from replicating after scientists found how to switch on the brakes.

http://www.telegraph.co.uk/news/science/science-news/11821334/Cancer-cells-programmed-back-to-normal-by-US-scientists.html

Cancer cells have been programmed back to normal by scientists in a breakthrough which could lead to new treatments and even reverse tumour growth.

For the first time aggressive breast, lung and bladder cancer cells have been turned back into harmless benign cells by restoring the function which prevents them from multiplying excessively and forming dangerous growths.

Scientists at the Mayo Clinic in Florida, US, said it was like applying the brakes to a speeding car.

So far it has only been tested on human cells in the lab, but the researchers are hopeful that the technique could one day be used to target tumours so that cancer could be ‘switched off’ without the need for harsh chemotherapy or surgery.

“We should be able to re-establish the brakes and restore normal cell function,” said Profesor Panos Anastasiadis, of the Department for Cancer Biology.

“Initial experiments in some aggressive types of cancer are indeed very promising.

“It represents an unexpected new biology that provides the code, the software for turning off cancer.”

Cells need to divide constantly to replace themselves. But in cancer the cells do not stop dividing leading to huge cell reproduction and tumour growth.

The scientists discovered that the glue which holds cells together is regulated by biological microprocessors called microRNAs. When everything is working normally the microRNAs instruct the cells to stop dividing when they have replicated sufficiently. They do this by triggering production of a protein called PLEKHA7 which breaks the cell bonds. But in cancer that process does not work.

Scientists discovered they could switch on cancer in cells by removing the microRNAs from cells and preventing them from producing the protein.

And, crucially they found that they could reverse the process switching the brakes back on and stopping cancer. MicroRNAs are small molecules which can be delivered directly to cells or tumours so an injection to increase levels could switch off disease.

“We have now done this in very aggressive human cell lines from breast and bladder cancer,” added Dr Anastasiadis.

“These cells are already missing PLEKHA7. Restoring either PLEKHA7 levels, or the levels of microRNAs in these cells turns them back to a benign state. We are now working on better delivery options.”

Cancer experts in Britain said the research solved a riddle that biologists had puzzled over for decades, why cells did not naturally prevent the proliferation of cancer.

“This is an unexpected finding,” said Dr Chris Bakal, a specialist in how cells change shape to become cancerous, at the Institute for Cancer Research in London.

“We have been trying to work out how normal cells might be suppressing cancer, and stopping dividing when they form contacts with each other, which has been a big mystery.

“Normal cells touch each other and form junctions then they shut down proliferation. If there is a way to turn that back on then that would be a way to stop tumours from growing.

“I think in reality it is unlikely that you could reverse tumours by reversing just one mechanism, but it’s a very interesting finding.”

Henry Scowcroft, Cancer Research UK’s senior science information manager, said: “This important study solves a long-standing biological mystery, but we mustn’t get ahead of ourselves.

“There’s a long way to go before we know whether these findings, in cells grown in a laboratory, will help treat people with cancer. But it’s a significant step forward in understanding how certain cells in our body know when to grow, and when to stop. Understanding these key concepts is crucial to help continue the encouraging progress against cancer we’ve seen in recent years.”

The research was published in the journal Nature Cell Biology.

Biomaterial Sponge-Like Impant Traps Spreading Cancer Cells

September 9, 2015 by mburatov http://wp.me/ptV19-1vG

Prof Lonnie Shea, from the Department of Biomedical Engineering at the University of Michigan and his team have designed a small sponge-like implant that has the ability to mop up cancer cells as they move through the body. This device has been tested in mice, but there is hope that the device could act as an early warning system in patients, alerting doctors to cancer spread. The sponge-like implant also seemed to stop rogue cancer cells from reaching other areas where they could establish the growth of new tumors. Shea and others published their findings in the journal Nature Communications.

According to Cancer Research UK, nine in 10 cancer deaths are caused by the disease-spreading to other areas of the body. Stopping the spread of cancer cells, or metastasis, is one of the ways to prevent cancers from becoming worse. Complicating this venture is the fact that cancer cells that circulate in the bloodstream are rare and difficult to detect.

Shea’s device is about 5mm or 0.2 inches in diameter and made of a “biomaterial” already approved for use in medical devices. So far, this implant has so far been tested in mice with breast cancer. Implantation experiments showed that it can be placed either in the abdominal fat or under the skin and that it tended to suck up cancer cells that had started to circulate in the body.

The implant mimicked a process known as chemoattraction in which cells that have broken free from a tumor are attracted to other areas in the body by immune cells. Shea and others found that these immune cells are drawn to the implant where they “set up shop.” This is actually a natural reaction to any foreign body, and the presence of the immune cells also attracts the cancer cells to the implant.

Initially, Shea and others labeled cancer cells with fluorescent proteins that caused them to glow under certain lights, which allowed them to be easily spotted. However, they eventually went on to use a special imaging technique that can distinguish between cancerous and normal cells. They discovered that they could definitively detect cancer cells that had been caught within the implant.

Unexpectedly, when they measured cancer cells that had spread in mice with and without the implant, they showed that the implant not only captured circulating cancer cells, but it also reduced the numbers of cancer cells present at other sites in the body.

Shea, said that he and his team were planning the first clinical trials in humans fairly soon: “We need to see if metastatic cells will show up in the implant in humans like they did in the mice, and if it’s a safe procedure and that we can use the same imaging to detect cancer cells.”

Shea and his coworkers are continuing their work in animals to determine what the outcomes if the spread of the cancer spread was detected at a very early stage, which is something that is presently not yet fully understood.

Lucy Holmes, Cancer Research UK’s science information manager, said: “We urgently need new ways to stop cancer in its tracks. So far this implant approach has only been tested in mice, but it’s encouraging to see these results, which could one day play a role in stopping cancer spread in patients.”

 

U of Penn Group Releases Hopeful Results of CAR T-Cells Trial

Sept 8, 2015 by mburatov

https://beyondthedish.wordpress.com/2015/09/08/u-of-penn-group-releases-hopeful-results-of-car-t-cells-trial/

Chimeric Antigen Receptor T-Cells (CART-cells) are a type of genetically engineered type of immune cell that represents one of the most promising avenues of cancer therapy. Such treatments can induce sustained remissions in patients with stubborn disease.

Studies with CART-cells have been tested in patients with relapsed and stubborn chronic lymphocytic leukemia (CLL). Now a new publication by Porter and others reports the results of a clinical trial that examined CART-cells as a treatment for blood-based cancers. This study reports that infused CART-cells were functional up to 4 years after treatment. Patients also achieved completely remission, and no patient who achieved complete remission relapsed, and no minimal residual disease was detected, suggesting that in a subset of patients, CAR T cells may drive disease eradication.

Patients enrolled in this study suffered from CLL and had a poor prognosis. The CART-cells employed in this study targeted the molecule CD19. Porter and others report the mature results of the treatment of 14 patients with relapsed and refractory CLL.

The patient’s own T-Cells were extracted from circulating blood, and genetically engineered to express a CD19-directed receptor. Patients received doses of 0.14 × 10[8] to 11 × 10[8] CTL019 cells. Patients were monitored for toxicity, response, expansion, and persistence of circulating CTL019 T cells.

The overall response rate in these heavily pretreated CLL patients was 8 of 14 (57%), and there were 4 complete remissions (CR) and 4 partial remissions (PR). The expansion of the CAR T-cells in culture correlated with clinical responses; the better the engineered T-cells grew in culture the better they performed in the Patient’s bodies. Furthermore, the CAR T-cells persisted and remained functional beyond 4 years in the first two patients achieving Complete Remission. None of the patients who experienced Complete Remission have relapsed.

All the patients who responded to the treatment developed “B cell aplastic” (abnormally low B-cell levels) and experienced cytokine release syndrome, which was part and partial of T cell proliferation.

Minimal residual disease was not detectable in patients who achieved Complete Remission, suggesting that disease eradication may be possible in some patients with advanced CLL.

 

New Method to Regulate Stem Cell Differentiation

GEN News Highlights Sep 2, 2015
http://www.genengnews.com/gen-news-highlights/new-method-developed-to-regulate-stem-cell-differentiation/81251707/

Researchers have developed a method that enables the regulation of a single gene’s behavior without changing the genome itself. [Professor Otonkoski Lab, University of Helsinki]

http://www.genengnews.com/Media/images/GENHighlight/thumb_Sep0915_UnivHelsinki_StemCellDifferentiationGraph3620321462.jpg

Scientists at the University of Helsinki in Finland say they have developed a new method that enables the activation of genes in a cell without changing the genome. Applications of the method include directing the differentiation of stem cells.

The method was developed by researchers Diego Balboa and Jere Weltner, who are working on their doctoral dissertations in the lab of  Timo Otonkoski, Ph.D., at the Meilahti medical campus of the University of Helsinki. The research study (“Conditionally Stabilized dCas9 Activator for Controlling Gene Expression in Human Cell Reprogramming and Differentiation”) was published in Stem Cell Reports.

The hottest topics in stem cell research at the moment are methods that can regulate the differentiation of cells. The differentiation process is based on how genes in a cell are activated and deactivated, so researchers are looking for ways to control the activation of the genes. The researchers dream of being able to activate and deactivate genes precisely at specific moments.

“We can produce undifferentiated stem cells from specialized cells, also known as iPS, or induced pluripotent stem cells, and we can regulate the differentiation of these cells by providing them with the right kinds of growth environments. However, we cannot control the differentiation process sufficiently. The process may go smoothly, but then at the very end, a single gene won’t activate at the necessary time, and the cell remains immature,” Dr. Otonkoski explains.

Researchers in Dr. Otonkoski’s laboratory have now developed a method that enables the regulation of a single gene’s behavior without changing the genome itself. The method employs CRISPR technology, but the regulation itself is controlled by the addition of chemicals. The desired gene is made receptive to the drug by introducing bits of RNA into the cell that will bind to the activator protein and the gene’s regulatory area. The gene will then activate in the desired way when the chemicals that regulates the activator protein are provided to the cell.

“In our research, we used two common antibiotics, doxycycline and trimethoprim, and these chemicals enabled us to regulate the expression of many genes precisely and effectively. The method worked on all cells we tested, including stem cells. We used human cells in our development,” continued Dr. Otonkoski, who emphasized that the method is currently being used in experimental models. It is far too early to discuss therapeutic applications.

“The basic idea has now been developed, and the method has been demonstrated to be viable, and I believe that it can become a very important research tool. In my laboratory we use the method to regulate the differentiation of stem cells, but it has many potential applications in other research fields, for example, in cancer biology.”

 

Single Cell Analysis (SCA): Expanding in Importance in Life Science Research — circa 2015

Technologies Impacting SCA and Driving Translation Towards Single Cell-based Diagnostics

GEN Sep 2, 2015  http://www.genengnews.com/insight-and-intelligence/single-cell-analysis-sca-expanding-in-importance-in-life-science-research-circa-2015/77900516/

The focus of this GEN Market & Tech Analysis report is Single Cell Analysis (SCA) Trends.

  • Select Biosciences performed a study of the en bloc Single Cell Analysis (SCA) space in August 2015 to reveal trends in this evolving field—the results from these analyses are presented in this GENReport
  • The field is evolving as it is permeating into life sciences research as well as diagnostics development — this represents the translation of SCA and is evidenced for instance by the increasing penetrance of circulating tumor cell (CTC) research in the SCA space
  • The field of SCA is intersecting with nucleic acid and protein characterizing approaches/technologies which suggests that the “cargo” of single cells is a current area of study
  • The utilization of microfluidics approaches in SCA is a key and growing theme and suggests that the use of microfluidics for single cell capture and interrogation is gaining momentum

Shedding Light On Century-Old Biochemical Mystery

Aug 20, 2015  http://www.technologynetworks.com/Metabolomics/news.aspx?ID=182141

Yale scientists have used magnetic resonance measurements to show how glucose is metabolized in yeast to answer the puzzle of the “Warburg Effect.”

Given plenty of glucose and oxygen, yeast and cancer cells do not burn it all to produce energy but convert much of it to the byproducts ethanol and lactate, respectively.

In the 1920s Nobel laureate Otto Heinrich Warburg asked why these cells were so wasteful of energy. He suggested that this seemingly inefficient cellular use of resources was a root cause of cancer, a hypothesis that has been the subject of research ever since.

Almost a century later, two Yale scientists have used magnetic resonance measurements showing how glucose is metabolized in yeast to answer the puzzle of the “Warburg Effect.” The production of these byproducts is a result of the cell’s need to keep its internal state constant during glucose consumption, they report.

This biochemical response is an example of homeostasis, a fundamental need of all life forms.

“It’s the cell’s way of saying it has enough to eat,” said Robert Shulman, professor emeritus of molecular biophysics and biochemistry.

In the 1980s, Shulman conducted pioneering studies of metabolism in yeast using magnetic resonance spectroscopy, a method then confined to the study of cells but now used routinely in patients.

More recently, Shulman and co-author Douglas Rothman, professor of diagnostic radiology and of biomedical engineering, reviewed the data applying new methods of analyzing metabolic control. They found key intermediate molecular steps involved in the conversion of glucose to ethanol as well as to ATP, the chief energy source of cells. When these molecular switches that maintained homeostasis were disabled by mutations, the cells died from accumulated excesses of both byproducts and ATP.

This chemical balancing act explains why yeast and likely cancer cells do not convert all available fuel to energy that they could use to divide and flourish.

“Cancer cells have to survive first,” Rothman said.

Shulman and Rothman point out that their results open a new direction for cancer researchers — identifying metabolic homeostasis mechanisms and targeting them for treatment.

“By taking another look at the in vivo data available from magnetic resonance experiments, I think we can revitalize research efforts in a host of areas,” Shulman said.

Orchestrating Organoids

A guide to crafting tissues in a dish that reprise in vivo organs

By Kelly Rae Chi | Sep 1, 2015 http://www.the-scientist.com//?articles.view/articleNo/43842/title/Orchestrating-Organoids/

In 2009, at the Hubrecht Institute in Utrecht, Netherlands, Hans Clevers and postdoc Toshiro Sato took adult stem cells from the mouse intestine and created the first mini-guts they called organoids—three-dimensional organized clusters of cells that would allow the researchers to glean new insights into the biology of gut health and disease, including colorectal cancer.

This method inspired many other scientists, working with both mouse and human tissues, to create a rapidly expanding palette of organoids that now includes kidney, brain, liver, prostate, and pancreas. These cultured clumps are tiny enough to be sustained without a blood supply, but large and diverse enough in their cell compositions to tell us something about tissue development and whole-organ physiology.

A typical organoid protocol starts with isolated embryonic or pluripotent stem cells. Scientists culture the cells in a proteinaceous matrix (such as Matrigel) that supports three-dimensional growth. After a set period of time the organoids grow mature enough for study, or for engrafting into a mouse to allow them to further develop. Researchers then harvest the organoids and slice them for immunohistochemistry, funnel them through a flow cytometer to study their cell surface markers, or blend them for PCR.

Of course, the devil’s in the details. Although the field of organoid research is maturing rapidly (see “2013’s Big Advances in Science,” The Scientist, December 24, 2013), with some organoids already moving into clinical studies to test drug efficacy, culture methods are still in their infancy, says Michael Shen, professor of medicine and of genetics and development at Columbia University in New York City. “Certainly there are different ways to pursue organoid culture, and some of these are just beginning to be explored. I don’t think we’re at the point yet where this is all entirely cookbook.”

The Scientist talked with researchers about how they’re producing organoids, and what beginners should know. Here’s what we learned.

BRAIN BEADS
Researcher: Madeline Lancaster, group leader, MRC Laboratory of Molecular Biology, Cambridge, U.K.

Project: Understanding early brain development and disease using organoids cultured from human stem cells

Background: In 2013, as a postdoctoral researcher in the lab of Jürgen Knoblich at the Institute of Molecular Biotechnology in Vienna, Austria, Lancaster developed organoids from neural stem cells that she had been studying in 2-D culture conditions. She used the method to coax human induced pluripotent stem cells into brain organoids in order to understand the biology of microcephaly, a disorder that is difficult to re-create in animal models (Nature, 501:373-79, 2013).

Researchers have adopted Lancaster’s methods to create models of embryonic brain development, analogous to what happens in the first trimester of pregnancy, and to probe the molecular mechanisms of brain disorders, including autism, schizophrenia, and neurodegenerative diseases such as Parkinson’s and Alzheimer’s.

Getting started: The group’s protocol addresses some of the common questions asked by new users and provides photos showing the appearance of healthy organoids (Nat Protoc, 9:2329-40, 2014).

For those well versed in cell and tissue culture, the time and financial investment required to delve into organoids is minimal, Lancaster says. You need two main things: Matrigel (the supportive structure that allows the organoids to develop into more complex tissue) and equipment that will allow you to agitate the organoids to enhance nutrient and oxygen exchange in the media, making bigger organoids possible. If you don’t have a spinning bioreactor, you can use an orbital shaker set inside a standard tissue culture incubator.

Considerations: You should closely characterize the first few batches using RT-PCR or immunofluorescence to check for the expression of certain genes that indicate the organoids are indeed brain cells, Lancaster says.

Researchers studying neurodegeneration might consider examining their organoids starting at about four months. Although the organoids survive for up to 15 months, by that time they don’t look healthy. They start to decline at around six or seven months, as the neurons begin to disappear and are replaced by glia.

Tip: It takes some time and practice to develop an eye for healthy organoids. A good way to learn is to take pictures of your organoids as they develop. “You can always look back and say, ‘Oh, at that point I think it started going bad,’” Lancaster says.

Cost: Roughly $150 per organoid (not including equipment), according to Lancaster’s calculations

Looking ahead: Lancaster has already tweaked the method to improve the reproducibility, using a combination of timing and media formulations, and some new additives. She expects to publish a revised protocol by the end of the year.

GUTSY GLOBS
INTIMATING INTESTINE: Mini-gut methods are the most established of organoid protocols. Proliferating epithelial cells in small intestinal aggregations from mouse (green, left) and human (pink, right) will pave the way for patient-specific organoids.COURTESY OF HELMRATH LABResearcher: Maxime Mahé, postdoctoral research fellow inMichael Helmrath’s lab at Cincinnati Children’s Hospital Medical Center, Ohio

Project: Understanding gastrointestinal development and homeostasis and generating patient-specific organoids for study

Background: The intestinal epithelial layer is made up of tiny, slender projections, called villi, resembling the strands of a shag carpet. The nooks formed at the bases of the villi, known as crypts, are home to intestinal stem cells responsible for constant renewal of the intestinal lining. Building on Sato’s protocol, Mahé added two new twists: he used manual dissection to extract the crypts, rather than shaking the tissue to dissociate the cells; and he added a small-molecule activator of the Wnt3A pathway to boost expansion of the cells (Curr Protoc Mouse Biol, 3:217-40, 2013).

Helmrath’s group grew such “enteroids” from intestinal stem cells isolated from the crypts of surgically removed human intestine. In principle, such organoids could be developed from the tissue of specific patients for diagnostic and clinical uses. A video protocol is available in the Journal of  Visualized Experiments (doi: 10.3791/52483, 2015).

Getting started: It takes five or six attempts to get comfortable with the procedure, especially mastering the hardest part: the initial dissection. “The tissue is not always the same; it’s not something you can standardize,” Mahé says. “Sometimes you get a high number of crypts, sometimes you have a few.”

Tip: Many questions about cell proliferation, migration, and differentiation can be answered using in vitro organoids, Mahé says. “You save time, you save money, you save animals as well.” After that, you might consider moving into an animal model, depending on your goals: for example, to see muscle development, you should work in vivo, Mahé adds.

Looking ahead: The group is still working to be able to efficiently engraft human adult intestinal stem cell–derived organoids into mice. Although their first attempts were unsuccessful, they have since generated organoids for research from human embryonic stem cells (ESCs) and human induced pluripotent stem cells (iPSCs) derived by reprogramming fibroblasts. When organoids created from the either type of pluripotent stem cells are engrafted into immunodeficient mice to allow the cells to mature further, they develop into a human intestine (Nat Med, 20:1310-14, 2014), which may eventually lead to bioengineering a custom human intestine.

Cost: The Helmrath group spends roughly $150/sample in reagents to culture their organoids for a month. The medical center’s Pluripotent Stem Cell Facility provides training for a fee, and sells human intestinal organoids for roughly $400/plate (which contains 20–30 organoids).

B-CELL BALLS
PROSTRATE PROGRESS: Researchers have grown prostate organoids that consist of basal cells (green/blue) and luminal cells (red/blue).MAHO SHIBATAResearcher: Ankur Singh, assistant professor of mechanical and aerospace engineering, Cornell University

Project: In vitro modeling of immune reactions in mice

Background: When naive B cells in the body are exposed to antigens, they form clumps of cells called germinal centers in a lymph node or the spleen, where they proliferate, mutate to generate high-affinity antibodies, and undergo clonal expansion. Until now, this process has been difficult to recapitulate in vitro. Adding the necessary (stromal) support cells to primary naive B cells and culturing them in 2-D does not enable them to differentiate into cells resembling those from germinal centers, Singh says. Unlike stem cells, naive B cells do not tend to grow in clusters, so they need a little extra help.

Rather than using the conventional Matrigel for 3-D culture, Singh and his collaborators developed a gelatin and silicate-nanoparticle mix that mimics the softness of the body’s lymphoid organs. Within four to six days, the B cells in these organoids mature—100 times faster than B cells in 2-D culture—and produce two classes of antibodies important for fighting infections. The scientists use collagenase to dissolve the gel and harvest the organoid’s cells for analysis using flow cytometry. These new germinal center organoids were described this year in Biomaterials (63:24-34).

Getting started: Making the gelatin-nanoparticle mix is as easy as making Jell-O at home, Singh says, and the ingredients are commercially available. You’ll need experience with animal dissection (the necessary starting point is isolation of naive B cells from the spleen) and with cell culture. Once these techniques have been mastered, it takes roughly one week to get your first batch of organoids with mature antibody-producing cells.

Considerations: Singh’s group has already determined an optimal gelatin-nanoparticle ratio (2% gelatin/1.5% nanoparticle), but if you you’re using genetically mutated B cells, you may need to tweak the ratios. “It can be easily tuned,” Singh says.

Tip: After four days of incubating the cells with gel, you will see dark spots—a sign that the cells are proliferating and that you’re on the right track.

Cost: Not including the cost of generating immortalized stromal cell lines, it costs roughly $1 to produce one germinal center.

Looking ahead: Eventually, Singh’s group hopes to adapt the technique for use with patient-specific stem cells, though it has proven challenging to produce immune cells from stem cells. “It’s a very complicated process,” says Singh, “[but] it will happen one day in the context of this system.”

PROSTATE PELLETS
Researcher: Michael Shen, professor of medicine and of genetics and development, Columbia University Medical Center, New York

Project: Understanding basic prostate regeneration and prostate cancer

Background: In 2009, Shen’s group discovered a rare population of stem cells from which prostate cancer can originate (Nature, 461:495-500, 2009). Calling them CARNS, for castration-resistant Nkx3.1-expressing cells, the group knew they would face challenges culturing the cells because they are a type of luminal epithelial cell, which had historically proven difficult to expand using 2-D methods. “We thought if any type of approach would succeed it would be 3-D,” Shen recalls.

Through a trial-and-error approach, postdoctoral researcher Chee Wai Chua eventually converted mouse CARNS into organoids (Nat Cell Biol, 16:951-61, 2014). The resulting cell types and tissue architecture resembled those characteristic of normal prostate epithelium. The researchers then engrafted the organoids into mice to generate prostatic tissues.

Getting started: Shen’s group has made their method available via the Nature Protocol Exchange. The most difficult part for beginners is the initial tissue-dissociation step, which is typical of any organoid protocol. “To work out the details of how to do this is not straightforward,” Shen says. “In our case, we’re still working on this. We’re continually seeking to improve dissociation conditions.”

Considerations: When applied to the prostate, Clevers’s conditions seem to favor the growth of a different type of prostate cell known as a basal cell, though his group also grew luminal cells. Shen’s conditions are less defined than those of Clevers, using serum instead of specific growth factors. Shen’s group doesn’t know exactly which growth factors in the serum drive organoid growth and development.

Tip: If you are making the organoids from normal prostate for the first time, you might consider assessing their response to androgen deprivation. They should lose expression of Nkx3.1 in response to this condition.

Cost: It costs $1 or less for one mouse prostate organoid (not counting animal, equipment or labor costs).

Looking ahead: The group has been able to create organoids derived from human prostate cells, but determining the ideal conditions for these cells is still a work in progress, Shen says.

Tags

techniquesorganoidsdisease/medicine and 3-D cell culture

Aurelian Udristioiu commented on your update

“The human body emits low levels light, heat, and acoustical energy, these wavelengths of radiations having the electrical and magnetic properties and may also to be transformed in kinds of energy that cannot be easily defined by classical physical sciences and chemistry. In last time most researches has focused on electromagnetic aspects of the bio-magnetic field Bio-energetic fluids can be used in technology of preparation of drugs, from homeopath medicine and in laboratory medicine by the changes of pH in liquid medium with cultivated stem cells for to prolong the span life of cells, in view of cell-stem transplantation in chronic diseases. ”

Umbilical Cord Blood Contains c-kit+ Cells that Can Differentiate into Heart-like Cells

https://beyondthedish.wordpress.com/2015/09/10/umbilical-cord-blood-contains-c-kit-cells-that-can-differentiate-into-heart-like-cells/

Directed Neural Differentiation of Induced Pluripotent Stem Cells in the Marmoset

Peter J. Hornsby Ph.D. | 10th-Sep-2015

http://medical.wesrch.com/paper-details/pdf-ME1XXFT06ILUR-directed-neural-differentiation-of-induced-pluripotent-stem-cells-in-the-marmoset#page1

Description: Personalized cell therapy: The marmoset as a model- Before personalized cell therapy is used in humans, need to move beyond rodent models, Beyond rodents, nonhuman primates play key roles, Within nonhuman primates, the marmoset is a suitable size and life span for stem cell studies, Has been used in drug studies and in disease models, e.g. Parkinson’s disease, The marmoset was the first nonhuman primate to have transgenics with germline transmission, The second nonhuman primate (after the rhesus macaque) for which induced pluripotent stem cells were derived (our work, 2010).

DMSO treatment/differentiation: Conclusions- Despite some differences in growth characteristics of 3 marmoset iPS cell lines, all can be directed to a uniform pattern of neural differentiation by prior exposure to 24 h DMSO, The optimal DMSO concentration should be determined for each cell line, Therefore we should be able to differentiate any given (newly created) iPS cell population “on demand” by a protocol similar to the one used here.

Progress so far; next step- Marmoset iPS cells generated by a reproducible reprogramming method, Many marmoset iPS cell lines continuously grown for >1 year – immortal; maintain pluripotency, Rapid differentiation into the neural lineage using combinations of drugs with iterative testing, Rapid reprogramming of samples from living individuals, Rapid differentiation of living individual iPS cells. .

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Pathway Specific Targeting in Anticancer Therapies

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

 

7.7 Pathway specific targeting in anticancer therapies

7.7.1 Structural basis for the allosteric inhibitory mechanism of human kidney-type glutaminase (KGA) and its regulation by Raf-Mek-Erk signaling in cancer cell metabolism

7.7.2 Sonic hedgehog (Shh) signaling promotes tumorigenicity and stemness via activation of epithelial-to-mesenchymal transition (EMT) in bladder cancer.

7.7.3 Differential activation of NF-κB signaling is associated with platinum and taxane resistance in MyD88 deficient epithelial ovarian cancer cells

7.7.4 Activation of apoptosis by caspase-3-dependent specific RelB cleavage in anticancer agent-treated cancer cells

7.7.5 Identification of Liver Cancer Progenitors Whose Malignant Progression Depends on Autocrine IL-6 Signaling

7.7.6 Acetylation Stabilizes ATP-Citrate Lyase to Promote Lipid Biosynthesis and Tumor Growth

7.7.7 Monoacylglycerol Lipase Regulates a Fatty Acid Network that Promotes Cancer Pathogenesis

7.7.8 Pirin regulates epithelial to mesenchymal transition and down-regulates EAF/U19 signaling in prostate cancer cells

7.7.9 O-GlcNAcylation at promoters, nutrient sensors, and transcriptional regulation

 

7.7.1 Structural basis for the allosteric inhibitory mechanism of human kidney-type glutaminase (KGA) and its regulation by Raf-Mek-Erk signaling in cancer cell metabolism

Thangavelua, CQ Pana, …, BC Lowa, and J. Sivaramana
Proc Nat Acad Sci 2012; 109(20):7705–7710
http://dx.doi.org:/10.1073/pnas.1116573109

Besides thriving on altered glucose metabolism, cancer cells undergo glutaminolysis to meet their energy demands. As the first enzyme in catalyzing glutaminolysis, human kidney-type glutaminase isoform (KGA) is becoming an attractive target for small molecules such as BPTES [bis-2-(5 phenylacetamido-1, 2, 4-thiadiazol-2-yl) ethyl sulfide], although the regulatory mechanism of KGA remains unknown. On the basis of crystal structures, we reveal that BPTES binds to an allosteric pocket at the dimer interface of KGA, triggering a dramatic conformational change of the key loop (Glu312-Pro329) near the catalytic site and rendering it inactive. The binding mode of BPTES on the hydrophobic pocket explains its specificity to KGA. Interestingly, KGA activity in cells is stimulated by EGF, and KGA associates with all three kinase components of the Raf-1/Mek2/Erk signaling module. However, the enhanced activity is abrogated by kinase-dead, dominant negative mutants of Raf-1 (Raf-1-K375M) and Mek2 (Mek2-K101A), protein phosphatase PP2A, and Mek-inhibitor U0126, indicative of phosphorylation-dependent regulation. Furthermore, treating cells that coexpressed Mek2-K101A and KGA with suboptimal level of BPTES leads to synergistic inhibition on cell proliferation. Consequently, mutating the crucial hydrophobic residues at this key loop abrogates KGA activity and cell proliferation, despite the binding of constitutive active Mek2-S222/226D. These studies therefore offer insights into (i) allosteric inhibition of KGA by BPTES, revealing the dynamic nature of KGA’s active and inhibitory sites, and (ii) cross-talk and regulation of KGA activities by EGF-mediated Raf-Mek-Erk signaling. These findings will help in the design of better inhibitors and strategies for the treatment of cancers addicted with glutamine metabolism.

The Warburg effect in cancer biology describes the tendency of cancer cells to take up more glucose than most normal cells, despite the availability of oxygen (12). In addition to altered glucose metabolism, glutaminolysis (catabolism of glutamine to ATP and lactate) is another hallmark of cancer cells (23). In glutaminolysis, mitochondrial glutaminase catalyzes the conversion of glutamine to glutamate (4), which is further catabolized in the Krebs cycle for the production of ATP, nucleotides, certain amino acids, lipids, and glutathione (25).

Humans express two glutaminase isoforms: KGA (kidney-type) and LGA (liver-type) from two closely related genes (6). Although KGA is important for promoting growth, nothing is known about the precise mechanism of its activation or inhibition and how its functions are regulated under physiological or pathophysiological conditions. Inhibition of rat KGA activity by antisense mRNA results in decreased growth and tumorigenicity of Ehrlich ascites tumor cells (7), reduced level of glutathione, and induced apoptosis (8), whereas Myc, an oncogenic transcription factor, stimulates KGA expression and glutamine metabolism (5). Interestingly, direct suppression of miR23a and miR23b (9) or activation of TGF-β (10) enhances KGA expression. Similarly, Rho GTPase that controls cytoskeleton and cell division also up-regulates KGA expression in an NF-κB–dependent manner (11). In addition, KGA is a substrate for the ubiquitin ligase anaphase-promoting complex/cyclosome (APC/C)-Cdh1, linking glutaminolysis to cell cycle progression (12). In comparison, function and regulation of LGA is not well studied, although it was recently shown to be linked to p53 pathway (1314). Although intense efforts are being made to develop a specific KGA inhibitor such as BPTES [bis-2-(5-phenylacetamido-1, 2, 4-thiadiazol-2-yl) ethyl sulfide] (15), its mechanism of inhibition and selectivity is not yet understood. Equally important is to understand how KGA function is regulated in normal and cancer cells so that a better treatment strategy can be considered.

The previous crystal structures of microbial (Mglu) and Escherichia coli glutaminases show a conserved catalytic domain of KGA (1617). However, detailed structural information and regulation are not available for human glutaminases especially the KGA, and this has hindered our strategies to develop inhibitors. Here we report the crystal structure of the catalytic domain of human apo KGA and its complexes with substrate (L-glutamine), product (L-glutamate), BPTES, and its derived inhibitors. Further, Raf-Mek-Erk module is identified as the regulator of KGA activity. Although BPTES is not recognized in the active site, its binding confers a drastic conformational change of a key loop (Glu312-Pro329), which is essential in stabilizing the catalytic pocket. Significantly, EGF activates KGA activity, which can be abolished by the kinase-dead, dominant negative mutants of Mek2 (Mek2-K101A) or its upstream activator Raf-1 (Raf-1-K375M), which are the kinase components of the growth-promoting Raf-Mek2-Erk signaling node. Furthermore, coexpression of phosphatase PP2A and treatment with Mek-specific inhibitor or alkaline phosphatase all abolished enhanced KGA activity inside the cells and in vitro, indicating that stimulation of KGA is phosphorylation dependent. Our results therefore provide mechanistic insights into KGA inhibition by BPTES and its regulation by EGF-mediated Raf-Mek-Erk module in cell growth and possibly cancer manifestation.

Structures of cKGA and Its Complexes with L-Glutamine and L-Glutamate.
The human KGA consists of 669 amino acids. We refer to Ile221-Leu533 as the catalytic domain of KGA (cKGA) (Fig. 1A). The crystal structures of the apo cKGA and in complex with L-glutamine or L-glutamate were determined (Table S1). The structure of cKGA has two domains with the active site located at the interface. Domain I comprises (Ile221-Pro281 and Cys424 -Leu533) of a five-stranded anti-parallel β-sheet (β2↓β1↑β5↓β4↑β3↓) surrounded by six α-helices and several loops. The domain II (Phe282-Thr423) mainly consists of seven α-helices. L-Glutamine/L-glutamate is bound in the active site cleft (Fig. 1B and Fig. S1B). Overall the active site is highly basic, and the bound ligand makes several hydrogen-bonding contacts to Gln285, Ser286, Asn335, Glu381, Asn388, Tyr414, Tyr466, and Val484 (Fig. 1C and Fig. S1C), and these residues are highly conserved among KGA homologs (Fig. S1D). Notably, the putative serine-lysine catalytic dyad (286-SCVK-289), corresponding to the SXXK motif of class D β-lactamase (17), is located in close proximity to the bound ligand. In the apo structure, two water molecules were located in the active site, one of them being displaced by glutamine in the substrate complex. The substrate side chain is within hydrogen-bonding distance (2.9 Å) to the active site Ser286. Other key residues involved in catalysis, such as Lys289, Tyr414, and Tyr466, are in the vicinity of the active site. Lys289 is within hydrogen-bonding distance to Ser286 (3.1 Å) and acts as a general base for the nucleophilic attack by accepting the proton from Ser286. Tyr466, which is close to Ser286 and in hydrogen-bonding contact (3.2 Å) with glutamine, is involved in proton transfer during catalysis. Moreover, the carbonyl oxygen of the glutamine is hydrogen-bonded with the main chain amino groups of Ser286 and Val484, forming the oxyanion hole. Thus, we propose that in addition to the putative catalytic dyad (Ser286 XX Lys289), Tyr466 could play an important role in the catalysis (Fig. 1Cand Fig. S2).

structure of the cKGA-L-glutamine complex

structure of the cKGA-L-glutamine complex

http://www.pnas.org/content/109/20/7705/F1.medium.gif

Fig. 1.  Schematic view and structure of the cKGA-L-glutamine complex. (A) Human KGA domains and signature motifs (refer to Fig. S1A for details). (B) Structure of the of cKGA and bound substrate (L-glutamine) is shown as a cyan stick. (C) Fourier 2Fo-Fc electron density map (contoured at 1 σ) for L-glutamine, that makes hydrogen bonds with active site residues are shown.

Allosteric Binding Pocket for BPTES. The chemical structure of BPTES has an internal symmetry, with two exactly equivalent parts including a thiadiazole, amide, and a phenyl group (Fig. S3A), and it equally interacts with each monomer. The thiadiazole group and the aliphatic linker are well buried in a hydrophobic cluster that consists of Leu321, Phe322, Leu323, and Tyr394 from both monomers, which forms the allosteric pocket (Fig. 2 B–E). The side chain of Phe322 is found at the bottom of the allosteric pocket. The phenyl-acetamido moiety of BPTES is partially exposed on the loop (Asn324-Glu325), where it interacts with Phe318, Asn324, and the aliphatic part of the Glu325 side chain. On the basis of our observations we synthesized a series of BPTES-derived inhibitors (compounds2–5) (Fig. S3 AF and SI Results) and solved their cocrystal structure of compounds 2–4. Similar to BPTES, compounds 24 all resides within the hydrophobic cluster of the allosteric pocket (Fig. S3 CF).

Fig. 2. Structure of cKGA: BPTES complex and the allosteric binding mode of BPTES.

Allosteric Binding of BPTES Triggers Major Conformational Change in the Key Loop Near the Active Site.  The overall structure of these inhibitor complexes superimposes well with apo cKGA. However, a major conformational change at the Glu312 to Pro329 loop was observed in the BPTES complex (Fig. 2F). The most conformational changes of the backbone atoms that moved away from the active site region are found at the center of the loop (Leu316-Lys320). The backbone of the residues Phe318 and Asn319 is moved ≈9 Å and ≈7 Å, respectively, compared with the apo structure, whereas the side chain of these residues moved ≈14 Å and ≈12 Å, respectively. This loop rearrangement in turn brings Phe318 closer to the phenyl group of the inhibitor and forms the inhibitor binding pocket, whereas in the apo structure the same loop region (Leu316-Lys320) was found to be adjacent to the active site and forms a closed conformation of the active site.

Binding of BPTES Stabilizes the Inactive Tetramers of cKGA.  To understand the role of oligomerization in KGA function, dimers and tetramers of cKGA were generated using the symmetry-related monomers (Fig. 2 A–E and Fig. S4 D and E). The dimer interface in the cKGA: BPTES complex is formed by residues from the helix Asp386-Lys398 of both monomers and involves hydrogen bonding, salt bridges, and hydrophobic interactions (Phe389, Ala390, Tyr393, and Tyr394), besides two sulfate ions located in the interface (Fig. 2E). The dimers are further stabilized by binding of BPTES, where it binds to loop residues (Glu312-Pro329) and Tyr394 from both monomers (Fig. 2 D and E). Similarly, residues from Lys311-Asn319 loop and Arg454, His461, Gln471, and Asn529-Leu533 are involved in the interface with neighboring monomers to form the tetramer in the BPTES complex.

BPTES Induces Allosteric Conformational Changes That Destabilize Catalytic Function of KGA

Fig. 3A shows that 293T cells overexpressing KGA produced higher level of glutamate compared with the vector control cells. Most significantly, all of these mutants, except Phe322Ala, greatly diminished the KGA activity.

Fig. 3. Mutations at allosteric loop and BPTES binding pocket abrogate KGA activity and BPTES sensitivity.

Raf-Mek-Erk Signaling Module Regulates KGA Activity. Because KGA supports cell growth and proliferation, we first validated that treatment of cells with BPTES indeed inhibits KGA activity and cell proliferation (Fig. S5 A–D and SI Results). Next, as cells respond to various physiological stimuli to regulate their metabolism, with many of the metabolic enzymes being the primary targets of modulation (18), we examined whether KGA activity can be regulated by physiological stimuli, in particular EGF, which is important for cell growth and proliferation. Cells overexpressing KGA were made quiescent and then stimulated with EGF for various time points. Fig. 4A shows that the basal KGA activity remained unchanged 30 min after EGF stimulation, but the activity was substantially enhanced after 1 h and then gradually returned to the basal level after 4 h. Because EGF activates the Raf-Mek-Erk signaling module (19), treatment of cells with Mek-specific inhibitor U0126 could block the enhanced KGA activity with parallel inhibition of Erk phosphorylation (Fig. 4A). Interestingly, such Mek-induced KGA activity is specific to EGF and lysophosphatidic acid (LPA) but not with other growth factors, such as PDGF, TGF-β, and basic FGF (bFGF), despite activation of Mek-Erk by bFGF (Fig. S6A).

The results show that KGA could interact equally well with the wild-type or mutant forms of Raf-1 and Mek2 (Fig. 4C). Importantly, endogenous Raf-1 or Erk1/2, including the phosphorylated Erk1/2 (Fig. 4 C and D), could be detected in the KGA complex. Taken together, these results indicate that the activity of KGA is directly regulated by Raf-Mek-Erk downstream of EGF receptor. To further show that Mek2-enhanced KGA activity requires both the kinase activity of Mek2 and the core residues for KGA catalysis, wild-type or triple mutant (Leu321Ala/Phe322Ala/Leu323Ala) of KGA was coexpressed with dominant negative Mek2-KA or the constitutive active Mek2-SD and their KGA activities measured. The result shows that the presence of Mek2-KA blocks KGA activity, whereas the triple mutant still remains inert even in the presence of the constitutively active Mek2 (Fig. 4E), and despite Mek2 binding to the KGA triple mutant (Fig. S7B). Consequently, expressing triple mutant did not support cell proliferation as well as the wild-type control (Fig. S7C).

Fig. 4. EGFR-Raf-Mek-Erk signaling stimulates KGA activity.

When cells expressing both KGA and Mek2-K101A were treated with subthreshold levels of BPTES, there was a synergistic reduction in cell proliferation (Fig. S6C and SI Results). Lastly, to determine whether regulation of KGA by Raf-Mek-Erk depends on its phosphorylation status, cells were transfected with KGA with or without the protein phosphatase PP2A and assayed for the KGA activity. PP2A is a ubiquitous and conserved serine/threonine phosphatase with broad substrate specificity. The results indicate that KGA activity was reduced down to the basal level in the presence of PP2A (Fig. 5A). Coimmunoprecipitation study also revealed that KGA interacts with PP2A (Fig. 5B), suggesting a negative feedback regulation by this protein phosphatase. Furthermore, treatment of immunoprecipitated and purified KGA with calf-intestine alkaline phosphatase (CIAP) almost completely abolished the KGA activity in vitro (Fig. S6D). Taken together, these results indicate that KGA activity is regulated by Raf-Mek2, and KGA activation by EGF could be part of the EGF-stimulated Raf-Mek-Erk signaling program in controlling cell growth and proliferation (Fig. 5C).

KGA activity is regulated by phosphorylation

KGA activity is regulated by phosphorylation

http://www.pnas.org/content/109/20/7705/F5.medium.gif

Fig. 5. KGA activity is regulated by phosphorylation. (C) Schematic model depicting the synergistic cross-talk between KGA-mediated glutaminolysis and EGF-activated Raf-Mek-Erk signaling. Exogenous glutamine can be transported across the membrane and converted to glutamate by glutaminase (KGA), thus feeding the metabolite to the ATP-producing tricarboxylic acid (TCA) cycle. This process can be stimulated by EGF receptor-mediated Raf-Mek-Erk signaling via their phosphorylation-dependent pathway, as evidenced by the inhibition of KGA activity by the kinase-dead and dominant negative mutants of Raf-1 (Raf-1-K375M) and Mek2 (Mek2-K101A), protein phosphatase PP2A, and Mek-specific inhibitor U0126. Consequently, inhibiting KGA with BPTES and blocking Raf-Mek pathway with Mek2-K101A provide a synergistic inhibition on cell proliferation.

Small-molecule inhibitors that target glutaminase activity in cancer cells are under development. Earlier efforts targeting glutaminase using glutamine analogs have been unsuccessful owing to their toxicities (2). BPTES has attracted much attention as a selective, nontoxic inhibitor of KGA (15), and preclinical testing of BPTES toward human cancers has just begun (20). BPTES selectively suppresses the growth of glioma cells (21) and inhibits the growth of lymphoma tumor growth in animal model studies (22). Wang et al. (11) reported a small molecule that targets glutaminase activity and oncogenic transformation. Despite extensive studies, nothing is known about the structural and molecular basis for KGA inhibitory mechanisms and how their function is regulated during normal and cancer cell metabolism. Such limited information impedes our effort in producing better generations of inhibitors for better treatment regimens.

Comparison of the complex structures with apo cKGA structure, which has well-defined electron density for the key loop, we provide the atomic view of an allosteric binding pocket for BPTES and elucidate the inhibitory mechanism of KGA by BPTES. The key residues of the loop (Glu312-Pro329) undergo major conformational changes upon binding of BPTES. In addition, structure-based mutagenesis studies suggest that this loop is essential for stabilizing the active site. Therefore, by binding in an allosteric pocket, BPTES inhibits the enzymatic activity of KGA through (i) triggering a major conformational change on the key residues that would normally be involved in stabilizing the active sites and regulating its enzymatic activity; and (ii) forming a stable inactive tetrameric KGA form. Our findings are further supported by two very recent reports on KGA isoform (GAC) (2324), although these studies lack full details owing to limitation of their electron density maps. BPTES is specific to KGA but not to LGA (15). Sequence comparison of KGA with LGA (Fig. S8A) reveals two unique residues on KGA, Phe318 and Phe322, which upon mutation to LGA counterparts, become resistant to BPTES. Thus, our study provides the molecular basis of BPTES specificity.

7.7.2 Sonic hedgehog (Shh) signaling promotes tumorigenicity and stemness via activation of epithelial-to-mesenchymal transition (EMT) in bladder cancer.

Islam SS, Mokhtari RB, Noman AS, …, van der Kwast T, Yeger H, Farhat WA.
Molec Carcinogenesis mar 2015; 54(5). http://dx.doi.org:/10.1002/mc.22300

shh sonic hedgehog signaling pathway nri2151-f1

shh sonic hedgehog signaling pathway nri2151-f1

Activation of the sonic hedgehog (Shh) signaling pathway controls tumorigenesis in a variety of cancers. Here, we show a role for Shh signaling in the promotion of epithelial-to-mesenchymal transition (EMT), tumorigenicity, and stemness in the bladder cancer. EMT induction was assessed by the decreased expression of E-cadherin and ZO-1 and increased expression of N-cadherin. The induced EMT was associated with increased cell motility, invasiveness, and clonogenicity. These progression relevant behaviors were attenuated by treatment with Hh inhibitors cyclopamine and GDC-0449, and after knockdown by Shh-siRNA, and led to reversal of the EMT phenotype. The results with HTB-9 were confirmed using a second bladder cancer cell line, BFTC905 (DM). In a xenograft mouse model TGF-β1 treated HTB-9 cells exhibited enhanced tumor growth. Although normal bladder epithelial cells could also undergo EMT and upregulate Shh with TGF-β1 they did not exhibit tumorigenicity. The TGF-β1 treated HTB-9 xenografts showed strong evidence for a switch to a more stem cell like phenotype, with functional activation of CD133, Sox2, Nanog, and Oct4. The bladder cancer specific stem cell markers CK5 and CK14 were upregulated in the TGF-β1 treated xenograft tumor samples, while CD44 remained unchanged in both treated and untreated tumors. Immunohistochemical analysis of 22 primary human bladder tumors indicated that Shh expression was positively correlated with tumor grade and stage. Elevated expression of Ki-67, Shh, Gli2, and N-cadherin were observed in the high grade and stage human bladder tumor samples, and conversely, the downregulation of these genes were observed in the low grade and stage tumor samples. Collectively, this study indicates that TGF-β1-induced Shh may regulate EMT and tumorigenicity in bladder cancer. Our studies reveal that the TGF-β1 induction of EMT and Shh is cell type context dependent. Thus, targeting the Shh pathway could be clinically beneficial in the ability to reverse the EMT phenotype of tumor cells and potentially inhibit bladder cancer progression and metastasis

Sonic_hedgehog_pathway

Sonic_hedgehog_pathway

7.7.3 Differential activation of NF-κB signaling is associated with platinum and taxane resistance in MyD88 deficient epithelial ovarian cancer cells

Gaikwad SM, Thakur B, Sakpal A, Singh RK, Ray P.
Int J Biochem Cell Biol. 2015 Apr; 61:90-102
http://dx.doi.org:/10.1016/j.biocel.2015.02.001

Development of chemoresistance is a major impediment to successful treatment of patients suffering from epithelial ovarian carcinoma (EOC). Among various molecular factors, presence of MyD88, a component of TLR-4/MyD88 mediated NF-κB signaling in EOC tumors is reported to cause intrinsic paclitaxel resistance and poor survival. However, 50-60% of EOC patients do not express MyD88 and one-third of these patients finally relapses and dies due to disease burden. The status and role of NF-κB signaling in this chemoresistant MyD88(negative) population has not been investigated so far. Using isogenic cellular matrices of cisplatin, paclitaxel and platinum-taxol resistant MyD88(negative) A2780 ovarian cancer cells expressing a NF-κB reporter sensor, we showed that enhanced NF-κB activity was required for cisplatin but not for paclitaxel resistance. Immunofluorescence and gel mobility shift assay demonstrated enhanced nuclear localization of NF-κB and subsequent binding to NF-κB response element in cisplatin resistant cells. The enhanced NF-κB activity was measurable from in vivo tumor xenografts by dual bioluminescence imaging. In contrast, paclitaxel and the platinum-taxol resistant cells showed down regulation in NF-κB activity. Intriguingly, silencing of MyD88 in cisplatin resistant and MyD88(positive) TOV21G and SKOV3 cells showed enhanced NF-κB activity after cisplatin but not after paclitaxel or platinum-taxol treatments. Our data thus suggest that NF-κB signaling is important for maintenance of cisplatin resistance but not for taxol or platinum-taxol resistance in absence of an active TLR-4/MyD88 receptor mediated cell survival pathway in epithelial ovarian carcinoma.

7.7.4 Activation of apoptosis by caspase-3-dependent specific RelB cleavage in anticancer agent-treated cancer cells

Kuboki MIto ASimizu SUmezawa K.
Biochem Biophys Res Commun. 2015 Jan 16; 456(3):810-4
http://dx.doi.org:/10.1016/j.bbrc.2014.12.024

Activation of caspase 3 and caspase-dependent apoptosis  nrmicro2071-f1

Activation of caspase 3 and caspase-dependent apoptosis nrmicro2071-f1

Highlights

  • We have prepared RelB mutants that are resistant to caspase 3-induced scission.
  • Vinblastine induced caspase 3-dependent site-specific RelB cleavage in cancer cells.
  • Cancer cells expressing cleavage-resistant RelB showed less sensitivity to vinblastine.
  • Caspase 3-induced RelB cleavage may provide positive feedback mechanism in apoptosis.

DTCM-glutarimide (DTCM-G) is a newly found anti-inflammatory agent. In the course of experiments with lymphoma cells, we found that DTCM-G induced specific RelB cleavage. Anticancer agent vinblastine also induced the specific RelB cleavage in human fibrosarcoma HT1080 cells. The site-directed mutagenesis analysis revealed that the Asp205 site in RelB was specifically cleaved possibly by caspase-3 in vinblastine-treated HT1080 cells. Moreover, the cells stably overexpressing RelB Asp205Ala were resistant to vinblastine-induced apoptosis. Thus, the specific Asp205 cleavage of RelB by caspase-3 would be involved in the apoptosis induction by anticancer agents, which would provide the positive feedback mechanism.

apoptotic-caspases-control-microglia-activation-cdd2011107f3

apoptotic-caspases-control-microglia-activation-cdd2011107f3

 

 

7.7.5 Identification of Liver Cancer Progenitors Whose Malignant Progression Depends on Autocrine IL-6 Signaling

He GDhar DNakagawa HFont-Burgada JOgata HJiang Y, et al.
Cell. 2013 Oct 10; 155(2):384-96
http://dx.doi.org/10.1016%2Fj.cell.2013.09.031

Il-6 signaling in cancer cells

Il-6 signaling in cancer cells

Hepatocellular carcinoma (HCC) is a slowly developing malignancy postulated to evolve from pre-malignant lesions in chronically damaged livers. However, it was never established that premalignant lesions actually contain tumor progenitors that give rise to cancer. Here, we describe isolation and characterization of HCC progenitor cells (HcPCs) from different mouse HCC models. Unlike fully malignant HCC, HcPCs give rise to cancer only when introduced into a liver undergoing chronic damage and compensatory proliferation. Although HcPCs exhibit a similar transcriptomic profile to bipotential hepatobiliary progenitors, the latter do not give rise to tumors. Cells resembling HcPCs reside within dysplastic lesions that appear several months before HCC nodules. Unlike early hepatocarcinogenesis, which depends on paracrine IL-6 production by inflammatory cells, due to upregulation of LIN28 expression, HcPCs had acquired autocrine IL-6 signaling that stimulates their in vivo growth and malignant progression. This may be a general mechanism that drives other IL-6-producing malignancies.

Clonal evolution and selective pressure may cause some descendants of the initial progenitor to cross the bridge of no return and form a premalignant lesion. Cancer genome sequencing indicates that most cancers require at least five genetic changes to evolve (Wood et al., 2007). It has been difficult to isolate and propagate cancer progenitors prior to detection of tumor masses. Further, it is not clear whether cancer progenitors are the precursors for the  cancer stem cells (CSCs)isolated from cancers. An answer to these critical questions depends on identification and isolation of cancer progenitors, which may also enable definition of molecular markers and signaling pathways suitable for early detection and treatment.

Hepatocellular carcinoma (HCC), the end product of chronic liver diseases, requires several decades to evolve (El-Serag, 2011). It is the third most deadly and fifth most common cancer worldwide, and in the United States its incidence has doubled in the past two decades. Furthermore, 8% of the world’s population are chronically infected with hepatitis B or C viruses (HBV and HCV) and are at a high risk of new HCC development (El-Serag, 2011). Up to 5% of HCV patients will develop HCC in their lifetime, and the yearly HCC incidence in patients with cirrhosis is 3%–5%. These tumors may arise from premalignant lesions, ranging from dysplastic foci to dysplastic hepatocyte nodules that are often seen in damaged and cirrhotic livers and are more proliferative than the surrounding parenchyma (Hytiroglou et al., 2007). There is no effective treatment for HCC and, upon diagnosis, most patients with advanced disease have a remaining lifespan of 4–6 months. Premalignant lesions, called foci of altered hepatocytes (FAH), were described in chemically induced HCC models (Pitot, 1990), but it was questioned whether these lesions harbor tumor progenitors or result from compensatory proliferation (Sell and Leffert, 2008). The aim of this study was to determine whether HCC progenitor cells (HcPCs) exist and if so, to isolate these cells and identify some of the signaling networks that are involved in their maintenance and progression.

We now describe HcPC isolation from mice treated with the procarcinogen diethyl nitrosamine (DEN), which induces poorly differentiated HCC nodules within 8 to 9 months (Verna et al., 1996). The use of a chemical carcinogen is justified because the finding of up to 121 mutations per HCC genome suggests that carcinogens may be responsible for human HCC induction (Guichard et al., 2012). Furthermore, 20%–30% of HCC, especially in HBV-infected individuals, evolve in noncirrhotic livers (El-Serag, 2011). Nonetheless, we also isolated HcPCs fromTak1Δhep mice, which develop spontaneous HCC as a result of progressive liver damage, inflammation, and fibrosis caused by ablation of TAK1 (Inokuchi et al., 2010). Although the etiology of each model is distinct, both contain HcPCs that express marker genes and signaling pathways previously identified in human HCC stem cells (Marquardt and Thorgeirsson, 2010) long before visible tumors are detected. Furthermore, DEN-induced premalignant lesions and HcPCs exhibit autocrine IL-6 production that is critical for tumorigenic progression. Circulating IL-6 is a risk indicator in several human pathologies and is strongly correlated with adverse prognosis in HCC and cholangiocarcinoma (Porta et al., 2008Soresi et al., 2006). IL-6 produced by in-vitro-induced CSCs was suggested to be important for their maintenance (Iliopoulos et al., 2009). Little is known about the source of IL-6 in HCC.

DEN-Induced Collagenase-Resistant Aggregates of HCC Progenitors

A single intraperitoneal (i.p.) injection of DEN into 15-day-old BL/6 mice induces HCC nodules first detected 8 to 9 months later. However, hepatocytes prepared from macroscopically normal livers 3 months after DEN administration already contain cells that progress to HCC when transplanted into the permissive liver environment of MUP-uPA mice (He et al., 2010), which express urokinase plasminogen activator (uPA) from a mouse liver-specific major urinary protein (MUP) promoter and undergo chronic liver damage and compensatory proliferation (Rhim et al., 1994). HCC markers such as α fetoprotein (AFP), glypican 3 (Gpc3), and Ly6D, whose expression in mouse liver cancer was reported (Meyer et al., 2003), were upregulated in aggregates from DEN-treated livers, but not in nonaggregated hepatocytes or aggregates from control livers (Figure S1A). Using 70 μm and 40 μm sieves, we separated aggregated from nonaggregated hepatocytes (Figure 1A) and tested their tumorigenic potential by transplantation into MUP-uPA mice (Figure 1B). To facilitate transplantation, the aggregates were mechanically dispersed and suspended in Dulbecco’s modified Eagle’s medium (DMEM). Five months after intrasplenic (i.s.) injection of 104 viable cells, mice receiving cells from aggregates developed about 18 liver tumors per mouse, whereas mice receiving nonaggregated hepatocytes developed less than 1 tumor each (Figure 1B). The tumors exhibited typical trabecular HCC morphology and contained cells that abundantly express AFP (Figure S1B).

Only liver tumors were formed by the transplanted cells. Other organs, including the spleen into which the cells were injected, remained tumor free (Figure 1B), suggesting that HcPCs progress to cancer only in the proper microenvironment. Indeed, no tumors appeared after HcPC transplantation into normal BL/6 mice. But, if BL/6 mice were first treated with retrorsine (a chemical that permanently inhibits hepatocyte proliferation [Laconi et al., 1998]), intrasplenically transplanted with HcPC-containing aggregates, and challenged with CCl4 to induce liver injury and compensatory proliferation (Guo et al., 2002), HCCs readily appeared (Figure 1C). CCl4 omission prevented tumor development. Notably, MUP-uPA or CCl4-treated livers are fragile, rendering direct intrahepatic transplantation difficult. CCl4-induced liver damage, especially within a male liver, generates a microenvironment that drives HcPC proliferation and malignant progression. To examine this point, we transplanted GFP-labeled HcPC-containing aggregates into retrorsine-treated BL/6 mice and examined their ability to proliferate with or without subsequent CCl4 treatment. Indeed, the GFP+ cells formed clusters that grew in size only in CCl4-treated host livers (Figure S1E). Omission of CC14 prevented their expansion.

Because CD44 is expressed by HCC stem cells (Yang et al., 2008Zhu et al., 2010), we dispersed the aggregates and separated CD44+ from CD44 cells and transplanted both into MUP-uPA mice. Whereas as few as 103 CD44+ cells gave rise to HCCs in 100% of recipients, no tumors were detected after transplantation of CD44 cells (Figure 1E). Remarkably, 50% of recipients developed at least one HCC after receiving as few as 102 CD44+ cells.

HcPC-Containing Aggregates in Tak1Δhep Mice

We applied the same HcPC isolation protocol to Tak1Δhep mice, which develop HCC of different etiology from DEN-induced HCC. Importantly, Tak1Δhep mice develop HCC as a consequence of chronic liver injury and fibrosis without carcinogen or toxicant exposure (Inokuchi et al., 2010). Indeed, whole-tumor exome sequencing revealed that DEN-induced HCC contained about 24 mutations per 106 bases (Mb) sequenced, with B-RafV637E being the most recurrent, whereas 1.4 mutations per Mb were detected inTak1Δhep HCC’s exome (Table S1). By contrast, Tak1Δhep HCC exhibited gene copy number changes. HCC developed in 75% of MUP-uPA mice that received dispersed Tak1Δhep aggregates, but no tumors appeared in mice receiving nonaggregated Tak1Δhep or totalTak1f/f hepatocytes (Figure 2B). bile duct ligation (BDL) or feeding with 3,5-dicarbethoxy-1,4-dihydrocollidine (DDC), treatments that cause cholestatic liver injuries and oval cell expansion (Dorrell et al., 2011), did increase the number of small hepatocytic cell aggregates (Figure S2A). Nonetheless, no tumors were observed 5 months after injection of such aggregates into MUP-uPA mice (Figure S2B). Thus, not all hepatocytic aggregates contain HcPCs, and HcPCs only appear under tumorigenic conditions.

The HcPC Transcriptome Is Similar to that of HCC and Oval Cells

To determine the relationship between DEN-induced HcPCs, normal hepatocytes, and fully transformed HCC cells, we analyzed the transcriptomes of aggregated and nonaggregated hepatocytes from male littermates 5 months after DEN administration, HCC epithelial cells from DEN-induced tumors, and normal hepatocytes from age- and gender-matched littermate controls. Clustering analysis distinguished the HCC samples from other samples and revealed that the aggregated hepatocyte samples did not cluster with each other but rather with nonaggregated hepatocytes derived from the same mouse (Figure S3A). 57% (583/1,020) of genes differentially expressed in aggregated relative to nonaggregated hepatocytes are also differentially expressed in HCC relative to normal hepatocytes (Figure 3B, top), a value that is highly significant (p < 7.13 × 10−243). More specifically, 85% (494/583) of these genes are overexpressed in both HCC and HcPC-containing aggregates (Figure 3B, bottom table). Thus, hepatocyte aggregates isolated 5 months after DEN injection contain cells that are related in their gene expression profile to HCC cells isolated from fully developed tumor nodules.

Figure 3 Aggregated Hepatocytes Exhibit an Altered Transcriptome Similar to that of HCC Cells

We examined which biological processes or cellular compartments were significantly overrepresented in the induced or repressed genes in both pairwise comparisons (Gene Ontology Analysis). As expected, processes and compartments that were enriched in aggregated hepatocytes relative to nonaggregated hepatocytes were almost identical to those that were enriched in HCC relative to normal hepatocytes (Figure 3C). Several human HCC markers, including AFP, Gpc3 and H19, were upregulated in aggregated hepatocytes (Figures 3D and 3E). Aggregated hepatocytes also expressed more Tetraspanin 8 (Tspan8), a cell-surface glycoprotein that complexes with integrins and is overexpressed in human carcinomas (Zöller, 2009). Another cell-surface molecule highly expressed in aggregated cells is Ly6D (Figures 3D and 3E). Immunofluorescence (IF) analysis revealed that Ly6D was undetectable in normal liver but was elevated in FAH and ubiquitously expressed in most HCC cells (Figure S3C). A fluorescent-labeled Ly6D antibody injected into HCC-bearing mice specifically stained tumor nodules (Figure S3D). Other cell-surface molecules that were upregulated in aggregated cells included syndecan 3 (Sdc3), integrin α 9 (Itga9), claudin 5 (Cldn5), and cadherin 5 (Cdh5) (Figure 3D). Aggregated hepatocytes also exhibited elevated expression of extracellular matrix proteins (TIF3 and Reln1) and a serine protease inhibitor (Spink3). Elevated expression of such proteins may explain aggregate formation. Aggregated hepatocytes also expressed progenitor cell markers, including the epithelial cell adhesion molecule (EpCAM) (Figure 3E) and Dlk1 (Figure 3D). We compared the HcPC and HCC (Figure 3A) to the transcriptome of DDC-induced oval cells (Shin et al., 2011). This analysis revealed a striking similarity between the HCC, HcPC, and the oval cell transcriptomes (Figure S3B). Despite these similarities, some genes that were upregulated in HcPC-containing aggregates and HCC were not upregulated in oval cells. Such genes may account for the tumorigenic properties of HcPC and HCC.

Figure 4  DEN-Induced HcPC Aggregates Express Pathways and Markers Characteristic of HCC and Hepatobiliary Stem Cells

We examined the aggregates for signaling pathways and transcription factors involved in hepatocarcinogenesis. Many aggregated cells were positive for phosphorylated c-Jun and STAT3 (Figure 4A), transcription factors involved in DEN-induced hepatocarcinogenesis (Eferl et al., 2003He et al., 2010). Sox9, a transcription factor that marks hepatobiliary progenitors (Dorrell et al., 2011), was also expressed by many of the aggregated cells, which were also positive for phosphorylated c-Met (Figure 4A), a receptor tyrosine kinase that is activated by hepatocyte growth factor (HGF) and is essential for liver development (Bladt et al., 1995) and hepatocarcinogenesis (Wang et al., 2001). Few of the nonaggregated hepatocytes exhibited activation of these signaling pathways. Despite different etiology, HcPC-containing aggregates from Tak1Δhep mice exhibit upregulation of many of the same markers and pathways that are upregulated in DEN-induced HcPC-containing aggregates. Flow cytometry confirmed enrichment of CD44+ cells as well as CD44+/CD90+ and CD44+/EpCAM+ double-positive cells in the HcPC-containing aggregates from either DEN-treated or Tak1Δhep livers (Figure S4B).

HcPC-Containing Aggregates Originate from Premalignant Dysplastic Lesions

FAH are dysplastic lesions occurring in rodent livers exposed to hepatic carcinogens (Su et al., 1990). Similar lesions are present in premalignant human livers (Su et al., 1997). Yet, it is still debated whether FAH correspond to premalignant lesions or are a reaction to liver injury that does not lead to cancer (Sell and Leffert, 2008). In DEN-treated males, FAH were detected as early as 3 months after DEN administration (Figure 5A), concomitant with the time at which HcPC-containing aggregates were detected. In females, FAH development was delayed. FAH contained cells positive for the same progenitor cell markers and activated signaling pathways present in HcPC-containing aggregates, including AFP, CD44, and EpCAM (Figure 5C). FAH also contained cells positive for activated STAT3, c-Jun, and PCNA (Figure 5C).

HcPCs Exhibit Autocrine IL-6 Expression Necessary for HCC Progression

In situ hybridization (ISH) and immunohistochemistry (IHC) revealed that DEN-induced FAH contained IL-6-expressing cells (Figures 6A, 6B, and S5), and freshly isolated DEN-induced aggregates contained more IL-6 messenger RNA (mRNA) than nonaggregated hepatocytes (Figure 6C). We examined several factors that control IL-6 expression and found that LIN28A and B were significantly upregulated in HcPCs and HCC (Figures 6D and 6E). LIN28-expressing cells were also detected within FAH (Figure 6F). As reported (Iliopoulos et al., 2009), knockdown of LIN28B in cultured HcPC or HCC cell lines decreased IL-6 expression (Figure 6G). LIN28 exerts its effects through downregulation of the microRNA (miRNA) Let-7 (Iliopoulos et al., 2009).

Figure 6  Liver Premalignant Lesions and HcPCs Exhibit Elevated IL-6 and LIN28 Expression

Figure 7  HCC Growth Depends on Autocrine IL-6 Production

The isolation and characterization of cells that can give rise to HCC only after transplantation into an appropriate host liver undergoing chronic injury demonstrates that cancer arises from progenitor cells that are yet to become fully malignant. Importantly, unlike fully malignant HCC cells, the HcPCs we isolated cannot form s.c. tumors or even liver tumors when introduced into a nondamaged liver. Liver damage induced by uPA expression or CCl4 treatment provides HcPCs with the proper cytokine and growth factor milieu needed for their proliferation. Although HcPCs produce IL-6, they may also depend on other cytokines such as TNF, which is produced by macrophages that are recruited to the damaged liver. In addition, uPA expression and CCl4 treatment may enhance HcPC growth and progression through their fibrogenic effect on hepatic stellate cells. Although HCC and other cancers have been suspected to arise from premalignant/dysplastic lesions (Hruban et al., 2007Hytiroglou et al., 2007), a direct demonstration that such lesions progress into malignant tumors has been lacking. Based on expression of common markers—EpCAM, CD44, AFP, activated STAT3, and IL-6—that are not expressed in normal hepatocytes, we postulate that HcPCs originate from FAH or dysplastic foci, which are first observed in male mice within 3 months of DEN exposure.

7.7.6 Acetylation Stabilizes ATP-Citrate Lyase to Promote Lipid Biosynthesis and Tumor Growth

Lin R1Tao RGao XLi TZhou XGuan KLXiong YLei QY.
Mol Cell. 2013 Aug 22; 51(4):506-18
http://dx.doi.org:/10.1016/j.molcel.2013.07.002

Increased fatty acid synthesis is required to meet the demand for membrane expansion of rapidly growing cells. ATP-citrate lyase (ACLY) is upregulated or activated in several types of cancer, and inhibition of ACLY arrests proliferation of cancer cells. Here we show that ACLY is acetylated at lysine residues 540, 546, and 554 (3K). Acetylation at these three lysine residues is stimulated by P300/calcium-binding protein (CBP)-associated factor (PCAF) acetyltransferase under high glucose and increases ACLY stability by blocking its ubiquitylation and degradation. Conversely, the protein deacetylase sirtuin 2 (SIRT2) deacetylates and destabilizes ACLY. Substitution of 3K abolishes ACLY ubiquitylation and promotes de novo lipid synthesis, cell proliferation, and tumor growth. Importantly, 3K acetylation of ACLY is increased in human lung cancers. Our study reveals a crosstalk between acetylation and ubiquitylation by competing for the same lysine residues in the regulation of fatty acid synthesis and cell growth in response to glucose.

Fatty acid synthesis occurs at low rates in most nondividing cells of normal tissues that primarily uptake lipids from circulation. In contrast, increased lipogenesis, especially de novo lipid synthesis, is a key characteristic of cancer cells. Many studies have demonstrated that in cancer cells, fatty acids are preferred to be derived from de novo synthesis instead of extracellular lipid supply (Medes et al., 1953Menendez and Lupu, 2007;Ookhtens et al., 1984Sabine et al., 1967). Fatty acids are key building blocks for membrane biogenesis, and glucose serves as a major carbon source for de novo fatty acid synthesis (Kuhajda, 2000McAndrew, 1986;Swinnen et al., 2006). In rapidly proliferating cells, citrate generated by the tricarboxylic acid (TCA) cycle, either from glucose by glycolysis or glutamine by anaplerosis, is preferentially exported from mitochondria to cytosol and then cleaved by ATP citrate lyase (ACLY) (Icard et al., 2012) to produce cytosolic acetyl coenzyme A (acetyl-CoA), which is the building block for de novo lipid synthesis. As such, ACLY couples energy metabolism with fatty acids synthesis and plays a critical role in supporting cell growth. The function of ACLY in cell growth is supported by the observation that inhibition of ACLY by chemical inhibitors or RNAi dramatically suppresses tumor cell proliferation and induces differentiation in vitro and in vivo (Bauer et al., 2005Hatzivassiliou et al., 2005). In addition, ACLY activity may link metabolic status to histone acetylation by providing acetyl-CoA and, therefore, gene expression (Wellen et al., 2009).

While ACLY is transcriptionally regulated by sterol regulatory element-binding protein 1 (SREBP-1) (Kim et al., 2010), ACLY activity is regulated by the phosphatidylinositol 3-kinase (PI3K)/Akt pathway (Berwick et al., 2002Migita et al., 2008Pierce et al., 1982). Akt can directly phosphorylate and activate ACLY (Bauer et al., 2005Berwick et al., 2002Migita et al., 2008Potapova et al., 2000). Covalent lysine acetylation has recently been found to play a broad and critical role in the regulation of multiple metabolic enzymes (Choudhary et al., 2009Zhao et al., 2010). In this study, we demonstrate that ACLY protein is acetylated on multiple lysine residues in response to high glucose. Acetylation of ACLY blocks its ubiquitinylation and degradation, thus leading to ACLY accumulation and increased fatty acid synthesis. Our observations reveal a crosstalk between protein acetylation and ubiquitylation in the regulation of fatty acid synthesis and cell growth.

Acetylation of ACLY at Lysines 540, 546, and 554

Recent mass spectrometry-based proteomic analyses have potentially identified a large number of acetylated proteins, including ACLY (Figure S1A available online; Choudhary et al., 2009Zhao et al., 2010). We detected the acetylation level of ectopically expressed ACLY followed by western blot using pan-specific anti-acetylated lysine antibody. ACLY was indeed acetylated, and its acetylation was increased by nearly 3-fold after treatment with nicotinamide (NAM), an inhibitor of the SIRT family deacetylases, and trichostatin A (TSA), an inhibitor of histone deacetylase (HDAC) class I and class II (Figure 1A). Experiments with endogenous ACLY also showed that TSA and NAM treatment enhanced ACLY acetylation (Figure 1B).

Figure 1  ACLY Is Acetylated at Lysines 540, 546, and 554

Ten putative acetylation sites were identified by mass spectrometry analyses (Table S1). We singly mutated each lysine to either a glutamine (Q) or an arginine (R) and found that no single mutation resulted in a significant reduction of ACLY acetylation (data not shown), indicating that ACLY may be acetylated at multiple lysine residues. Three lysine residues, K540, K546, and K554, received high scores in the acetylation proteomic screen and are evolutionarily conserved from C. elegans to mammals (Figure S1A). We generated triple Q and R mutants of K540, K546, and K554 (3KQ and 3KR) and found that both 3KQ and 3KR mutations resulted in a significant (~60%) decrease in ACLY acetylation (Figure 1C), indicating that 3K are the major acetylation sites of ACLY.  Further, we found that the acetylation of endogenous ACLY is clearly increased after treatment of cells with NAM and TSA (Figure 1D). These results demonstrate that ACLY is acetylated at K540, K546, and K554.

Glucose Promotes ACLY Acetylation to Stabilize ACLY

In mammalian cells, glucose is the main carbon source for de novo lipid synthesis. We found that ACLY levels increased with increasing glucose concentration, which also correlated with increased ACLY 3K acetylation (Figure 1E). Furthermore, to confirm whether the glucose level affects ACLY protein stability in vivo, we intraperitoneally injected glucose in BALB/c mice and found that high glucose resulted in a significant increase of ACLY protein levels (Figure 1F).

To determine whether ACLY acetylation affects its protein levels, we treated HeLa and Chang liver cells with NAM and TSA and found an increase in ACLY protein levels (Figure S1G, upper panel). ACLY mRNA levels were not significantly changed by the treatment of NAM and TSA (Figure S1G, lower panel), indicating that this upregulation of ACLY is mostly achieved at the posttranscriptional level. Indeed, ACLY protein was also accumulated in cells treated with the proteasome inhibitor MG132, indicating that ACLY stability could be regulated by the ubiquitin-proteasome pathway (Figure 1G). Blocking deacetylase activity stabilized ACLY (Figure S1H). The stabilization of ACLY induced by high glucose was associated with an increase of ACLY acetylation at K540, K546, and K554. Together, these data support a notion that high glucose induces both ACLY acetylation and protein stabilization and prompted us to ask whether acetylation directly regulates ACLY stability. We then generated ACLYWT, ACLY3KQ, and ACLY3KRstable cells after knocking down the endogenous ACLY. We found that the ACLY3KR or ACLY3KQmutant was more stable than the ACLYWT (Figures 1I and S1I). Collectively, our results suggest that glucose induces acetylation at K540, 546, and 554 to stabilize ACLY.

Acetylation Stabilizes ACLY by Inhibiting Ubiquitylation

To determine the mechanism underlying the acetylation and ACLY protein stability, we first examined ACLY ubiquitylation and found that it was actively ubiquitylated (Figure 2A). Previous proteomic analyses have identified K546 in ACLY as a ubiquitylation site (Wagner et al., 2011). In order to identify the ubiquitylation sites, we tested the ubiquitylation levels of double mutants 540R–546R and 546–554R (Figure S2A). We found that the ubiquitylation of the 540R-546R and 546R-554R mutants is partially decreased, while mutation of K540, K546, and K554 (3KR), which changes all three putative acetylation lysine residues of ACLY to arginine residues, dramatically reduced the ACLY ubiquitylation level (Figures 2B and S2A), indicating that 3K lysines might also be the ubiquitylation target residues. Moreover, inhibition of deacetylases by NAM and TSA decreased ubiquitylation of WT but not 3KQ or 3KR mutant ACLY (Figure 2C). These results implicate an antagonizing role of the acetylation towards the ubiquitylation of ACLY at these three lysine residues.

Figure 2  Acetylation Protects ACLY from Proteasome Degradation by Inhibiting Ubiquitylation

We found that ACLY acetylation was only detected in the nonubiquitylated, but not the ubiquitylated (high-molecular-weight), ACLY species. This result indicates that ACLY acetylation and ubiquitylation are mutually exclusive and is consistent with the model that K540, K546, and K554 are the sites of both ubiquitylation and acetylation. Therefore, acetylation of these lysines would block ubiquitylation.

We also found that glucose upregulates ACLY acetylation at 3K and decreases its ubiquitylation (Figure S2B). High glucose (25 mM) effectively decreased ACLY ubiquitylation, while inhibition of deacetylases clearly diminished its ubiquitylation (Figure 2E). We conclude that acetylation and ubiquitylation occur mutually exclusively at K540, K546, and K554 and that high-glucose-induced acetylation at these three sites blocks ACLY ubiquitylation and degradation.

UBR4 Targets ACLY for Degradation

UBR4 was identified as a putative ACLY-interacting protein by affinity purification coupled with mass spectrometry analysis (data not shown). To address if UBR4 is a potential ACLY E3 ligase, we determined the interaction between ACLY and UBR4 and found that ACLY interacted with the E3 ligase domain of UBR4; this interaction was enhanced by MG132 treatment (Figure 3A). UBR4 knockdown in A549 cells resulted in an increase of endogenous ACLY protein level (Figure 3C). Moreover, UBR4 knockdown significantly stabilized ACLY (Figure 3D) and decreased ACLY ubiquitylation (Figure 3E). Taken together, these results indicate that UBR4 is an ACLY E3 ligase that responds to glucose regulation.

Figure 3  UBR4 Is the E3 Ligase of ACLY

PCAF Acetylates ACLY

PCAF knockdown significantly reduced acetylation of 3K, indicating that PCAF is a potential 3K acetyltransferase in vivo (Figure 4C, upper panel). Furthermore, PCAF knockdown decreased the steady-state level of endogenous ACLY, but not ACLY mRNA (Figure 4C, middle and lower panels). Moreover, we found that PCAF knockdown destabilized ACLY (Figure 4D). In addition, overexpression of PCAF decreases ACLY ubiquitylation (Figure 4E), while PCAF inhibition increases the interaction between UBR4 E3 ligase domain and wild-type ACLY, but not 3KR (Figure 4F). Together, our results indicate that PCAF increases ACLY protein level, possibly via acetylating ACLY at 3K.

Figure 4  PCAF Is the Acetylase of ACLY

SIRT2 Deacetylates ACLY

Figure 5  SIRT2 Decreases ACLY Acetylation and Increases Its Protein Levels In Vivo

Acetylation of ACLY Promotes Cell Proliferation and De Novo Lipid Synthesis

The protein levels of ACLY 3KQ and 3KR were accumulated to a level higher than the wild-type cells upon extended culture in low-glucose medium (Figure S6A, right panel), indicating a growth advantage conferred by ACLY stabilization resulting from the disruption of both acetylation and ubiquitylation at K540, K546, and K554. Cellular acetyl-CoA assay showed that cells expressing 3KQ or 3KR mutant ACLY produce more acetyl-CoA than cells expressing the wild-type ACLY under low glucose (Figures 6B and S6B), further supporting the conclusion that 3KQ or 3KR mutation stabilizes ACLY.

Figure 6  Acetylation of ACLY at 3K Promotes Lipogenesis and Tumor Cell Proliferation

ACLY is a key enzyme in de novo lipid synthesis. Silencing ACLY inhibited the proliferation of multiple cancer cell lines, and this inhibition can be partially rescued by adding extra fatty acids or cholesterol into the culture media (Zaidi et al., 2012). This prompted us to measure extracellular lipid incorporation in A549 cells after knockdown and ectopic expression of ACLY. We found that when cultured in low glucose (2.5 mM), cells expressing wild-type ACLY uptake significantly more phospholipids compared to cells expressing 3KQ or 3KR mutant ACLY (Figures 6C, 6D, and S6D). When cultured in the presence of high glucose (25 mM), however, cells expressing either the wild-type, 3KQ, or 3KR mutant ACLY all have reduced, but similar, uptake of extracellular phospholipids (Figures 6C, 6D, and S6D). The above results are consistent with a model that acetylation of ACLY induced by high glucose increases its stability and stimulates de novo lipid synthesis.

3K Acetylation of ACLY Is Increased in Lung Cancer

ACLY is reported to be upregulated in human lung cancer (Migita et al., 2008). Many small chemicals targeting ACLY have been designed for cancer treatment (Zu et al., 2012). The finding that 3KQ or 3KR mutant increased the ability of ACLY to support A549 lung cancer cell proliferation prompted us to examine 3K acetylation in human lung cancers. We collected a total of 54 pairs of primary human lung cancer samples with adjacent normal lung tissues and performed immunoblotting for ACLY protein levels. This analysis revealed that, when compared to the matched normal lung tissues, 29 pairs showed a significant increase of total ACLY protein using b-actin as a loading control (Figures 7A and S7A). The tumor sample analyses demonstrate that ACLY protein levels are elevated in lung cancers, and 3K acetylation positively correlates with the elevated ACLY protein. These data also indicate that ACLY with 3K acetylation may be potential biomarker for lung cancer diagnosis.

Figure 7
  Acetylation of ACLY at 3K Is Upregulated in Human Lung Carcinoma

Dysregulation of cellular metabolism is a hallmark of cancer (Hanahan and Weinberg, 2011Vander Heiden et al., 2009). Besides elevated glycolysis, increased lipogenesis, especially de novo lipid synthesis, also plays an important role in tumor growth. Because most carbon sources for fatty acid synthesis are from glucose in mammalian cells (Wellen et al., 2009), the channeling of carbon into de novo lipid synthesis as building blocks for tumor cell growth is primarily linked to acetyl-CoA production by ACLY. Moreover, the ACLY-catalyzed reaction consumes ATP. Therefore, as the key cellular energy and carbon source, one may expect a role for glucose in ACLY regulation. In the present study, we have uncovered a mechanism of ACLY regulation by glucose that increases ACLY protein level to meet the enhanced demand of lipogenesis in growing cells, such as tumor cells (Figure 7C). Glucose increases ACLY protein levels by stimulating its acetylation.

Upregulation of ACLY is common in many cancers (Kuhajda, 2000Milgraum et al., 1997Swinnen et al., 2004Yahagi et al., 2005). This is in part due to the transcriptional activation by SREBP-1 resulting from the activation of the PI3K/AKT pathway in cancers (Kim et al., 2010Nadler et al., 2001Wang and Dey, 2006). In this study, we report a mechanism of ACLY regulation at the posttranscriptional level. We propose that acetylation modulated by glucose status plays a crucial role in coordinating the intracellular level of ACLY, hence fatty acid synthesis, and glucose availability. When glucose is sufficient, lipogenesis is enhanced. This can be achieved, at least in part, by the glucose-induced stabilization of ACLY. High glucose increases ACLY acetylation, which inhibits its ubiquitylation and degradation, leading to the accumulation of ACLY and enhanced lipogenesis. In contrast, when glucose is limited, ACLY is not acetylated and thus can be ubiquitylated, leading to ACLY degradation and reduced lipogenesis. Moreover, our data indicate that acetylation and ubiquitylation in ACLY may compete with each other by targeting the same lysine residues at K540, K546, and K554. Consistently, previous proteomic analyses have identified K546 in ACLY as a ubiquitylation site (Wagner et al., 2011). Similar models of different modifications on the same lysine residues have been reported in the regulation of other proteins (Grönroos et al., 2002Li et al., 20022012). We propose that acetylation and ubiquitylation have opposing effects in the regulation of ACLY by competitively modifying the same lysine residues. The acetylation-mimetic 3KQ and the acetylation-deficient 3KR mutants behaved indistinguishably in most biochemical and functional assays, mainly due to the fact that these mutations disrupt lysine ubiquitylation that primarily occurs on these three residues.

ACLY is increased in lung cancer tissues compared to adjacent tissues. Consistently, ACLY acetylation at 3K is also significantly increased in lung cancer tissues. These observations not only confirm ACLY acetylation in vivo, but also suggest that ACLY 3K acetylation may play a role in lung cancer development. Our study reveals a mechanism of ACLY regulation in response to glucose signals.

 

7.7.7 Monoacylglycerol Lipase Regulates a Fatty Acid Network that Promotes Cancer Pathogenesis

Nomura DK1Long JZNiessen SHoover HSNg SWCravatt BF.
Cell. 2010 Jan 8; 140(1):49-61
http://dx.doi.org/10.1016.2Fj.cell.2009.11.027

Highlights

  • Monoacylglycerol lipase (MAGL) is elevated in aggressive human cancer cells
  • Loss of MAGL lowers fatty acid levels in cancer cells and impairs pathogenicity
  • MAGL controls a signaling network enriched in protumorigenic lipids
  • A high-fat diet can restore the growth of tumors lacking MAGL in vivo
monoacylglycerol-lipase-magl-is-highly-expressed-in-aggressive-human-cancer-cells-and-primary-tumors

monoacylglycerol-lipase-magl-is-highly-expressed-in-aggressive-human-cancer-cells-and-primary-tumors

http://www.cell.com/cms/attachment/1082768/7977146/fx1.jpg

Tumor cells display progressive changes in metabolism that correlate with malignancy, including development of a lipogenic phenotype. How stored fats are liberated and remodeled to support cancer pathogenesis, however, remains unknown. Here, we show that the enzyme monoacylglycerol lipase (MAGL) is highly expressed in aggressive human cancer cells and primary tumors, where it regulates a fatty acid network enriched in oncogenic signaling lipids that promotes migration, invasion, survival, and in vivo tumor growth. Overexpression of MAGL in nonaggressive cancer cells recapitulates this fatty acid network and increases their pathogenicity—phenotypes that are reversed by an MAGL inhibitor. Impairments in MAGL-dependent tumor growth are rescued by a high-fat diet, indicating that exogenous sources of fatty acids can contribute to malignancy in cancers lacking MAGL activity. Together, these findings reveal how cancer cells can co-opt a lipolytic enzyme to translate their lipogenic state into an array of protumorigenic signals.

We show that the enzyme monoacylglycerol lipase (MAGL) is highly expressed in aggressive human cancer cells and primary tumors, where it regulates a fatty acid network enriched in oncogenic signaling lipids that promotes migration, invasion, survival, and in vivo tumor growth. Overexpression of MAGL in non-aggressive cancer cells recapitulates this fatty acid network and increases their pathogenicity — phenotypes that are reversed by an MAGL inhibitor. Interestingly, impairments in MAGL-dependent tumor growth are rescued by a high-fat diet, indicating that exogenous sources of fatty acids can contribute to malignancy in cancers lacking MAGL activity. Together, these findings reveal how cancer cells can co-opt a lipolytic enzyme to translate their lipogenic state into an array of pro-tumorigenic signals.

The conversion of cells from a normal to cancerous state is accompanied by reprogramming of metabolic pathways (Deberardinis et al., 2008Jones and Thompson, 2009Kroemer and Pouyssegur, 2008), including those that regulate glycolysis (Christofk et al., 2008Gatenby and Gillies, 2004), glutamine-dependent anaplerosis (DeBerardinis et al., 2008DeBerardinis et al., 2007Wise et al., 2008), and the production of lipids (DeBerardinis et al., 2008Menendez and Lupu, 2007). Despite a growing appreciation that dysregulated metabolism is a defining feature of cancer, it remains unclear, in many instances, how such biochemical changes occur and whether they play crucial roles in disease progression and malignancy.

Among dysregulated metabolic pathways, heightened de novo lipid biosynthesis, or the development a “lipogenic” phenotype (Menendez and Lupu, 2007), has been posited to play a major role in cancer. For instance, elevated levels of fatty acid synthase (FAS), the enzyme responsible for fatty acid biosynthesis from acetate and malonyl CoA, are correlated with poor prognosis in breast cancer patients, and inhibition of FAS results in decreased cell proliferation, loss of cell viability, and decreased tumor growth in vivo (Kuhajda et al., 2000Menendez and Lupu, 2007Zhou et al., 2007). FAS may support cancer growth, at least in part, by providing metabolic substrates for energy production (via fatty acid oxidation) (Buzzai et al., 2005Buzzai et al., 2007Liu, 2006). Many other features of lipid biochemistry, however, are also critical for supporting the malignancy of cancer cells, including:

Prominent examples of lipid messengers that contribute to cancer include:

Here, we use functional proteomic methods to discover a lipolytic enzyme, monoacylglycerol lipase (MAGL), that is highly elevated in aggressive cancer cells from multiple tissues of origin. We show that MAGL, through hydrolysis of monoacylglycerols (MAGs), controls free fatty acid (FFA) levels in cancer cells. The resulting MAGL-FFA pathway feeds into a diverse lipid network enriched in pro-tumorigenic signaling molecules and promotes migration, survival, and in vivo tumor growth. Aggressive cancer cells thus pair lipogenesis with high lipolytic activity to generate an array of pro-tumorigenic signals that support their malignant behavior.

Activity-Based Proteomic Analysis of Hydrolytic Enzymes in Human Cancer Cells

To identify enzyme activities that contribute to cancer pathogenesis, we conducted a functional proteomic analysis of a panel of aggressive and non-aggressive human cancer cell lines from multiple tumors of origin, including melanoma [aggressive (C8161, MUM2B), non-aggressive (MUM2C)], ovarian [aggressive (SKOV3), non-aggressive (OVCAR3)], and breast [aggressive (231MFP), non-aggressive (MCF7)] cancer. Aggressive cancer lines were confirmed to display much greater in vitro migration and in vivo tumor-growth rates compared to their non-aggressive counterparts (Figure S1), as previously shown (Jessani et al., 2004;Jessani et al., 2002Seftor et al., 2002Welch et al., 1991). Proteomes from these cancer lines were screened by activity-based protein profiling (ABPP) using serine hydrolase-directed fluorophosphonate (FP) activity-based probes (Jessani et al., 2002Patricelli et al., 2001). Serine hydrolases are one of the largest and most diverse enzyme classes in the human proteome (representing ~ 1–1.5% of all human proteins) and play important roles in many biochemical processes of potential relevance to cancer, such as proteolysis (McMahon and Kwaan, 2008Puustinen et al., 2009), signal transduction (Puustinen et al., 2009), and lipid metabolism (Menendez and Lupu, 2007Zechner et al., 2005). The goal of this study was to identify hydrolytic enzyme activities that were consistently altered in aggressive versus non-aggressive cancer lines, working under the hypothesis that these conserved enzymatic changes would have a high probability of contributing to the pathogenic state of cancer cells.

Among the more than 50 serine hydrolases detected in this analysis (Tables S13), two enzymes, KIAA1363 and MAGL, were found to be consistently elevated in aggressive cancer cells relative to their non-aggressive counterparts, as judged by spectral counting (Jessani et al., 2005Liu et al., 2004). We confirmed elevations in KIAA1363 and MAGL in aggressive cancer cells by gel-based ABPP, where proteomes are treated with a rhodamine-tagged FP probe and resolved by 1D-SDS-PAGE and in-gel fluorescence scanning (Figure 1A). In both cases, two forms of each enzyme were detected (Figure 1A), due to differential glycoslyation for KIAA1363 (Jessani et al., 2002), and possibly alternative splicing for MAGL (Karlsson et al., 2001). We have previously shown that KIAA1363 plays a role in regulating ether lipid signaling pathways in aggressive cancer cells (Chiang et al., 2006). On the other hand, very little was known about the function of MAGL in cancer.

Figure 1  MAGL is elevated in aggressive cancer cells, where the enzyme regulates monoacylgycerol (MAG) and free fatty acid (FFA) levels

The heightened activity of MAGL in aggressive cancer cells was confirmed using the substrate C20:4 MAG (Figure 1B). Since several enzymes have been shown to display MAG hydrolytic activity (Blankman et al., 2007), we confirmed the contribution that MAGL makes to this process in cancer cells using the potent and selective MAGL inhibitor JZL184 (Long et al., 2009a).

MAGL Regulates Free Fatty Acid Levels in Aggressive Cancer Cells

MAGL is perhaps best recognized for its role in degrading the endogenous cannabinoid 2-arachidonoylglycerol (2-AG, C20:4 MAG), as well as other MAGs, in brain and peripheral tissues (Dinh et al., 2002Long et al., 2009aLong et al., 2009bNomura et al., 2008). Consistent with this established function, blockade of MAGL by JZL184 (1 μM, 4 hr) produced significant elevations in the levels of several MAGs, including 2-AG, in each of the aggressive cancer cell lines (Figure 1C and Figure S2). Interestingly, however, MAGL inhibition also caused significant reductions in the levels of FFAs in aggressive cancer cells (Figure 1D and Figure S2). This surprising finding contrasts with the function of MAGL in normal tissues, where the enzyme does not, in general, control the levels of FFAs (Long et al., 2009aLong et al., 2009b;Nomura et al., 2008).

Metabolic labeling studies using the non-natural C17:0-MAG confirmed that MAGs are converted to LPC and LPE by aggressive cancer cells, and that this metabolic transformation is significantly enhanced by treatment with JZL184 (Figure S1). Finally, JZL184 treatment did not affect the levels of MAGs and FFAs in non-aggressive cancer lines (Figure 1C, D), consistent with the negligible expression of MAGL in these cells (Figure 1A, B).

We next stably knocked down MAGL expression by RNA interference technology using two independent shRNA probes (shMAGL1, shMAGL2), both of which reduced MAGL activity by 70–80% in aggressive cancer lines (Figure 2A, D and Figure S2). Other serine hydrolase activities were unaffected by shMAGL probes (Figure 2A, D and Figures S2), confirming the specificity of these reagents. Both shMAGL probes caused significant elevations in MAGs and corresponding reductions in FFAs in aggressive melanoma (Figure 2B, C), ovarian (Figure 2E, F), and breast cancer cells (Figure S2).

Figure 2  Stable shRNA-mediated knockdown of MAGL lowers FFA levels in aggressive cancer cells.

Together, these data demonstrate that both acute (pharmacological) and stable (shRNA) blockade of MAGL cause elevations in MAGs and reductions in FFAs in aggressive cancer cells. These intriguing findings indicate that MAGL is the principal regulator of FFA levels in aggressive cancer cells. Finally, we confirmed that MAGL activity (Figure 3A, B) and FFA levels (Figure 3C) are also elevated in high-grade primary human ovarian tumors compared to benign or low-grade tumors. Thus, heightened expression of the MAGL-FFA pathway is a prominent feature of both aggressive human cancer cell lines and primary tumors.

Figure 3  High-grade primary human ovarian tumors possess elevated MAGL activity and FFAs compared to benign tumors.

Disruption of MAGL Expression and Activity Impairs Cancer Pathogenicity

shMAGL cancer lines were next examined for alterations in pathogenicity using a set of in vitro and in vivo assays. shMAGL-melanoma (C8161), ovarian (SKOV3), and breast (231MFP) cancer cells exhibited significantly reduced in vitro migration (Figure 4A, F and Figure S2), invasion (Figure 4B, G and Figure S2), and cell survival under serum-starvation conditions (Figure 4C, H and Figure S2). Acute pharmacological blockade of MAGL by JZL184 also decreased cancer cell migration (Figure S2), but not survival, possibly indicating that maximal impairments in cancer aggressiveness require sustained inhibition of MAGL.

Figure 4  shRNA-mediated knockdown and pharmacological inhibition of MAGL impair cancer aggressiveness.

MAGL Overexpression Increases FFAs and the Aggressiveness of Cancer Cells

Stable MAGL-overexpressing (MAGL-OE) and control [expressing an empty vector or a catalytically inactive version of MAGL, where the serine nucleophile was mutated to alanine (S122A)] variants of MUM2C and OVCAR3 cells were generated by retroviral infection and evaluated for their respective MAGL activities by ABPP and C20:4 MAG substrate assays. Both assays confirmed that MAGL-OE cells possess greater than 10-fold elevations in MAGL activity compared to control cells (Figure 5A and Figure S4). MAGL-OE cells also showed significant reductions in MAGs (Figure 5B andFigure S4) and elevated FFAs (Figure 5C and Figure S4). This altered metabolic profile was accompanied by increased migration (Figure 5D and Figure S4), invasion (Figure 5E and Figure S4), and survival (Figure S4) in MAGL-OE cells. None of these effects were observed in cancer cells expressing the S122A MAGL mutant, indicating that they require MAGL activity.  MAGL-OE MUM2C cells also showed enhanced tumor growth in vivo compared to control cells (Figure 5F). Notably, the increased tumor growth rate of MAGL-OE MUM2C cells nearly matched that of aggressive C8161 cells (Figure S4). These data indicate that the ectopic expression of MAGL in non-aggressive cancer cells is sufficient to elevate their FFA levels and promote pathogenicity both in vitro and in vivo.

Figure 5 Ectopic expression of MAGL elevates FFA levels and enhances the in vitro and in vivo pathogenicity of MUM2C melanoma cells.

Metabolic Rescue of Impaired Pathogenicity in MAGL-Disrupted Cancer Cells

MAGL could support the aggressiveness of cancer cells by either reducing the levels of its MAG substrates, elevating the levels of its FFA products, or both. Among MAGs, the principal signaling molecule is the endocannabinoid 2-AG, which activates the CB1 and CB2 receptors (Ahn et al., 2008Mackie and Stella, 2006). The endocannabinoid system has been implicated previously in cancer progression and, depending on the specific study, shown to promote (Sarnataro et al., 2006Zhao et al., 2005) or suppress (Endsley et al., 2007Wang et al., 2008) cancer pathogenesis. Neither a CB1 or CB2 antagonist rescued the migratory defects of shMAGL cancer cells (Figure S5). CB1 and CB2 antagonists also did not affect the levels of MAGs or FFAs in cancer cells (Figure S5).

We then determined whether increased FFA delivery could rectify the tumor growth defect observed for shMAGL cells in vivo. Immune-deficient mice were fed either a normal chow or high-fat diet throughout the duration of a xenograft tumor growth experiment. Notably, the impaired tumor growth rate of shMAGL-C8161 cells was completely rescued in mice fed a high-fat diet. In contrast, shControl-C8161 cells showed equivalent tumor growth rates on a normal versus high-fat diet. The recovery in tumor growth for shMAGL-C8161 cells in the high-fat diet group correlated with significantly increases levels of FFAs in excised tumors (Figure 6D). Collectively, these results indicate that MAGL supports the pathogenic properties of cancer cells by maintaining tonically elevated levels of FFAs.

Figure 6  Recovery of the pathogenic properties of shMAGL cancer cells by treatment with exogenous fatty acids.

MAGL Regulates a Fatty Acid Network Enriched in Pro-Tumorigenic Signals

Studies revealed that neither

  • the MAGL-FFA pathway might serve as a means to regenerate NAD+ (via continual fatty acyl glyceride/FFA recycling) to fuel glycolysis, or
  • increased lipolysis could be to generate FFA substrates for β-oxidation, which may serve as an important energy source for cancer cells (Buzzai et al., 2005), or
  • CPT1 blockade (reduced expression of CPT1 in aggressive cancer cells (data not shown) has been reported previously (Deberardinis et al., 2006))

providing evidence against a role for β-oxidation as a downstream mediator of the pathogenic effects of the MAGL-fatty acid pathway.

Considering that FFAs are fundamental building blocks for the production and remodeling of membrane structures and signaling molecules, perturbations in MAGL might be expected to affect several lipid-dependent biochemical networks important for malignancy. To test this hypothesis, we performed lipidomic analyses of cancer cell models with altered MAGL activity, including comparisons of:

  1. MAGL-OE versus control cancer cells (OVCAR3, MUM2C), and
  2. shMAGL versus shControl cancer cells (SKOV3, C8161).

Complementing these global profiles, we also conducted targeted measurements of specific bioactive lipids (e.g., prostaglandins) that are too low in abundance for detection by standard lipidomic methods. The resulting data sets were then mined to identify a common signature of lipid metabolites regulated by MAGL, which we defined as metabolites that were significantly increased or reduced in MAGL–OE cells and showed the opposite change in shMAGL cells relative to their respective control groups (Figure 7A, B and Table S4).

Figure 7  MAGL regulates a lipid network enriched in pro-tumorigenic signaling molecules.

Most of the lipids in the MAGL-fatty acid network, including several lysophospholipids (LPC, LPA, LPE), ether lipids (MAGE, alkyl LPE), phosphatidic acid (PA), and prostaglandin E2 (PGE2), displayed similar profiles to FFAs, being consistently elevated and reduced in MAGL-OE and shMAGL cells, respectively. Only MAGs were found to show the opposite profile (elevated and reduced in shMAGL and MAGL-OE cells, respectively). Interestingly, virtually this entire lipidomic signature was also observed in aggressive cancer cells when compared to their non-aggressive counterparts (e.g., C8161 versus MUM2C and SKOV3 versus OVCAR3, respectively; Table S4). These findings demonstrate that MAGL regulates a lipid network in aggressive cancer cells that consists of not only FFAs and MAGs, but also a host of secondary lipid metabolites. Increases (rather than decreases) in LPCs and LPEs were observed in JZL184-treated cells (Figure S1 and Table S4). These data indicate that acute and chronic blockade of MAGL generate distinct metabolomic effects in cancer cells, likely reflecting the differential outcomes of short- versus long-term depletion of FFAs.

Within the MAGL-fatty acid network are several pro-tumorigenic lipid messengers, including LPA and PGE2, that have been reported to promote the aggressiveness of cancer cells (Gupta et al., 2007Mills and Moolenaar, 2003). Metabolic labeling studies confirmed that aggressive cancer cells can convert both MAGs and FFAs (Figure S1) to LPA and PGE2 and, for MAGs, this conversion was blocked by JZL184 (Figure S1). Interestingly, treatment with either LPA or PGE2 (100 nM, 4 hr) rescued the impaired migration of shMAGL cancer cells at concentrations that did not affect the migration of shControl cells (Figure 7E).

Heightened lipogenesis is an established early hallmark of dysregulated metabolism and pathogenicity in cancer (Menendez and Lupu, 2007). Cancer lipogenesis appears to be driven principally by FAS, which is elevated in most transformed cells and important for survival and proliferation (De Schrijver et al., 2003;Kuhajda et al., 2000Vazquez-Martin et al., 2008). It is not yet clear how FAS supports cancer growth, but most of the proposed mechanisms invoke pro-tumorigenic functions for the enzyme s fatty acid products and their lipid derivatives (Menendez and Lupu, 2007). This creates a conundrum, since the fatty acid molecules produced by FAS are thought to be rapidly incorporated into neutral- and phospho-lipids, pointing to the need for complementary lipolytic pathways in cancer cells to release stored fatty acids for metabolic and signaling purposes (Prentki and Madiraju, 2008Przybytkowski et al., 2007). Consistent with this hypothesis, we found that acute treatment with the FAS inhibitor C75 (40 μM, 4 h) did not reduce FFA levels in cancer cells (data not shown). Furthermore, aggressive and non-aggressive cancer cells exhibited similar levels of FAS (data not shown), indicating that lipogenesis in the absence of paired lipolysis may be insufficient to confer high levels of malignancy.

Here we show that aggressive cancer cells do indeed acquire the ability to liberate FFAs from neutral lipid stores as a consequence of heightened expression of MAGL. MAGL and its FFA products were found to be elevated in aggressive human cancer cell lines from multiple tissues of origin, as well as in high-grade primary human ovarian tumors. These data suggest that the MAGL-FFA pathway may be a conserved feature of advanced forms of many types of cancer. Further evidence in support of this premise originates from gene expression profiling studies, which have identified increased levels of MAGL in primary human ductal breast tumors compared to less malignant medullary breast tumors (Gjerstorff et al., 2006). The key role that MAGL plays in regulating FFA levels in aggressive cancer cells contrasts with the function of this enzyme in normal tissues, where it mainly controls the levels of MAGs, but not FFAs (Long et al., 2009b). These data thus provide a striking example of the co-opting of an enzyme by cancer cells to serve a distinct metabolic purpose that supports their pathogenic behavior.

Taken together, our results indicate that MAGL serves as key metabolic hub in aggressive cancer cells, where the enzyme regulates a fatty acid network that feeds into a number of pro-tumorigenic signaling pathways.

 

7.7.8 Pirin regulates epithelial to mesenchymal transition and down-regulates EAF/U19 signaling in prostate cancer cells

7.7.8.1  Pirin regulates epithelial to mesenchymal transition independently of Bcl3-Slug signaling

Komai K1Niwa Y1Sasazawa Y1Simizu S2.
FEBS Lett. 2015 Mar 12; 589(6):738-43
http://dx.doi.org:/10.1016/j.febslet.2015.01.040

Highlights

  • Pirin decreases E-cadherin expression and induces EMT.
  • The induction of EMT by Pirin is achieved through a Bcl3 independent pathway.
  • Pirin may be a novel target for cancer therapy.

Epithelial to mesenchymal transition (EMT) is an important mechanism for the initial step of metastasis. Proteomic analysis indicates that Pirin is involved in metastasis. However, there are no reports demonstrating its direct contribution. Here we investigated the involvement of Pirin in EMT. In HeLa cells, Pirin suppressed E-cadherin expression and regulated the expression of other EMT markers. Furthermore, cells expressing Pirin exhibited a spindle-like morphology, which is reminiscent of EMT. A Pirin mutant defective for Bcl3 binding decreased E-cadherin expression similar to wild-type, suggesting that Pirin regulates E-cadherin independently of Bcl3-Slug signaling. These data provide direct evidence that Pirin contributes to cancer metastasis.

Pirin regulates the expression of E-cadherin and EMT markers

In melanoma, Pirin enhances NF-jB activity and increases Slug expression by binding Bcl3 [31], and it may also be involved in adenoid cystic tumor metastasis [23]. Since Slug suppresses E-cadherin transcription and is recognized as a major EMT inducer, we hypothesized that Pirin may regulate EMT through inducing Slug expression. To investigate whether Pirin regulates EMT, we measured E-cadherin expression following Pirin knockdown. As shown in Fig. 1A and B, E-cadherin expression was significantly increased following Pirin knockdown indicating that it may promote EMT. To confirm this, we established Pirin-expressing HeLa cells (Fig. 1C), which inhibited the expression of E-cadherin (Fig. 1D). Additionally, the expression of Occludin, an epithelial marker, was decreased, and several mesenchymal markers, including Fibronectin, N-cadherin, and Vimentin, were increased by Pirin expression (Fig. 1D). These data suggest that Pirin promotes EMT.

Pirin induces EMT-associated cell morphological changes

As mentioned above, cells undergo morphological changes during EMT. Therefore, we next analyzed whether Pirin expression affects cell morphology. Quantitative analysis of morphological changes was based on cell circularity, {4p(area)/(perimeter)2}100, which decreases during EMT-associated morphological changes [34–36]. Indeed, TGF-b or TNF-a exposure induced EMTassociated cell morphological changes in HeLa cells (data not shown). Employing this parameter of circularity, we compared the morphology of our established HeLa/Pirin-GFP cells with control HeLa/GFP cells. Although the control HeLa/GFP cells displayed a cobblestone-like morphology, HeLa/Pirin-GFP cells were elongated in shape (Fig. 2A). Indeed, compared with control cells, the circularity of HeLa/Pirin-GFP cells was significantly decreased (Fig. 2B). To confirm that these observations were dependent on Pirin expression, HeLa/Pirin-GFP cells were treated with an siRNA targeting Pirin. HeLa/Pirin-GFP cells recovered a cobblestone-like morphology (Fig. 2C) and circularity (Fig. 2D) when treated with Pirin siRNA indicating that Pirin expression induces EMT.

Pirin induces cell migration

During EMT cells acquire migratory capabilities. Therefore, we analyzed whether Pirin affects cell migration. HeLa cells were treated with an siRNA targeting Pirin and migration was assessed using a wound healing assay. Although Pirin knockdown had no effect on cell proliferation (data not shown), wound repair was inhibited in Pirin-depleted HeLa cells (Fig. 3A and B) suggesting that Pirin promoted cell migration. Furthermore, camptothecin treatment of HeLa/GFP cells caused decreased cell viability in a dose-dependent manner, whereas HeLa/Pirin-GFP cells were more resistantto drugtreatment (datanot shown).These results suggest that Pirin induces EMT-like phenotypes, such as cell migration and anticancer drug resistance.
Pirin regulates EMT independently of Bcl3-Slug signaling

To investigate whether Pirin controls E-cadherin expression at the transcriptional level, we measured E-cadherin promoter activity with a reporter assay. Indeed, the luciferase reporter analysis indicated that Pirin inhibited E-cadherin promoter activity (Fig. 4A and B). To determine if Bcl3 is involved in Pirin-induced EMT, we tested whether a Pirin mutant defective in Bcl3 binding could inhibit E-cadherin expression. We generated a mutation in the metal-binding cavity of Pirin(E103A) and confirmed that it disrupted Bcl3 binding. In vitro GST pull-down analysis using recombinant Pirin and Bcl3/ARD demonstrated that the Pirin mutant was defective for Bcl3 binding compared to wild-type (Fig. 5A). Interestingly, expression of both wild-type Pirin and the mutant defective in Bcl3 binding reduced E-cadherin gene and protein expression (Fig. 5B and C). Taken together these results indicate that Pirin decreases E-cadherin expression without binding Bcl3, and suggest that Pirin regulates EMT independently of Bcl3-Slug signaling.

Discussion

A characteristic feature of EMT is the disruption of epithelial cell–cell contact, which is achieved by reduced E-cadherin expression. Therefore, revealing the regulatory pathways controlling E-cadherin expression may elucidate the mechanisms of EMT. Several transcription factors regulate E-cadherin transcription. For instance,Snail,Slug,Twist,and Zebact as mastertranscriptional regulators that bind the consensus E-box sequence in the E-cadherin gene promoter and decrease the transcriptional activity [38]. Since Pirin regulates the transcription of Slug [31], we hypothesized that Pirin may also regulate EMT. In this study we demonstrated that Pirin decreases E-cadherin expression, and induces EMT and cancer malignant phenotypes. Since EMT is an initial step of metastasis, Pirin may contribute to cancer progression. We next examined whether the regulation of EMT by Pirin is attributed to Bcl3 binding and the induction of Slug. To this end, we generated a Pirin mutant (E103A) defective for Bcl3 binding (Fig. 5A). Single Fe2+ ion chelating is coordinated by His56, His58, His101, and Glu103 of Pirin, and the N-terminal domain containing these residues is highly conserved between mammals, plants, fungi, and prokaryotic organisms [15,27]. Therefore, it has been predicted that this N-terminal domain containing the metal-binding cavity is important for Pirin function [20,26,31]. Indeed, TPh A inserts into the metal-binding cavity and inhibits binding to Bcl3 suggesting that the interaction occurs with the metal-binding cavity of Pirin [31]. In contrast, Hai Pang suggests that a Pirin–Bcl3– (p50)2 complex forms between acidic regions of the N-terminal Pirin domain at residues 77–82, 97–103 and 124–128 with a basic patch of Bcl3 [27]. In this study, we mutated Glutamic acid 103, a residue common between Hai Pang’s model and Pirin’s metalbinding cavity. Pull-down analysis indicated that an E103A mutant is defectiveinfor Bcl3binding(Fig.5A). Thisis the firstexperimental demonstration showing that Glu103 of Pirin is important Bcl3 binding. However, expression of the E103A mutant suppressed Ecadherin gene expression similarly to wild-type Pirin (Fig. 5B and C). Although the Bcl3–(p50)2 complex participates in oncogene addiction in cervical cells [39,40], expression of Pirin in HeLa cells did not increase Slug expression (data not shown). Therefore, we concludethatPirindecreasesE-cadherinexpressionindependently of Bcl3-Slug signaling. To understand how Pirin suppresses E-cadherin gene expression, we analyzed E-cadherin promoter activity (Fig. 4). Since Pirin decreased the activity of the E-cadherin promoter (995+1), we constructed a series of promoter deletion mutants (795+1, 565+1, 365+1, 175+1) to identify a region important for Pirin-mediated regulation. Expression of Pirin decreased the transcriptional activity of all constructs (Supplementary Fig. S1A), suggesting that Pirin may suppress E-cadherin expression through element(s) in region 175+1. Yan-Nan Liu and colleagues proposed that this region contains four Sp1-binding sites and two E-boxes that regulate E-cadherin expression.

Fig. 1. Pirin regulates E-cadherin gene expression. (A, B) HeLa cells were transfected with siRNA targeting Pirin (siPirin#1 or #2) or control siRNA (siCTRL). Forty-eight hours after transfection, cDNA was used for PCR using primer sets specific against Pirin, E-cadherin and GAPDH (A). Forty-eight hours after transfection, HeLa cells were lysed and the lysates were analyzed by Western blot with the indicated antibodies (B). (C) Lysates from HeLa/Pirin-GFP and HeLa/GFP cells were analyzed by Western blot with the indicated antibodies. (D) cDNA from HeLa/GFP or HeLa/Pirin-GFP cells was used for PCR to determine the effect of Pirin on the expression of EMT marker genes.

Fig. 2. Pirin induces cell morphological changes associated with EMT. (A) Phase contrast and fluorescence microscopic images were taken of HeLa/GFP and HeLa/Pirin-GFP cells. (B) Cell circularity was defined as form factor, {4p(area)/(perimeter)2}100 [%], and calculated using Image J software. A random selection of 100 cells from each condition was measured. (C, D) Phase contrast and fluorescence microscopic images were taken of siRNA-treated HeLa/GFP and HeLa/Pirin-GFP cells. Each cell line was transfected with siPirin#2 or siCTRL. Cells were observed by microscopy 48 h after transfection (C) and circularity was measured (D). Data shown are means ± s.d. ⁄P <0.05, bars 100lm.

Fig. 3. Pirin knockdown suppresses cell migration. (A, B) HeLa cells were transfected with siPirin#2 or siCTRL. An artificial wound was created with a tip 24h after transfection and cells were cultured for an additional 12 h. For quantification, the cells were photographed after 12h of incubation (A) and the area covered by cells was measured using Image J and normalized to control cells (B).

Fig. 4. Pirin regulates E-cadherin promoter activity.(A). HeLacells were transfected with siPirin#2 or siGFP (control) and cultured for 24 h. The E-cadherin promoter construct (995+1) and phRL-TK vectorwere transfected and cellswere cultured for an additional 24 h. Luciferase activities were measured and normalized to Renilla luciferase activity. (B) HeLa cells were transfected with the promoter construct (995+1), phRL-TK vector, and a Pirin expression vector. After 24 h, luciferase activities were measured and normalized to Renilla luciferase activity. Data are the mean ± s.d. ⁄P < 0.05.

Fig. 5. Pirin decreases E-cadherin expression in a Bcl3-independent manner. (A) Purified His6-Pirin and His6-Pirin(E103A) were incubated with Glutathione-Sepharose beads conjugated to GST or GST-Bcl3/ARD. The samples were analyzed by Western blot. (B, C) HeLa cells were transfected with vectors encoding GFP, Pirin-GFP, or Pirin(E103A)GFP. Cells were lysed 48 h after transfection and lysates were analyzed by Western blot (B). RNA collected at 48h was used for RT-PCR with the specified primer sets for each gene (C).

7.7.8.2 1324 PIRIN DOWN-REGULATES THE EAF2/U19 SIGNALING AND RETARDS THE GROWTH INHIBITION INDUCED BY EAF2/U19 IN PROSTATE CANCER CELLS

Zhongjie Qiao, Dan Wang, Zhou Wang
The Journal of Urology Apr 2013; 189(4), Supplement: e541
http://dx.doi.org/10.1016/j.juro.2013.02.2678
EAF2/U19, as the tumor suppressor, has been reported to induce apoptosis of LNCaP cells and suppress AT6.1 xenograft prostate tumor growth in vivo, and its expression level is down-regulated in advanced human prostate cancer. EAF2/U19 is also a putative transcription factor with a transactivation domain and capability of sequence-specific DNA binding. Identification and characterization of the binding partners and regulators of EAF2/U19 is essential to understand its function in regulating apoptosis/survival of prostate cancer cells.

7.7.8.3 Pirin Inhibits Cellular Senescence in Melanocytic Cells

Cellular senescence has been widely recognized as a tumor suppressing mechanism that acts as a barrier to cancer development after oncogenic stimuli. A prominent in vivo model of the senescence barrier is represented by nevi, which are composed of melanocytes that, after an initial phase of proliferation induced by activated oncogenes (most commonly BRAF), are blocked in a state of cellular senescence. Transformation to melanoma occurs when genes involved in controlling senescence are mutated or silenced and cells reacquire the capacity to proliferate. Pirin (PIR) is a highly conserved nuclear protein that likely functions as a transcriptional regulator whose expression levels are altered in different types of tumors. We analyzed the expression pattern of PIR in adult human tissues and found that it is expressed in melanocytes and has a complex pattern of regulation in nevi and melanoma: it is rarely detected in mature nevi, but is expressed at high levels in a subset of melanomas. Loss of function and overexpression experiments in normal and transformed melanocytic cells revealed that PIR is involved in the negative control of cellular senescence and that its expression is necessary to overcome the senescence barrier. Our results suggest that PIR may have a relevant role in melanoma progression

Cellular senescence is a physiological process through which normal somatic cells lose their ability to divide and enter an irreversible state of cell cycle arrest, although they remain viable and metabolically active.1,2The specific molecular circuitry underlying the onset of cellular senescence is dependent on the type of stimulus and on the cellular context. A central role is held by the activation of the tumor suppressor proteins p53 and retinoblastoma susceptibility protein (pRB),3–5 which act by interfering with the transcriptional program of the cell and ultimately arresting cell cycle progression.

In the last decade, senescence has been recognized as a major barrier against the development of tumors in mammals.6–8 One of the most prominent in vivo examples is represented by nevi, in which cells proliferate after oncogene activation and then become senescent. Melanoma is a highly aggressive form of neoplasm often observed to derive from nevi, and the transition implies suppression of the mechanisms that sustain the onset and maintenance of senescence.9 In fact, many of the melanoma-associated tumor suppressor genes identified to date are themselves involved in control of senescence, including BRAF (encoding serine/threonine-protein kinase B-raf), CKD4 (cyclin-dependent kinase 4), and CDKN2A (encoding cyclin-dependent kinase inhibitor 2A isoforms p16INK4a and p19ARF).3,10

Nevi frequently harbor oncogenic mutations of the tyrosine kinase BRAF gene, particularly V600E,11 andBRAFV600E is also found in approximately 70% of cutaneous melanomas.12 Expression of BRAFV600E in human melanocytes leads to oncogene-induced senescence,8 which can be considered as a mechanism that protects from malignant progression. In time, some cells may eventually escape senescence, probably through the acquisition of additional genetic abnormalities, thus favoring transformation to melanoma.13

Pirin (PIR) is a highly conserved nuclear protein belonging to the Cupin superfamily14 whose function is, to date, poorly characterized. It has been described as a putative transcriptional regulator on the basis of its physical association with the nuclear I/CCAAT box transcription factor NFI/CTF115 and with the B-cell lymphoma protein, BCL-3, a regulator of NF-κB/Rel activity. A recent report shows that PIR controls melanoma cell migration through the transcriptional regulation of snail homolog 2, SNAI2 (previously SLUG).16 Other reports described quercetinase enzymatic activity,17 and regulation of apoptosis18,19 and stress response, unveiling a high degree of cell-type and species specificity in PIR function.

There is evidence of variations in PIR expression levels in different types of malignancies, but a systematic analysis of PIR expression in human tumors has been lacking. We analyzed PIR expression pattern in a collection of normal and neoplastic human tissues and found that it is expressed in scattered melanocytes, virtually absent in more mature regions of nevi, and present at high levels in a subset of melanomas. Functional studies performed in normal and transformed melanocytic cells revealed that PIR ablation results in cellular senescence, and that PIR levels decrease in response to senescence stimuli. Our results suggest that PIR may be a relevant player in the negative control of cellular senescence in PIR-expressing melanomas.

PIR overexpression in melanoma

Figure 3  PIR overexpression in PIR melanoma cells has no effect on proliferation.
PIR Expression Is Down-Regulated by BRAF Activation and Camptothecin Treatment

BRAF mutations are frequent in nevi, and are directly linked to the induction of oncogene-induced senescence. Variations in PIR expression levels were therefore investigated in an experimental model of senescence induced by oncogenic BRAF. Human diploid fibroblasts (TIG3–hTERT) expressing a conditional form of constitutively activated BRAF fused to the ligand-binding domain of the estrogen receptor (ER) rapidly undergo oncogene-induced senescence on treatment with 4-hydroxytamoxifen (OHT).28,29 PIR protein and mRNA levels were measured in TIG3-BRAF-ER cells at different time points of treatment with 800 nmol/L OHT. PIR expression was significantly repressed both at the mRNA and at the protein level after BRAF activation (Figure 6A), and remained at low levels after 120 hours, suggesting that a significant reduction of PIR expression is associated with the establishment of oncogene-induced senescence in different cell types.

7.7.9 O-GlcNAcylation at promoters, nutrient sensors, and transcriptional regulation

Brian A. Lewis
Biochim et Biophys Acta (BBA) – Gene Regulatory Mechanisms Nov 2013; 1829(11): 1202–1206
http://dx.doi.org/10.1016/j.bbagrm.2013.09.003

Highlights

  • This review article discusses recent advances in the links between O-GlcNAc and transcriptional regulation.
  • Discusses several systems to illustrate O-GlcNAc dynamics: Tet proteins, MLL complexes, circadian clock proteins and RNA pol II.
  • Suggests that promoters are nutrient sensors.

Post-translational modifications play important roles in transcriptional regulation. Among the less understood PTMs is O-GlcNAcylation. Nevertheless, O-GlcNAcylation in the nucleus is found on hundreds of transcription factors and coactivators and is often found in a mutually exclusive ying–yang relationship with phosphorylation. O-GlcNAcylation also links cellular metabolism directly to the proteome, serving as a conduit of metabolic information to the nucleus. This review serves as a brief introduction to O-GlcNAcylation, emphasizing its important thematic roles in transcriptional regulation, and highlights several recent and important additions to the literature that illustrate the connections between O-GlcNAc and transcription.

links between O-GlcNAc and transcriptional regulation.

links between O-GlcNAc and transcriptional regulation.

http://ars.els-cdn.com/content/image/1-s2.0-S1874939913001351-gr1.sml
links between O-GlcNAc and transcriptional regulation.

systems to illustrate O-GlcNAc dynamics

systems to illustrate O-GlcNAc dynamics

http://ars.els-cdn.com/content/image/1-s2.0-S1874939913001351-gr2.sml
systems to illustrate O-GlcNAc dynamics

7.7.10 O-GlcNAcylation in cellular functions and human diseases

Yang YR1Suh PG2.
Adv Biol Regul. 2014 Jan; 54:68-73
http://dx.doi.org:/10.1016/j.jbior.2013.09.007

O-GlcNAcylation is dynamic and a ubiquitous post-translational modification. O-GlcNAcylated proteins influence fundamental functions of proteins such as protein-protein interactions, altering protein stability, and changing protein activity. Thus, aberrant regulation of O-GlcNAcylation contributes to the etiology of chronic diseases of aging, including cancer, cardiovascular disease, metabolic disorders, and Alzheimer’s disease. Diverse cellular signaling systems are involved in pathogenesis of these diseases. O-GlcNAcylated proteins occur in many different tissues and cellular compartments and affect specific cell signaling. This review focuses on the O-GlcNAcylation in basic cellular functions and human diseases.

O-GlcNAcylated proteins influence protein phosphorylation and protein-protein interactions

O-GlcNAcylated proteins influence protein phosphorylation and protein-protein interactions

http://ars.els-cdn.com/content/image/1-s2.0-S2212492613000717-gr2.sml
O-GlcNAcylated proteins influence protein phosphorylation and protein-protein interactions

aberrant regulation of O-GlcNAcylation in disease

aberrant regulation of O-GlcNAcylation in disease

http://ars.els-cdn.com/content/image/1-s2.0-S2212492613000717-gr3.sml
aberrant regulation of O-GlcNAcylation in disease

 Comment:

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

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Evolution and Medicine

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

 

http://paleoaerie.org/2015/01/21/what-has-evolution-done-for-me-lately/

Excerpt of article

Cancer is an inescapable fact of life. All of us with either die from it or know someone who will. Cancer is so prevalent because it isn’t a disease in the way a flu or a cold is. No outside force or germ is needed to cause cancer (although it can). It arises from the very way we are put together.  Most of the genes that are needed for multicellular life have been found to be associated with cancer. Cancer is a result of our natural genetic machinery that has been built up over billions of years breaking down over time.

CLONAL EVOLUTION OF CANCER. MEL GREAVES.HTTP://WWW.SCIENCE-CONNECTIONS.COM/TRENDS/SCIENCE_CONTENT/EVOLUTION_6.HTM

Cancer is not only a result of evolutionary processes, cancer itself follows evolutionary theory as it grows. The immune system places a selective pressure on cancer cells, keeping it in check until the cancer evolves a way to avoid it and surpass it in a process known as immunoediting. Cancers face selective pressures in the microenvironments in which they grow. Due to the fast growth of cancer cells, they suck up oxygen in the tissues, causing wildly fluctuating oxygen levels as the body tries to get oxygen to the tissues. This sort of situation is bad for normal tissues and so it is for cancer, at least until they evolve and adapt. At some point, some cancer cells will develop the ability to use what is called aerobic glycolysis to make the ATP we use for energy. Ordinarily, our cells only use glycolysis when they run out of oxygen because aerobic respiration (aka oxidative phosphorylation) is far more efficient. Cancer cells, on the other hand, learn to use glycolysis all the time, even in the presence of abundant oxygen. They may not grow as quickly when there is plenty of oxygen, but they are far better than normal cells at hypoxic, or low oxygen, conditions, which they create by virtue of their metabolism. Moreover, they are better at taking up nutrients because many of the metabolic pathways for aerobic respiration also influence nutrient uptake, so shifting those pathways to nutrient uptake rather than metabolism ensures cancer cells get first pick of any nutrients in the area. The Warburg Effect, as this is called, works by selective pressures hindering those cells that can’t do so and favoring those that can. Because cancer cells have loose genetic controls and they are constantly dividing, the cancer population can evolve, whereas the normal cells cannot.

Evolutionary theory can also be used to track cancer as it metastasizes. If a person has several tumors, it is possible to take biopsies of each one and use standard cladistic programs that are normally used to determine evolutionary relationships between organisms to find which tumor is the original tumor. If the original tumor is not one of those biopsied, it will tell you where the cancer originated within the body. You can thus track the progression of cancer throughout a person’s body. Expanding on this, one can even track the effect of cancer through its effects on how organisms interact within ecosystems, creating its own evolutionary stamp on the environment as its effects radiate throughout the ecosystem.

I’ve talked about cancer at decent length (although I could easily go one for many more pages) because it is less well publicly known than some of the other ways that evolutionary theory helps us out in medicine. The increasing resistance of bacteria and viruses to antibiotics is well known. Antibiotic resistance follows standard evolutionary processes, with the result that antibiotic resistant bacteria are expected to kill 10 million people a year by 2050.  People have to get a new flu shot every year because the flu viruses are legion and they evolve rapidly to bypass old vaccinations.  If we are to accurately predict how the viruses may adapt and properly prepare vaccines for the coming year, evolutionary theory must be taken into account. Without it, the vaccines are much less likely to be effective. Evolutionary studies have pointed out important changes in the Ebola virus and how those changes areaffecting its lethality, which will need to be taken into account for effective treatments. Tracking the origins of viruses, like the avian flu or swine flu, gives us information that will be useful in combating them or even stopping them at their source before they become a problem.

HTTP://WWW.MEDSCAPE.COM/VIEWARTICLE/756378

 

 

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Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com

Compilation of References by Leaders in Pharmaceutical Business Intelligence in the Journal http://pharmaceuticalintelligence.com about
Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation

Curator: Larry H Bernstein, MD, FCAP

Proteomics

  1. The Human Proteome Map Completed

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

http://pharmaceuticalintelligence.com/2014/08/28/the-human-proteome-map-completed/

  1. Proteomics – The Pathway to Understanding and Decision-making in Medicine

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/06/24/proteomics-the-pathway-to-
understanding-and-decision-making-in-medicine/

3. Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/10/22/advances-in-separations-technology-for-the-omics-and-clarification-         of-therapeutic-targets/

  1. Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-                metabolome/

5. Genomics, Proteomics and standards

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/06/genomics-proteomics-and-standards/

6. Proteins and cellular adaptation to stress

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/08/proteins-and-cellular-adaptation-to-stress/

 

Metabolomics

  1. Extracellular evaluation of intracellular flux in yeast cells

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2014/08/25/extracellular-evaluation-of-intracellular-flux-in-yeast-cells/

  1. Metabolomic analysis of two leukemia cell lines. I.

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2014/08/23/metabolomic-analysis-of-two-leukemia-cell-lines-_i/

  1. Metabolomic analysis of two leukemia cell lines. II.

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2014/08/24/metabolomic-analysis-of-two-leukemia-cell-lines-ii/

  1. Metabolomics, Metabonomics and Functional Nutrition: the next step in nutritional metabolism and biotherapeutics

Reviewer and Curator, Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/22/metabolomics-metabonomics-and-functional-nutrition-the-next-step-          in-nutritional-metabolism-and-biotherapeutics/

  1. Buffering of genetic modules involved in tricarboxylic acid cycle metabolism provides homeomeostatic regulation

Larry H. Bernstein, MD, FCAP, Reviewer and curator

http://pharmaceuticalintelligence.com/2014/08/27/buffering-of-genetic-modules-involved-in-tricarboxylic-acid-cycle-              metabolism-provides-homeomeostatic-regulation/

Metabolic Pathways

  1. Pentose Shunt, Electron Transfer, Galactose, more Lipids in brief

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

http://pharmaceuticalintelligence.com/2014/08/21/pentose-shunt-electron-transfer-galactose-more-lipids-in-brief/

  1. Mitochondria: More than just the “powerhouse of the cell”

Ritu Saxena, PhD

http://pharmaceuticalintelligence.com/2012/07/09/mitochondria-more-than-just-the-powerhouse-of-the-cell/

  1. Mitochondrial fission and fusion: potential therapeutic targets?

Ritu saxena

http://pharmaceuticalintelligence.com/2012/10/31/mitochondrial-fission-and-fusion-potential-therapeutic-target/

4.  Mitochondrial mutation analysis might be “1-step” away

Ritu Saxena

http://pharmaceuticalintelligence.com/2012/08/14/mitochondrial-mutation-analysis-might-be-1-step-away/

  1. Selected References to Signaling and Metabolic Pathways in PharmaceuticalIntelligence.com

Curator: Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/14/selected-references-to-signaling-and-metabolic-pathways-in-                     leaders-in-pharmaceutical-intelligence/

  1. Metabolic drivers in aggressive brain tumors

Prabodh Kandal, PhD

http://pharmaceuticalintelligence.com/2012/11/11/metabolic-drivers-in-aggressive-brain-tumors/

  1. Metabolite Identification Combining Genetic and Metabolic Information: Genetic association links unknown metabolites to functionally related genes

Writer and Curator, Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/10/22/metabolite-identification-combining-genetic-and-metabolic-                        information-genetic-association-links-unknown-metabolites-to-functionally-related-genes/

  1. Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation

Larry H Bernstein, MD, FCAP, author and curator

http://pharmaceuticalintelligence.com/2012/09/26/mitochondria-origin-from-oxygen-free-environment-role-in-aerobic-            glycolysis-metabolic-adaptation/

  1. Therapeutic Targets for Diabetes and Related Metabolic Disorders

Reporter, Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/08/20/therapeutic-targets-for-diabetes-and-related-metabolic-disorders/

10.  Buffering of genetic modules involved in tricarboxylic acid cycle metabolism provides homeomeostatic regulation

Larry H. Bernstein, MD, FCAP, Reviewer and curator

http://pharmaceuticalintelligence.com/2014/08/27/buffering-of-genetic-modules-involved-in-tricarboxylic-acid-cycle-              metabolism-provides-homeomeostatic-regulation/

11. The multi-step transfer of phosphate bond and hydrogen exchange energy

Larry H. Bernstein, MD, FCAP, Curator:

http://pharmaceuticalintelligence.com/2014/08/19/the-multi-step-transfer-of-phosphate-bond-and-hydrogen-                          exchange-energy/

12. Studies of Respiration Lead to Acetyl CoA

http://pharmaceuticalintelligence.com/2014/08/18/studies-of-respiration-lead-to-acetyl-coa/

13. Lipid Metabolism

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

http://pharmaceuticalintelligence.com/2014/08/15/lipid-metabolism/

14. Carbohydrate Metabolism

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

http://pharmaceuticalintelligence.com/2014/08/13/carbohydrate-metabolism/

15. Update on mitochondrial function, respiration, and associated disorders

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

http://pharmaceuticalintelligence.com/2014/07/08/update-on-mitochondrial-function-respiration-and-associated-                   disorders/

16. Prologue to Cancer – e-book Volume One – Where are we in this journey?

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

http://pharmaceuticalintelligence.com/2014/04/13/prologue-to-cancer-ebook-4-where-are-we-in-this-journey/

17. Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

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

http://pharmaceuticalintelligence.com/2014/04/04/introduction-the-evolution-of-cancer-therapy-and-cancer-research-          how-we-got-here/

18. Inhibition of the Cardiomyocyte-Specific Kinase TNNI3K

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

http://pharmaceuticalintelligence.com/2013/11/01/inhibition-of-the-cardiomyocyte-specific-kinase-tnni3k/

19. The Binding of Oligonucleotides in DNA and 3-D Lattice Structures

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

http://pharmaceuticalintelligence.com/2013/05/15/the-binding-of-oligonucleotides-in-dna-and-3-d-lattice-structures/

20. Mitochondrial Metabolism and Cardiac Function

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

http://pharmaceuticalintelligence.com/2013/04/14/mitochondrial-metabolism-and-cardiac-function/

21. How Methionine Imbalance with Sulfur-Insufficiency Leads to Hyperhomocysteinemia

Curator: Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/04/04/sulfur-deficiency-leads_to_hyperhomocysteinemia/

22. AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

Author and Curator: Stephen J. Williams, PhD

http://pharmaceuticalintelligence.com/2013/03/12/ampk-is-a-negative-regulator-of-the-warburg-effect-and-suppresses-         tumor-growth-in-vivo/

23. A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

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

http://pharmaceuticalintelligence.com/2012/12/03/a-second-look-at-the-transthyretin-nutrition-inflammatory-                         conundrum/

24. Mitochondrial Damage and Repair under Oxidative Stress

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

http://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/

25. Nitric Oxide and Immune Responses: Part 2

Author and Curator: Aviral Vatsa, PhD, MBBS

http://pharmaceuticalintelligence.com/2012/10/28/nitric-oxide-and-immune-responses-part-2/

26. Overview of Posttranslational Modification (PTM)

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

http://pharmaceuticalintelligence.com/2014/07/29/overview-of-posttranslational-modification-ptm/

27. Malnutrition in India, high newborn death rate and stunting of children age under five years

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

http://pharmaceuticalintelligence.com/2014/07/15/malnutrition-in-india-high-newborn-death-rate-and-stunting-of-                   children-age-under-five-years/

28. Update on mitochondrial function, respiration, and associated disorders

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

http://pharmaceuticalintelligence.com/2014/07/08/update-on-mitochondrial-function-respiration-and-associated-                  disorders/

29. Omega-3 fatty acids, depleting the source, and protein insufficiency in renal disease

Larry H. Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/06/omega-3-fatty-acids-depleting-the-source-and-protein-insufficiency-         in-renal-disease/

30. Introduction to e-Series A: Cardiovascular Diseases, Volume Four Part 2: Regenerative Medicine

Larry H. Bernstein, MD, FCAP, writer, and Aviva Lev- Ari, PhD, RN

http://pharmaceuticalintelligence.com/2014/04/27/larryhbernintroduction_to_cardiovascular_diseases-                                  translational_medicine-part_2/

31. Epilogue: Envisioning New Insights in Cancer Translational Biology
Series C: e-Books on Cancer & Oncology

Author & Curator: Larry H. Bernstein, MD, FCAP, Series C Content Consultant

http://pharmaceuticalintelligence.com/2014/03/29/epilogue-envisioning-new-insights/

32. Ca2+-Stimulated Exocytosis:  The Role of Calmodulin and Protein Kinase C in Ca2+ Regulation of Hormone                         and Neurotransmitter

Writer and Curator: Larry H Bernstein, MD, FCAP and
Curator and Content Editor: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/12/23/calmodulin-and-protein-kinase-c-drive-the-ca2-regulation-of-                    hormone-and-neurotransmitter-release-that-triggers-ca2-stimulated-exocy

33. Cardiac Contractility & Myocardial Performance: Therapeutic Implications of Ryanopathy (Calcium Release-                           related Contractile Dysfunction) and Catecholamine Responses

Author, and Content Consultant to e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC
Author and Curator: Larry H Bernstein, MD, FCAP
and Article Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/08/28/cardiac-contractility-myocardium-performance-ventricular-arrhythmias-      and-non-ischemic-heart-failure-therapeutic-implications-for-cardiomyocyte-ryanopathy-calcium-release-related-                    contractile/

34. Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility

Author and Curator: Larry H Bernstein, MD, FCAP Author: Stephen Williams, PhD, and Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/08/26/role-of-calcium-the-actin-skeleton-and-lipid-structures-in-signaling-and-cell-motility/

35. Identification of Biomarkers that are Related to the Actin Cytoskeleton

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2012/12/10/identification-of-biomarkers-that-are-related-to-the-actin-                           cytoskeleton/

36. Advanced Topics in Sepsis and the Cardiovascular System at its End Stage

Author: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/08/18/advanced-topics-in-Sepsis-and-the-Cardiovascular-System-at-its-              End-Stage/

37. The Delicate Connection: IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

Demet Sag, PhD, Author and Curator

http://pharmaceuticalintelligence.com/2013/08/04/the-delicate-connection-ido-indolamine-2-3-dehydrogenase-and-               immunology/

38. IDO for Commitment of a Life Time: The Origins and Mechanisms of IDO, indolamine 2, 3-dioxygenase

Demet Sag, PhD, Author and Curator

http://pharmaceuticalintelligence.com/2013/08/04/ido-for-commitment-of-a-life-time-the-origins-and-mechanisms-of-             ido-indolamine-2-3-dioxygenase/

39. Confined Indolamine 2, 3 dioxygenase (IDO) Controls the Homeostasis of Immune Responses for Good and Bad

Curator: Demet Sag, PhD, CRA, GCP

http://pharmaceuticalintelligence.com/2013/07/31/confined-indolamine-2-3-dehydrogenase-controls-the-hemostasis-           of-immune-responses-for-good-and-bad/

40. Signaling Pathway that Makes Young Neurons Connect was discovered @ Scripps Research Institute

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/06/26/signaling-pathway-that-makes-young-neurons-connect-was-                     discovered-scripps-research-institute/

41. Naked Mole Rats Cancer-Free

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

http://pharmaceuticalintelligence.com/2013/06/20/naked-mole-rats-cancer-free/

42. Late Onset of Alzheimer’s Disease and One-carbon Metabolism

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

http://pharmaceuticalintelligence.com/2013/05/06/alzheimers-disease-and-one-carbon-metabolism/

43. Problems of vegetarianism

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

http://pharmaceuticalintelligence.com/2013/04/22/problems-of-vegetarianism/

44.  Amyloidosis with Cardiomyopathy

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

http://pharmaceuticalintelligence.com/2013/03/31/amyloidosis-with-cardiomyopathy/

45. Liver endoplasmic reticulum stress and hepatosteatosis

Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2013/03/10/liver-endoplasmic-reticulum-stress-and-hepatosteatosis/

46. The Molecular Biology of Renal Disorders: Nitric Oxide – Part III

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/the-molecular-biology-of-renal-disorders/

47. Nitric Oxide Function in Coagulation – Part II

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

http://pharmaceuticalintelligence.com/2012/11/26/nitric-oxide-function-in-coagulation/

48. Nitric Oxide, Platelets, Endothelium and Hemostasis

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/08/nitric-oxide-platelets-endothelium-and-hemostasis/

49. Interaction of Nitric Oxide and Prostacyclin in Vascular Endothelium

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/09/14/interaction-of-nitric-oxide-and-prostacyclin-in-vascular-endothelium/

50. Nitric Oxide and Immune Responses: Part 1

Curator and Author:  Aviral Vatsa PhD, MBBS

http://pharmaceuticalintelligence.com/2012/10/18/nitric-oxide-and-immune-responses-part-1/

51. Nitric Oxide and Immune Responses: Part 2

Curator and Author:  Aviral Vatsa PhD, MBBS

http://pharmaceuticalintelligence.com/2012/10/28/nitric-oxide-and-immune-responses-part-2/

52. Mitochondrial Damage and Repair under Oxidative Stress

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/

53. Is the Warburg Effect the cause or the effect of cancer: A 21st Century View?

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/10/17/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-                 century-view/

54. Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                  proteolysis-and-cell-apoptosis/

55. Ubiquitin-Proteosome pathway, Autophagy, the Mitochondrion, Proteolysis and Cell Apoptosis: Part III

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2013/02/14/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                   proteolysis-and-cell-apoptosis-reconsidered/

56. Nitric Oxide and iNOS have Key Roles in Kidney Diseases – Part II

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/nitric-oxide-and-inos-have-key-roles-in-kidney-diseases/

57. New Insights on Nitric Oxide donors – Part IV

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/new-insights-on-no-donors/

58. Crucial role of Nitric Oxide in Cancer

Curator and Author: Ritu Saxena, Ph.D.

http://pharmaceuticalintelligence.com/2012/10/16/crucial-role-of-nitric-oxide-in-cancer/

59. Nitric Oxide has a ubiquitous role in the regulation of glycolysis -with a concomitant influence on mitochondrial function

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/09/16/nitric-oxide-has-a-ubiquitous-role-in-the-regulation-of-glycolysis-with-         a-concomitant-influence-on-mitochondrial-function/

60. Targeting Mitochondrial-bound Hexokinase for Cancer Therapy

Curator and Author: Ziv Raviv, PhD, RN 04/06/2013

http://pharmaceuticalintelligence.com/2013/04/06/targeting-mitochondrial-bound-hexokinase-for-cancer-therapy/

61. Biochemistry of the Coagulation Cascade and Platelet Aggregation – Part I

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/biochemistry-of-the-coagulation-cascade-and-platelet-aggregation/

Genomics, Transcriptomics, and Epigenetics

  1. What is the meaning of so many RNAs?

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

http://pharmaceuticalintelligence.com/2014/08/06/what-is-the-meaning-of-so-many-rnas/

  1. RNA and the transcription the genetic code

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

http://pharmaceuticalintelligence.com/2014/08/02/rna-and-the-transcription-of-the-genetic-code/

  1. A Primer on DNA and DNA Replication

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

http://pharmaceuticalintelligence.com/2014/07/29/a_primer_on_dna_and_dna_replication/

4. Synthesizing Synthetic Biology: PLOS Collections

Reporter: Aviva Lev-Ari

http://pharmaceuticalintelligence.com/2012/08/17/synthesizing-synthetic-biology-plos-collections/

5. Pathology Emergence in the 21st Century

Author and Curator: Larry Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/03/pathology-emergence-in-the-21st-century/

6. RNA and the transcription the genetic code

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

http://pharmaceuticalintelligence.com/2014/08/02/rna-and-the-transcription-of-the-genetic-code/

7. A Great University engaged in Drug Discovery: University of Pittsburgh

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2014/07/15/a-great-university-engaged-in-drug-discovery/

8. microRNA called miRNA-142 involved in the process by which the immature cells in the bone  marrow give                              rise to all the types of blood cells, including immune cells and the oxygen-bearing red blood cells

Aviva Lev-Ari, PhD, RN, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/24/microrna-called-mir-142-involved-in-the-process-by-which-the-                   immature-cells-in-the-bone-marrow-give-rise-to-all-the-types-of-blood-cells-including-immune-cells-and-the-oxygen-             bearing-red-blood-cells/

9. Genes, proteomes, and their interaction

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

http://pharmaceuticalintelligence.com/2014/07/28/genes-proteomes-and-their-interaction/

10. Regulation of somatic stem cell Function

Larry H. Bernstein, MD, FCAP, Writer and Curator    Aviva Lev-Ari, PhD, RN, Curator

http://pharmaceuticalintelligence.com/2014/07/29/regulation-of-somatic-stem-cell-function/

11. Scientists discover that pluripotency factor NANOG is also active in adult organisms

Larry H. Bernstein, MD, FCAP, Reporter

http://pharmaceuticalintelligence.com/2014/07/10/scientists-discover-that-pluripotency-factor-nanog-is-also-active-in-           adult-organisms/

12. Bzzz! Are fruitflies like us?

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/07/bzzz-are-fruitflies-like-us/

13. Long Non-coding RNAs Can Encode Proteins After All

Larry H Bernstein, MD, FCAP, Reporter

http://pharmaceuticalintelligence.com/2014/06/29/long-non-coding-rnas-can-encode-proteins-after-all/

14. Michael Snyder @Stanford University sequenced the lymphoblastoid transcriptomes and developed an
allele-specific full-length transcriptome

Aviva Lev-Ari, PhD, RN, Author and Curator

http://pharmaceuticalintelligence.com/014/06/23/michael-snyder-stanford-university-sequenced-the-lymphoblastoid-            transcriptomes-and-developed-an-allele-specific-full-length-transcriptome/

15. Commentary on Biomarkers for Genetics and Genomics of Cardiovascular Disease: Views by Larry H                                     Bernstein, MD, FCAP

Author: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/07/16/commentary-on-biomarkers-for-genetics-and-genomics-of-                        cardiovascular-disease-views-by-larry-h-bernstein-md-fcap/

16. Observations on Finding the Genetic Links in Common Disease: Whole Genomic Sequencing Studies

Author an curator: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/05/18/observations-on-finding-the-genetic-links/

17. Silencing Cancers with Synthetic siRNAs

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2013/12/09/silencing-cancers-with-synthetic-sirnas/

18. Cardiometabolic Syndrome and the Genetics of Hypertension: The Neuroendocrine Transcriptome Control Points

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/12/12/cardiometabolic-syndrome-and-the-genetics-of-hypertension-the-neuroendocrine-transcriptome-control-points/

19. Developments in the Genomics and Proteomics of Type 2 Diabetes Mellitus and Treatment Targets

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2013/12/08/developments-in-the-genomics-and-proteomics-of-type-2-diabetes-           mellitus-and-treatment-targets/

20. Loss of normal growth regulation

Larry H Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/06/loss-of-normal-growth-regulation/

21. CT Angiography & TrueVision™ Metabolomics (Genomic Phenotyping) for new Therapeutic Targets to Atherosclerosis

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/11/15/ct-angiography-truevision-metabolomics-genomic-phenotyping-for-           new-therapeutic-targets-to-atherosclerosis/

22.  CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

Genomics Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/30/cracking-the-code-of-human-life-the-birth-of-bioinformatics-                      computational-genomics/

23. Big Data in Genomic Medicine

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/12/17/big-data-in-genomic-medicine/

24. From Genomics of Microorganisms to Translational Medicine

Author and Curator: Demet Sag, PhD

http://pharmaceuticalintelligence.com/2014/03/20/without-the-past-no-future-but-learn-and-move-genomics-of-                      microorganisms-to-translational-medicine/

25. Summary of Genomics and Medicine: Role in Cardiovascular Diseases

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/01/06/summary-of-genomics-and-medicine-role-in-cardiovascular-diseases/

 26. Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious                      Depression

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/02/19/genomic-promise-for-neurodegenerative-diseases-dementias-autism-        spectrum-schizophrenia-and-serious-depression/

 27.  BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

Sudipta Saha, PhD

http://pharmaceuticalintelligence.com/2012/12/04/brca1-a-tumour-suppressor-in-breast-and-ovarian-cancer-functions-         in-transcription-ubiquitination-and-dna-repair/

28. Personalized medicine gearing up to tackle cancer

Ritu Saxena, PhD

http://pharmaceuticalintelligence.com/2013/01/07/personalized-medicine-gearing-up-to-tackle-cancer/

29. Differentiation Therapy – Epigenetics Tackles Solid Tumors

Stephen J Williams, PhD

      http://pharmaceuticalintelligence.com/2013/01/03/differentiation-therapy-epigenetics-tackles-solid-tumors/

30. Mechanism involved in Breast Cancer Cell Growth: Function in Early Detection & Treatment

     Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/17/mechanism-involved-in-breast-cancer-cell-growth-function-in-early-          detection-treatment/

31. The Molecular pathology of Breast Cancer Progression

Tilde Barliya, PhD

http://pharmaceuticalintelligence.com/2013/01/10/the-molecular-pathology-of-breast-cancer-progression

32. Gastric Cancer: Whole-genome reconstruction and mutational signatures

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/12/24/gastric-cancer-whole-genome-reconstruction-and-mutational-                   signatures-2/

33. Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine –                                                       Part 1 (pharmaceuticalintelligence.com)

Aviva  Lev-Ari, PhD, RN

http://pharmaceuticalntelligence.com/2013/01/13/paradigm-shift-in-human-genomics-predictive-biomarkers-and-personalized-medicine-part-1/

34. LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer                                         Personalized Treatment: Part 2

A Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/13/leaders-in-genome-sequencing-of-genetic-mutations-for-therapeutic-       drug-selection-in-cancer-personalized-treatment-part-2/

35. Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/13/personalized-medicine-an-institute-profile-coriell-institute-for-medical-        research-part-3/

36. Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of                           Cancer Scientific Leaders @http://pharmaceuticalintelligence.com

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/13/7000/Harnessing_Personalized_Medicine_for_ Cancer_Management-      Prospects_of_Prevention_and_Cure/

37.  GSK for Personalized Medicine using Cancer Drugs needs Alacris systems biology model to determine the in silico
effect of the inhibitor in its “virtual clinical trial”

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/11/14/gsk-for-personalized-medicine-using-cancer-drugs-needs-alacris-             systems-biology-model-to-determine-the-in-silico-effect-of-the-inhibitor-in-its-virtual-clinical-trial/

38. Personalized medicine-based cure for cancer might not be far away

Ritu Saxena, PhD

  http://pharmaceuticalintelligence.com/2012/11/20/personalized-medicine-based-cure-for-cancer-might-not-be-far-away/

39. Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/11/24/human-variome-project-encyclopedic-catalog-of-sequence-variants-         indexed-to-the-human-genome-sequence/

40. Inspiration From Dr. Maureen Cronin’s Achievements in Applying Genomic Sequencing to Cancer Diagnostics

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/10/inspiration-from-dr-maureen-cronins-achievements-in-applying-                genomic-sequencing-to-cancer-diagnostics/

41. The “Cancer establishments” examined by James Watson, co-discoverer of DNA w/Crick, 4/1953

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/09/the-cancer-establishments-examined-by-james-watson-co-discover-         of-dna-wcrick-41953/

42. What can we expect of tumor therapeutic response?

Author and curator: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/12/05/what-can-we-expect-of-tumor-therapeutic-response/

43. Directions for genomics in personalized medicine

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

http://pharmaceuticalintelligence.com/2013/01/27/directions-for-genomics-in-personalized-medicine/

44. How mobile elements in “Junk” DNA promote cancer. Part 1: Transposon-mediated tumorigenesis.

Stephen J Williams, PhD

http://pharmaceuticalintelligence.com/2012/10/31/how-mobile-elements-in-junk-dna-prote-cancer-part1-transposon-            mediated-tumorigenesis/

45. mRNA interference with cancer expression

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

 http://pharmaceuticalintelligence.com/2012/10/26/mrna-interference-with-cancer-expression/

46. Expanding the Genetic Alphabet and linking the genome to the metabolome

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-               metabolome/

47. Breast Cancer, drug resistance, and biopharmaceutical targets

Author and Curator: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/09/18/breast-cancer-drug-resistance-and-biopharmaceutical-targets/

48.  Breast Cancer: Genomic profiling to predict Survival: Combination of Histopathology and Gene Expression                            Analysis

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/12/24/breast-cancer-genomic-profiling-to-predict-survival-combination-of-           histopathology-and-gene-expression-analysis

49. Gastric Cancer: Whole-genome reconstruction and mutational signatures

Aviva  Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/12/24/gastric-cancer-whole-genome-reconstruction-and-mutational-                   signatures-2/

50. Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/08/22/genomic-analysis-fluidigm-technology-in-the-life-science-and-                   agricultural-biotechnology/

51. 2013 Genomics: The Era Beyond the Sequencing Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2013_Genomics

52. Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/Paradigm Shift in Human Genomics_/

Signaling Pathways

  1. Proteins and cellular adaptation to stress

Larry H Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/08/proteins-and-cellular-adaptation-to-stress/

  1. A Synthesis of the Beauty and Complexity of How We View Cancer:
    Cancer Volume One – Summary

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

http://pharmaceuticalintelligence.com/2014/03/26/a-synthesis-of-the-beauty-and-complexity-of-how-we-view-cancer/

  1. Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in
    serous endometrial tumors

Sudipta Saha, PhD

http://pharmaceuticalintelligence.com/2012/11/19/recurrent-somatic-mutations-in-chromatin-remodeling-ad-ubiquitin-           ligase-complex-genes-in-serous-endometrial-tumors/

4.  Prostate Cancer Cells: Histone Deacetylase Inhibitors Induce Epithelial-to-Mesenchymal Transition

Stephen J Williams, PhD

http://pharmaceuticalintelligence.com/2012/11/30/histone-deacetylase-inhibitors-induce-epithelial-to-mesenchymal-              transition-in-prostate-cancer-cells/

5. Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis

Author and Curator: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                   proteolysis-and-cell-apoptosis/

6. Signaling and Signaling Pathways

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2014/08/12/signaling-and-signaling-pathways/

7.  Leptin signaling in mediating the cardiac hypertrophy associated with obesity

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/11/03/leptin-signaling-in-mediating-the-cardiac-hypertrophy-associated-            with-obesity/

  1. Sensors and Signaling in Oxidative Stress

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/11/01/sensors-and-signaling-in-oxidative-stress/

  1. The Final Considerations of the Role of Platelets and Platelet Endothelial Reactions in Atherosclerosis and Novel
    Treatments

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/10/15/the-final-considerations-of-the-role-of-platelets-and-platelet-                      endothelial-reactions-in-atherosclerosis-and-novel-treatments

10.   Platelets in Translational Research – Part 1

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/10/07/platelets-in-translational-research-1/

11.  Disruption of Calcium Homeostasis: Cardiomyocytes and Vascular Smooth Muscle Cells: The Cardiac and
Cardiovascular Calcium Signaling Mechanism

Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to e-SERIES A:
Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/09/12/disruption-of-calcium-homeostasis-cardiomyocytes-and-vascular-             smooth-muscle-cells-the-cardiac-and-cardiovascular-calcium-signaling-mechanism/

12. The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and
Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia,
Similarities and Differences, and Pharmaceutical Targets

     Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to
e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and
Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/09/08/the-centrality-of-ca2-signaling-and-cytoskeleton-involving-calmodulin-       kinases-and-ryanodine-receptors-in-cardiac-failure-arterial-smooth-muscle-post-ischemic-arrhythmia-similarities-and-           differen/

13.  Nitric Oxide Signalling Pathways

Aviral Vatsa, PhD, MBBS

http://pharmaceuticalintelligence.com/2012/08/22/nitric-oxide-signalling-pathways/

14. Immune activation, immunity, antibacterial activity

Larry H. Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/06/immune-activation-immunity-antibacterial-activity/

15.  Regulation of somatic stem cell Function

Larry H. Bernstein, MD, FCAP, Writer and Curator    Aviva Lev-Ari, PhD, RN, Curator

http://pharmaceuticalintelligence.com/2014/07/29/regulation-of-somatic-stem-cell-function/

16. Scientists discover that pluripotency factor NANOG is also active in adult organisms

Larry H. Bernstein, MD, FCAP, Reporter

http://pharmaceuticalintelligence.com/2014/07/10/scientists-discover-that-pluripotency-factor-nanog-is-also-active-in-adult-organisms/

Read Full Post »

Read Full Post »

Cancer Metastasis

Author: Tilda Barliya PhD

Metastasis, a complex process that involves the spread of tumor cells, accounts for more than 90%of cancer-related mortality (1,2). A metastatic tumor cell has a treacherous journey to go through:

  • local invasion and intravasation
  • survival in the circulation
  • homing and extravasation into the parenchyma of distant organs
  • adaptation to the new environment
  • outgrowth of secondary lesions

Although tumor cells that are shed from the primary tumor disseminate throughout the body, they tend to colonize select organs, with characteristically different periods of latency and efficiency depending on tumor type or subtype (2).

Steven Paget’s century-old ‘seed and soil’ hypothesis (2, 9) likened tumor cells to ‘seeds’ that are systemically distributed, but that only inhabit particular environments, or ‘soils’, which are supportive to their sustained growth. Understanding the molecular complexity of this process is difficult and we’ll try to unravel some of the pathogenesis and cellular basis that support the metastatic process.

Progression models:

There are two major tumor progression models (2) :

  • Linear –  primary tumour cells undergo successive rounds of mutation and selection35, giving rise to a biologically heterogeneous cellular population in which a subset of malignant clones have accumulated genetic alterations, necessary for metastasis.
  • Parallel –  tumor cells may disseminate very early in malignant progression, colonize multiple secondary sites at different times and ultimately accumulate genetic changes independently from those incurred by the primary tumor.

While both theories are possible, the linear model is validated by both clinical evidence and animal models, the parallel model is mainly based on animal models and still under investigation for clinical clues.

Meera Saxena. Molecular Oncology
Volume 7, Issue 2 , Pages 283-296, April 2013

Drivers of metastasis

During the past few years several methods and studies have been used to find and correlate between a specific gene and it’s homing target.

These genes, which were found using next-generation sequencing and their equivalents, were also validated their actual functional consequences.

Figure 1 (Meera Saxena et al) represent some of the genes that were associated with organ-specific translocation (additional genes were recently identified and included in table 1 – Sethi N et all). Herein, we generally show the gene to organ-specific homing, yet we will not discuss each and every one of them.  An example of specific gene to organ will be further discussed in detail in follow up article.

Signalling pathways in cancer metastasis have been extensively studied at the level of individual proteins or as a linear cascade of proteins but they have been less frequently evaluated through a network approach (2). Understanding the different variables in the gene-metastasis network may be crucial for drug development.

For example;  the drug–gene–phenotype Connectivity Map approach was successfully used to identify the mTOR inhibitor rapamycin as an effective agent for overcoming dexamethasone resistance in acute lymphoblastic leukaemia (2, 4).

Microenvironment

“Non-neoplastic stromal cells have a function in the development of tumor metastasis. Stromal cells as important regulators of metastasis through their ability to influence cancer cell functions such as chemotaxis and invasion, as well as microenvironment properties. It should not come as a surprise that tumor angiogenesis was among the initial findings that supported a role for stromal cells in cancer metastasis; the poor vascular integrity of newly synthesized blood vessels within the tumour allows for the escape of malignant cells with the potential of distant spread” (2). Such cells include:

  • Tumour-associated macrophages,
  • Leukocytes and other immune cells,
  • Mesenchymal cells that reside in breast tissue
  • Mesenchymal cells and neuroendocrine cells

Although some of the molecular pathway was discovered, the molecular components that facilitate communication between tumour cells and individual stromal cells of the primary tumor have yet to be fully understood.

Circulating Tumor cells (CTC)

“Essential to cancer metastasis is the ability of primary tumor cells to enter the vasculature and to use these fluid ‘highways’ as a means to reach distant organs”. Tight vascular wall barriers, unfavorable conditions for survival in distant organs, and a rate-limiting acquisition of organ colonization functions are just some of the impediments to the formation of distant metastasis (2,5,6 ).

Despite their clear prognostic importance, the diagnostic value of CTCs is largely unknown and fairly unexplored. Research challenges both in detection and interpretation render their ability to  be clinically accepted. Additional research is needed to fully explore CTCs’ potential in to predict clinical response to therapy would also help to guide disease management.

Colonization

The colonization and outgrowth of tumor cells in a secondary organ is often considered the rate-limiting, as well as the most poorly delineated, step in the metastatic cascade. Understanding the functional involvement of the tumor stromal cells of the secondary site may be crucial to understanding their ability to colonize.

The pre-metastatic niche model shows that, preceding the arrival of  disseminated tumour cells (DTCs), bone marrow-derived haematopoietic stem cells are mobilized by tumour-derived factors and are recruited to the secondary site where they negotiate a more hospitable microenvironment to foster the survival and expansion of metastatic lesions. Inflammatory cytokines have emerged as crucial mediators of the pre-metastatic niche and self-seeding and include IL-6, SRC and NF-kB.

After surviving the adjustment to the secondary site, tumor cells must sustain their growth to develop overt metastases. Developmental pathways have emerged as important players in tumor progression and metastasis. These include: transforming growth factor-β (TGFβ), bone morphogenetic protein (BMP), WNT and Hedgehog.  These genes will trigger additional genes that will affect downstream steps of the colonization process.

Clinical Aspect

“As most metastatic cancers are inoperable, systemic treatments using chemotherapeutic or targeted therapy is often the only option to slow tumor growth or to relieve metastasis-associated morbidity”.  Genes and pathways that have crucial roles in primary tumour growth and metastasis are ideal targets for therapeutic inventions. One example is the oncogenic BRAF:  potent inhibitors of mutant BRAF, had initial clinical results which suggest dramatic efficacy in the treatment of metastatic malignant melanoma.  It is important to keep in mind that many cancers develop resistance to BRAF inhibitor and require used of next-generation drugs. More so,  the mechanism of resistance will be discussed elsewhere.

A sound framework of normal homeostatic mechanisms can improve our ability to understand and target tumor–stromal interactions in metastasis.

Summary:

“Despite recognizing the devastating consequences of metastasis, we are not yet able to effectively treat cancer that has spread to vital organs” .  Despite our increasing knowledge about metastatic colonization, we still hold little understanding of how metastatic tumour cells behave as solitary disseminated entities. Understanding the genomics of metastatic cancer cells and the complexity of the metastasis process will enable us to develop a better target-therapeutic drugs.

 

References:

1. Naure Review: Cancer: focus on metastasis. http://www.nature.com/nrc/focus/metastasis/index.html

2. Nilay Sethi and Yibin Kang. Unravelling the complexity of metastasis — molecular understanding and targeted therapies. Nature Reviews Cancer 2011; 11:732- 748. http://www.nature.com/nrc/journal/v11/n10/abs/nrc3125.html

3. Meera Saxena and Gerhard Christophor. Rebuilding cancer metastasis in the mouse. Molecular Oncology 2013, 7(2):283-296. http://www.moloncol.org/article/S1574-7891(13)00033-1/abstract

4. Lamb, J. et al. The Connectivity Map: using geneexpression signatures to connect small molecules, genes, and disease. Science 2006 313, 1929–1935. http://www.sciencemag.org/content/313/5795/1929.short

5. Chiang AC and Massagué J. Molecular basis of metastasis. N Engl J Med. 2008 Dec 25;359(26):2814 23 ;http://www.ncbi.nlm.nih.gov/pubmed/19109576

6. By: Ritu Saxena PhD. In focus: Circulating Tumor Cells. http://pharmaceuticalintelligence.com/2013/06/24/in-focus-circulating-tumor-cells/

7.   Davies, H. et al. Mutations of the BRAF gene in human cancer. Nature 2002, 417, 949–954. http://www.nature.com/nature/journal/v417/n6892/full/nature00766.html

8. Arozarena, I. et al. Oncogenic BRAF induces melanoma cell invasion by downregulating the cGMP specific phosphodiesterase PDE5A. Cancer Cell 19, 45–57 (2011). http://www.ncbi.nlm.nih.gov/pubmed/21215707

9. Isaiah J. Fidler. The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited. Nature Review Cancer. 2003 June. 3(6):453-8. http://www.ncbi.nlm.nih.gov/pubmed/12778135

10. Christoph A. Klein. Parallel progression of primary tumours and metastases.   Nat Rev Cancer. 2009 Apr;9(4):302-12  http://www.ncbi.nlm.nih.gov/pubmed/19308069 http://prometheus.fmrp.usp.br/biocelmolcancer/Klein.pdf

 

Other related articles published on this Open Access Scientific Journal, include the following:

I. By: Ritu Saxena PhD. In focus: Circulating Tumor Cells. http://pharmaceuticalintelligence.com/2013/06/24/in-focus-circulating-tumor-cells/

II. By: Ritu Saxena PhD. Scientists use natural agents for prostate cancer bone metastasis treatment. http://pharmaceuticalintelligence.com/2012/09/17/natural-agents-for-prostate-cancer-bone-metastasis-treatment/

III. By: Prabodh Kandala, PhD. All Cancer Cells Are Not Created Equal: Some Cell Types Control Continued Tumor Growth, Others Prepare the Way for Metastasis. http://pharmaceuticalintelligence.com/2012/05/17/all-cancer-cells-are-not-created-equal-some-cell-types-control-continued-tumor-growth-others-prepare-the-way-for-metastasis/

IV. By: Aviva Lev-Ari PhD RN. MIT Scientists Identified Gene that Controls Aggressiveness in Breast Cancer Cells. http://pharmaceuticalintelligence.com/2013/07/03/mit-scientists-identified-gene-that-controls-aggressiveness-in-breast-cancer-cells/

V. By: Demet Sag PhD CRA, GCP.  The Magic of the Pandora’s Box : Epigenetics and Stemness with Long non-coding RNAs (lincRNA). http://pharmaceuticalintelligence.com/2013/06/30/the-magic-of-the-pandoras-box-epigenetics-and-stemmness-with-long-non-coding-rnas-lincrna/

 

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Author/Curator: Ritu Saxena, PhD

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Word Cloud By Danielle Smolyar

For several decades, research efforts have focused on targeting progression of cancer cells in primary tumors. Primary tumor cell targeting strategies include standard chemotherapy and immunotherapy and modulation of host microenvironment including tumor vasculature. However, cancer progression is comprised of both primary tumor growth and secondary metastasis (Langley RR and Fidler IJ. Tumor cell-organ microenvironment interactions in the pathogenesis of cancer metastasis. Endocr Rev. 2007 May;28(3):297-321; http://www.ncbi.nlm.nih.gov/pubmed/17409287). Owing to the property of unilimited cell division, cells in primary tumor increase rapidly in number and density and are able to favorably influence their microenvironment. Metastasis, on the other hand, depends on the ability of cancer cells to disseminate, circulate, adapt to the harsh environment and seed in different organs to establish secondary tumors. Although tumor cells are shed into the circulation in large numbers since early stages of tumor formation, few tumor cells can survive and proceed to overt metastasis. (Husemann Y et al. Systemic spread is an early step in breast cancer. Cancer Cell. 2008 Jan;13(1):58-68; http://www.ncbi.nlm.nih.gov/pubmed/18167340). Tight vascular wall barriers, unfavorable conditions for survival in distant organs, and a rate-limiting acquisition of organ colonization functions are just some of the impediments to the formation of distant metastasis (Chiang AC and Massagué J. Molecular basis of metastasis. N Engl J Med. 2008 Dec 25;359(26):2814-23; http://www.ncbi.nlm.nih.gov/pubmed/19109576).

It has been hypothesized that metastasis is initiated by a subpopulation of circulating tumor cells (CTC) found in the blood of patients. Therefore, understanding the function of CTC and targeting the CTC is gaining attention as a possible therapeutic avenue in carcinoma treatment.

CTCs

Figure: Circulating tumor cells in the metastatic cascade

(Image source: Chaffer CL and Weinberg RA. Science 2011,331, pp. 1559-1564; http://www.ncbi.nlm.nih.gov/pubmed/21436443)

Isolation of CTC

Initial methods relied on the difference in physical properties of cells. When spun in a centrifuge, different cells in the blood sample settle in separate layers based on their byoyancy, and CTC are found in the white blood cell fraction. Because CTC are generally larger than white blood cells, a size-based filter could be used to separate the cell types (Vona G, et al, Isolation by size of epithelial tumor cells : a new method for the immunomorphological and molecular characterization of circulating tumor cells. Am J Pathol, 2000 Jan;156(1):57-63; http://www.ncbi.nlm.nih.gov/pubmed/10623654).

Herbert A Fritsche, PhD, Professor and Chief, Clinical Chemistry, Department of Laboratory Medicine, The University of Texas, MD Anderson Cancer Center, demonstrated that the CTC can be captured using antibody labeled magnetic beads, either in positive or negative selection schema. After the circulating tumor cells are isolated, they may be characterized by immunohistochemistry and counted.  Alternatively, these cells may be characterized by gene expression analysis using RT-PCR. One of the CTC detection methods, Veridex Inc, Cell Search Assay, has been cleared by the US FDA for use as a prognostic test in patients with metastatic cancers of the breast, prostate and colon. This technology relies on the expression of epithelial cellular adhesion molecular (EpCAM) by epithelial cells and the isolation of these cells by immunomagnetic capture using anti-EpCAM antibodies.  Enriched CTC are identified by immunofluorescence. Martin Fleisher, PhD, Chair, Department of Clinical Laboratories, Memorial Sloan-Kettering Cancer Center discussed in a webinar at the biomarker symposia, Cambridge Healthtech Institute, that every new technology has shortcomings, and the reliance on cancer cells to express sufficient EpCAM to enable capture may affect the role of this technology in future clinical use. Heterogeneous downregulation of epithelial surface antigen in invasive tumor cells has been reported. Thus, alternative methods to detect CTC are being developed. These new methods include-

  1. Flow cytometry that sorts cells by size and surface antigen expression.
  2. CTC microchips that are designed to capture CTC as whole blood flows past EpCAM-coated mirco-posts.
  3. Enrichment by filtration using filters with a pore size of 7-8 µm, that permits smaller red blood cell, leukocytes, and platelets to pass, but captures CTC that have diameters of about 12-15 µm.

Better identification of CTC

Baccelli et al (2013) developed a xenograft assay and demonstrated that the primary human luminal breast cancer CTC contain metastasis-initiated cells (MICs) that give rise to bone, lung and liver metastases in mice. These MIC-containing CTC populations expressed EPCAM, CD44, CD47 and MET. It was observed that in a small cohort of patients with metastases, the number of CTC expressing markers EPCAM,CD44, CD47 and MET, but not of bulk EPCAM+ CTC, correlated with lower overall survival and increased number of metastasic sites. These data describe functional circulating MICs and associated markers, which may aid the design of better tools to diagnose and treat metastatic breast cancer. The findings were published in the Nature Biotechnology journal recently (Baccelli I, et al. Identification of a population of blood circulating tumor cells from breast cancer patients that initiates metastasis in a xenograft assay. Nature Biotechnology 2013 31, 539–544; http://www.ncbi.nlm.nih.gov/pubmed/23609047).

CTC as prognostic and predictive factor for cancer progression

Martin Fleisher, PhD states “detecting CTC in peripheral blood of patients with cancer has become a clinically relevant and important prognostic biomarker and has been shown to be a predictive biomarker post-therapy. But, key to the use of CTC as a biomarker is the technology designed to enrich cancer cells from peripheral blood.”

Since CTC isolation methods started being established, correlation studies between the cells and a patient’s disease emerged. In 2004, investigators at the Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center (Houston, TX) discovered that the CTC were associated with disease progression and survival in metastatic breast cancer. The clinical trial recruited 177 patients with measurable metastatic breast cancer for levels of CTC both before the patients were to start a new line of treatment and at the first follow-up visit. The progression of the disease or the response to treatment was determined with the use of standard imaging studies at the participating centers. Patients in a training set with levels of CTC equal to or higher than 5 per 7.5 ml of whole blood, as compared with the group with fewer than 5 CTC per 7.5 ml, had a shorter median progression-free survival (2.7 months vs. 7.0 months, P<0.001) and shorter overall survival (10.1 months vs. >18 months, P<0.001). At the first follow-up visit after the initiation of therapy, this difference between the groups persisted (progression-free survival, 2.1 months vs. 7.0 months; P<0.001; overall survival, 8.2 months vs. >18 months; P<0.001), and the reduced proportion of patients (from 49 percent to 30 percent) in the group with an unfavorable prognosis suggested that there was a benefit from therapy.  Thus, the number of CTC was found to be an independent predictor of progression-free survival and overall survival in patients with metastatic breast cancer (Cristofanilli M, et al, Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004 Aug 19;351(8):781-91; http://www.ncbi.nlm.nih.gov/pubmed/15317891).

Similar results have been observed in other cancer types, including prostate and colorectal cancer. The Cell Search System developed by Veridex LLC (Huntingdon Valley, PA) enumerated CTC from 7.5 mL of venous blood and was used to compare the outcomes from three prospective multicenter studies investigating the use of CTC to monitor patients undergoing treatment for metastatic breast, colorectal, or prostate cancer. Evaluation of CTC at anytime during the course of disease allowed assessment of patient prognosis and is predictive of overall survival (Miller MC, et al. Significance of Circulating Tumor Cells Detected by the CellSearch System in Patients with Metastatic Breast Colorectal and Prostate Cancer. J Oncol. 2010; http://www.ncbi.nlm.nih.gov/pubmed/20016752). In addition, the CTC test may permit the oncologist to make an early decision to discontinue first line therapy for metastatic breast cancer and pursue more aggressive alternative treatments.

Genetic analysis of CTC

Additional studies have analyzed the genetic mutations that the cells carry, comparing the mutations to those in a primary tumor or correlating the findings to a patient’s disease severity or spread. In one study, lung cancer patients whose CTC carried a mutation known to cause drug resistance had faster disease progression than those whose CTC lacked the mutation. The investigators analyzed the evolutionary aspect of cancer progression and studied the precursor cells of metastases directly for the identification of prognostic and therapeutic markers. Single disseminated cancer cells isolated from lymph nodes and bone marrow of 107 consecutive esophageal cancer patients were analyzed by whole-genome screening which revealed that primary tumors and lymphatically and hematogenously disseminated cancer cells diverged for most genetic aberrations. Chromosome 17q12-21, the region comprising HER2, was identified as the most frequent gain in disseminated tumor cells that were isolated from both ectopic sites. Furthermore, survival analysis demonstrated that HER2 gain in a single disseminated tumor cell but not in primary tumors conferred high risk for early death (Stoecklein NH, et al. Direct genetic analysis of single disseminated cancer cells for prediction of outcome and therapy selection in esophageal cancer. Cancer Cell. 2008 May;13(5):441-53; http://www.ncbi.nlm.nih.gov/pubmed/18455127).

The abovementioned studies indicate that CTC blood tests have been successfully used to track the severity of a cancer or efficacy of a treatment. In conclusion, the evolution of the CTC technology will be critical in the emerging area of targeted therapy.  With the development and use of new technologies, the links between the genomic information and CTC could be explored and established for targeted therapy.

Challenges in CTC research

  1. Potential clinical significance of CTC has been demonstrated as early detection, diagnostic, prognostic, predictive, surrogate, stratification, and pharmacodynamic biomarkers. Hong B and Zu Y (2013) discuss that “the role of CTC as a disease marker may be unique in different clinical conditions and should be carefully interpreted. A good example is the comparison between the prognostic and predictive biomarkers. Both biomarkers employ progression-free survival and overall survival for data interpretation; however, the prognostic biomarker is independent of specific drug treatment or therapy, and used for the determination of outcomes before treatment, while the predictive biomarker is related to a particular treatment to predict the response. Furthermore, inconsistent results are increasingly reported among the various CTC assay methods, specifically pertaining to results for the CTC detection rate, patient positivity rate, and the correlation between the presence of CTC and survival rate (Hong B and Zu Y. Detecting circulating tumor cells: current challenges and new trends. Source. Theranostics. 2013 Apr 23;3(6):377-94; http://www.ncbi.nlm.nih.gov/pubmed/23781285).
  2. Heterogeneity in CTC along with several other technical factors contribute to discordance, including the changes in methodology, lack of reference standard, spectrum and selection bias, operator variability and bias, sample size, blurred clinical impact with known clinical/pathologic data, use of diverse capture antibodies from different sources, lack of awareness of the pre-analytical phase, oversimplification of the cytopathology process, use of dichotomous decision criteria, etc (Sturgeon C. Limitations of assay techniques for tumor markers. In: (ed.) Diamandis EP, Fritsche HA, Lilja H, Chan DW, Schwartz MK. Tumor markers: physiology, pathobiology, technology, and clinical applications. Washington, DC: AACC Press. 2002:65-82; Gion M and Daidone MG. Circulating biomarkers from tumour bulk to tumour machinery: promises and pitfalls. Eur J Cancer. 2004;40(17):2613-2622; http://www.ncbi.nlm.nih.gov/pubmed/15541962). Therefore, employing a standard protocol is essential in order to minimize a lot of inconsistencies and technical errors.
  3. CTC in a small amount of blood sample might not represent the actual CTC count in the whole blood. In fact, it has been reported that the Cell Search system might undercount the number of CTC. Nagrath et al (2007) have demonstrated that the average CTC number per mL of whole blood is approximately 79-155 in various cancers (Nagrath S, et al. Isolation of rare circulating tumous cells in cancer patients by microchip technology. Nature. 2007;450(7173):1235-1239; http://www.ncbi.nlm.nih.gov/pubmed/18097410). In addition, an investigative CellSearch Profile approach (for research use only) detected an approximately 30-fold higher number of the median CTC in the same paired blood samples (Flores LM, et al. Improving the yield of circulating tumour cells facilitates molecular characterisation and recognition of discordant HER2 amplification in breast cancer. Br J Cancer. 2010;102(10):1495-502; http://www.ncbi.nlm.nih.gov/pubmed/20461092). Such measurement discrepancies indicate that the actual CTC numbers in the blood of patients could be at least 30-100 fold higher than that currently reported by the only FDA-cleared CellSearch system.

Thus, although promising, the CTC technology faces several challenges both in detection and interpretation, which has resulted in its limited clinical acceptance and use. In order to prepare the CTC technology for future widespread clinical acceptance, a comprehensive guideline for all phases of CTC technology development was published by the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium. The guidelines describe methods for interactive comparisons of proprietary new technologies, clinical trial designs, a clinical validation qualification strategy, and an approach for effectively carrying out this work through a public-private partnership that includes test developers, drug developers, clinical trialists, the FDA and the National Cancer Institute (NCI) (Parkinson DR, et al. Considerations in the development of circulating tumor cell technology for clinical use. J Transl Med. 2012;10(1):138; http://www.ncbi.nlm.nih.gov/pubmed/22747748).

Reference:

  1. Langley RR and Fidler IJ. Tumor cell-organ microenvironment interactions in the pathogenesis of cancer metastasis. Endocr Rev. 2007 May;28(3):297-321; http://www.ncbi.nlm.nih.gov/pubmed/17409287
  2. Husemann Y et al. Systemic spread is an early step in breast cancer. Cancer Cell. 2008 Jan;13(1):58-68; http://www.ncbi.nlm.nih.gov/pubmed/18167340
  3. Chiang AC and Massagué J. Molecular basis of metastasis. N Engl J Med. 2008 Dec 25;359(26):2814-23; http://www.ncbi.nlm.nih.gov/pubmed/19109576
  4. Vona G, et al, Isolation by size of epithelial tumor cells : a new method for the immunomorphological and molecular characterization of circulating tumor cells. Am J Pathol, 2000 Jan;156(1):57-63; http://www.ncbi.nlm.nih.gov/pubmed/10623654
  5. Baccelli I, et al. Identification of a population of blood circulating tumor cells from breast cancer patients that initiates metastasis in a xenograft assay. Nature Biotechnology 2013 31, 539–544; http://www.ncbi.nlm.nih.gov/pubmed/23609047
  6. Cristofanilli M, et al, Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004 Aug 19;351(8):781-91; http://www.ncbi.nlm.nih.gov/pubmed/15317891
  7. Miller MC, et al. Significance of Circulating Tumor Cells Detected by the CellSearch System in Patients with Metastatic Breast Colorectal and Prostate Cancer. J Oncol. 2010; http://www.ncbi.nlm.nih.gov/pubmed/20016752
  8. Stoecklein NH, et al. Direct genetic analysis of single disseminated cancer cells for prediction of outcome and therapy selection in esophageal cancer. Cancer Cell. 2008 May;13(5):441-53; http://www.ncbi.nlm.nih.gov/pubmed/18455127
  9. Hong B and Zu Y. Detecting circulating tumor cells: current challenges and new trends. Source. Theranostics. 2013 Apr 23;3(6):377-94; http://www.ncbi.nlm.nih.gov/pubmed/23781285
  10. 10. Sturgeon C. Limitations of assay techniques for tumor markers. In: (ed.) Diamandis EP, Fritsche HA, Lilja H, Chan DW, Schwartz MK. Tumor markers: physiology, pathobiology, technology, and clinical applications. Washington, DC: AACC Press. 2002:65-82
  11. Gion M and Daidone MG. Circulating biomarkers from tumour bulk to tumour machinery: promises and pitfalls. Eur J Cancer. 2004;40(17):2613-2622; http://www.ncbi.nlm.nih.gov/pubmed/15541962
  12. Nagrath S, et al. Isolation of rare circulating tumous cells in cancer patients by microchip technology. Nature. 2007;450(7173):1235-1239; http://www.ncbi.nlm.nih.gov/pubmed/18097410
  13. Flores LM, et al. Improving the yield of circulating tumour cells facilitates molecular characterisation and recognition of discordant HER2 amplification in breast cancer. Br J Cancer. 2010;102(10):1495-502; http://www.ncbi.nlm.nih.gov/pubmed/20461092
  14. Chaffer CL and Weinberg RA. Science 2011,331, pp. 1559-1564; http://www.ncbi.nlm.nih.gov/pubmed/21436443

Other related articles on circulation cells as biomarkers published on this Open Access Scientific Journal, include the following:

Blood-vessels-generating stem cells discovered

Ritu Saxena, PhD

http://pharmaceuticalintelligence.com/2012/10/22/blood-vessel-generating-stem-cells-discovered/

Cardiovascular and circulating endothelial cells as BIOMARKERS for prediction of Disease progression risks

Statins’ Nonlipid Effects on Vascular Endothelium through eNOS Activation Curator, Author,Writer, Reporter: Larry Bernstein, MD, FCAP

Cardiovascular Outcomes: Function of circulating Endothelial Progenitor Cells (cEPCs): Exploring Pharmaco-therapy targeted at Endogenous Augmentation of cEPCs Author and Curator: Aviva Lev-Ari, PhD, RN

Vascular Medicine and Biology: Macrovascular Disease – Therapeutic Potential of cEPCs Curator and Author: Aviva Lev-Ari, PhD, RN

Repair damaged blood vessels in heart disease, stroke, diabetes and trauma: Cellular Reprogramming amniotic fluid-derived cells into Endothelial Cells

Reporter: Aviva Lev-Ari, PhD, RN

Stem cells in therapy

A possible light by Stem cell therapy in painful dark of Osteoarthritis” – Kartogenin, a small molecule, differentiates stem cells to chondrocyte, healthy cartilage cells Author and Reporter: Anamika Sarkar, Ph.D and Ritu Saxena, Ph.D.

Human embryonic pluripotent stem cells and healing post-myocardial infarctionAuthor: Larry H. Bernstein, MD

Stem cells create new heart cells in baby mice, but not in adults, study showsReporter: Aviva Lev-Ari, PhD, RN

Stem cells for the rescue of mitochondrial dysfunction in Parkinson’s diseaseReporter: Ritu Saxena, Ph.D.

Stem Cell Research — The Frontier is at the Technion in Israel Reporter: Aviva Lev-Ari, PhD, RN

Research articles by MA Gaballa, PhD

Harris DT, Badowski M, Nafees A, Gaballa MAThe potential of Cord Blood Stem Cells for Use in Regenerative Medicine. Expert Opinion in Biological Therapy 2007. Sept 7(9): 1131-22.

Furfaro E, Gaballa MADo adult stem cells ameliorate the damaged myocardium?. Human cord blood as a potential source of stem cells. Current Vascular Pharmacology 2007, 5; 27-44.

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Treatment for Endocrine Tumors and Side Effects

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

Surgery

The purpose of surgery is typically to remove the entire tumor, along with some of the healthy tissue around it, called the margin. If the tumor cannot be removed entirely, “debulking” surgery may be performed. Debulking surgery is a procedure in which the goal is to remove as much of the tumor as possible. Side effects of surgery include weakness, fatigue, and pain for the first few days following the procedure.

Chemotherapy

Chemotherapy is the use of drugs to kill tumor cells, usually by stopping the cells’ ability to grow and divide. Systemic chemotherapy is delivered through the bloodstream to reach tumor cells throughout the body. A chemotherapy regimen (schedule) usually consists of a specific number of cycles given over a set period of time. A patient may receive one drug at a time or combinations of different drugs at the same time. The side effects of chemotherapy depend on the individual and the dose used, but they can include fatigue, risk of infection, nausea and vomiting, loss of appetite, and diarrhea. These side effects usually go away once treatment is finished.

Radiation therapy

Radiation therapy is the use of high-energy x-rays or other particles to kill tumor cells. The most common type of radiation treatment is called external-beam radiation therapy, which is radiation given from a machine outside the body. When radiation treatment is given using implants, it is called internal radiation therapy or brachytherapy. A radiation therapy regimen usually consists of a specific number of treatments given over a set period of time. Side effects from radiation therapy may include fatigue, mild skin reactions, upset stomach, and loose bowel movements. Most side effects go away soon after treatment is finished.

Hormone therapy

The goal of hormone therapy is often to lower the levels of hormones in the body. Hormone therapy may be given to help stop the tumor from growing or to relieve symptoms caused by the tumor. In addition, for thyroid cancer, hormone therapy will be given if the thyroid gland has been removed, to replace the hormone that is needed by the body to function properly.

Immunotherapy

Immunotherapy (also called biologic therapy) is designed to boost the body’s natural defenses to fight the tumor. It uses materials made either by the body or in a laboratory to bolster, target, or restore immune system function. Examples of immunotherapy include cancer vaccines, monoclonal antibodies, and interferons. Alpha interferon is a form of biologic therapy given as an injection under the skin. This is sometimes used to help relieve symptoms caused by the tumor, but it can have severe side effects including fatigue, depression, and flu-like symptoms.

Targeted therapy

Targeted therapy is a treatment that targets the tumor’s specific genes, proteins, or the tissue environment that contributes to cancer growth and survival. This type of treatment blocks the growth and spread of tumor cells while limiting damage to normal cells, usually leading to fewer side effects than other cancer medications.

Recent studies show that not all tumors have the same targets. To find the most effective treatment, the doctor may run tests to identify the genes, proteins, and other factors in the tumor. As a result, doctors can better match each patient with the most effective treatment whenever possible.

Depending on the type of endocrine tumor, targeted therapy may be a possible treatment option. For instance, targeted therapies, such as sunitinib (Sutent) and everolimus (Afinitor), have been approved for treating advanced islet cell tumors. Early results of clinical trials (research studies) with targeted therapy drugs for other types of endocrine tumors are promising, but more research is needed to prove they are effective.

Recurrent endocrine tumor

Once the treatment is complete and there is a remission (absence of symptoms; also called “no evidence of disease” or NED). Many survivors feel worried or anxious that the tumor will come back. If the tumor does return after the original treatment, it is called a recurrent tumor. It may come back in the same place (called a local recurrence), nearby (regional recurrence), or in another place (distant recurrence). When this occurs, a cycle of testing will begin again to learn as much as possible about the recurrence. Often the treatment plan will include the therapies described above (such as surgery, chemotherapy, and radiation therapy) but may be used in a different combination or given at a different pace. People with a recurrent tumor often experience emotions such as disbelief or fear. Patients are encouraged to talk with their health care team about these feelings and ask about support services to help them cope.

Metastatic endocrine tumor

If a cancerous tumor has spread to another location in the body, it is called metastatic cancer. A treatment plan that includes a combination of surgery, chemotherapy, radiation therapy, hormone therapy, immunotherapy, or targeted therapy may be recommended if required.

In addition to treatment to slow, stop, or eliminate the cancer (also called disease-directed treatment), an important part of cancer care is relieving a person’s symptoms and side effects. It includes supporting the patient with his or her physical, emotional, and social needs, an approach called palliative or supportive care. People often receive disease-directed therapy and treatment to ease symptoms at the same time.

Source References:

http://www.cancer.net/cancer-types/endocrine-tumor/treatment

 

http://www.macmillan.org.uk/Cancerinformation/Cancertypes/Endocrine/Endocrinetumours.aspx

 

http://cancer.osu.edu/patientsandvisitors/cancerinfo/cancertypes/endocrine/Pages/index.aspx

 

http://cancer.northwestern.edu/cancertypes/cancer_type.cfm?category=8

 

http://www.cancervic.org.au/about-cancer/cancer_types/endocrine_cancer

 

http://www.oncolink.org/types/types1.cfm?c=4

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