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Archive for the ‘CANCER BIOLOGY & Innovations in Cancer Therapy’ Category

Immunoediting can be a constant defense in the cancer landscape


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

 

There are many considerations in the cancer immunoediting landscape of defense and regulation in the cancer hallmark biology. The cancer hallmark biology in concert with key controls of the HLA compatibility affinity mechanisms are pivotal in architecting a unique patient-centric therapeutic application. Selection of random immune products including neoantigens, antigens, antibodies and other vital immune elements creates a high level of uncertainty and risk of undesirable immune reactions. Immunoediting is a constant process. The human innate and adaptive forces can either trigger favorable or unfavorable immunoediting features. Cancer is a multi-disease entity. There are multi-factorial initiators in a certain disease process. Namely, environmental exposures, viral and / or microbiome exposure disequilibrium, direct harm to DNA, poor immune adaptability, inherent risk and an individual’s own vibration rhythm in life.

 

When a human single cell is crippled (Deranged DNA) with mixed up molecular behavior that is the initiator of the problem. A once normal cell now transitioned into full threatening molecular time bomb. In the modeling and creation of a tumor it all begins with the singular molecular crisis and crippling of a normal human cell. At this point it is either chop suey (mixed bit responses) or a productive defensive and regulation response and posture of the immune system. Mixed bits of normal DNA, cancer-laden DNA, circulating tumor DNA, circulating normal cells, circulating tumor cells, circulating immune defense cells, circulating immune inflammatory cells forming a moiety of normal and a moiety of mess. The challenge is to scavenge the mess and amplify the normal.

 

Immunoediting is a primary push-button feature that is definitely required to be hit when it comes to initiating immune defenses against cancer and an adaptation in favor of regression. As mentioned before that the tumor microenvironment is a “mixed bit” moiety, which includes elements of the immune system that can defend against circulating cancer cells and tumor growth. Personalized (Precision-Based) cancer vaccines must become the primary form of treatment in this case. Current treatment regimens in conventional therapy destroy immune defenses and regulation and create more serious complications observed in tumor progression, metastasis and survival. Commonly resistance to chemotherapeutic agents is observed. These personalized treatments will be developed in concert with cancer hallmark analytics and immunocentrics affinity and selection mapping. This mapping will demonstrate molecular pathway interface and HLA compatibility and adaptation with patientcentricity.

References:

 

https://www.linkedin.com/pulse/immunoediting-cancer-landscape-john-catanzaro/

 

https://www.cell.com/cell/fulltext/S0092-8674(16)31609-9

 

https://www.researchgate.net/publication/309432057_Circulating_tumor_cell_clusters_What_we_know_and_what_we_expect_Review

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840207/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

 

https://www.frontiersin.org/articles/10.3389/fimmu.2018.00414/full

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388310/

 

https://www.linkedin.com/pulse/cancer-hallmark-analytics-omics-data-pathway-studio-review-catanzaro/

 

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Immunotherapy may help in glioblastoma survival


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

 

Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. But, in a glimmer of hope, a recent study found that a drug designed to unleash the immune system helped some patients live longer. Glioblastoma powerfully suppresses the immune system, both at the site of the cancer and throughout the body, which has made it difficult to find effective treatments. Such tumors are complex and differ widely in their behavior and characteristics.

 

A small randomized, multi-institution clinical trial was conducted and led by researchers at the University of California at Los Angeles involved patients who had a recurrence of glioblastoma, the most common central nervous system cancer. The aim was to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab (checkpoint inhibitor) in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone.

 

Neoadjuvant PD-1 blockade was associated with upregulation of T cell– and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhanced both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor.

 

Immunotherapy has not proved to be effective against glioblastoma. This small clinical trial explored the effect of PD-1 blockade on recurrent glioblastoma in relation to the timing of administration. A total of 35 patients undergoing resection of recurrent disease were randomized to either neoadjuvant or adjuvant pembrolizumab, and surgical specimens were compared between the two groups. Interestingly, the tumoral gene expression signature varied between the two groups, such that those who received neoadjuvant pembrolizumab displayed an INF-γ gene signature suggestive of T-cell activation as well as suppression of cell-cycle signaling, possibly consistent with growth arrest. Although the study was not powered for efficacy, the group found an increase in overall survival in patients receiving neoadjuvant pembrolizumab compared with adjuvant pembrolizumab of 13.7 months versus 7.5 months, respectively.

 

In this small pilot study, neoadjuvant PD-1 blockade followed by surgical resection was associated with intratumoral T-cell activation and inhibition of tumor growth as well as longer survival. How the drug works in glioblastoma has not been totally established. The researchers speculated that giving the drug before surgery prompted T-cells within the tumor, which had been impaired, to attack the cancer and extend lives. The drug didn’t spur such anti-cancer activity after the surgery because those T-cells were removed along with the tumor. The results are very important and very promising but would need to be validated in much larger trials.

 

References:

 

https://www.washingtonpost.com/health/2019/02/11/immunotherapy-may-help-patients-with-kind-cancer-that-killed-john-mccain/?noredirect=on&utm_term=.e1b2e6fffccc

 

https://www.ncbi.nlm.nih.gov/pubmed/30742122

 

https://www.practiceupdate.com/content/neoadjuvant-anti-pd-1-immunotherapy-promotes-immune-responses-in-recurrent-gbm/79742/37/12/1

 

https://www.esmo.org/Oncology-News/Neoadjuvant-PD-1-Blockade-in-Glioblastoma

 

https://neurosciencenews.com/immunotherapy-glioblastoma-cancer-10722/

 

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Lesson 5 Cell Signaling And Motility: Cytoskeleton & Actin: Curations and Articles of reference as supplemental information: #TUBiol3373

Curator: Stephen J. Williams, Ph.D.

Cell motility or migration is an essential cellular process for a variety of biological events. In embryonic development, cells migrate to appropriate locations for the morphogenesis of tissues and organs. Cells need to migrate to heal the wound in repairing damaged tissue. Vascular endothelial cells (ECs) migrate to form new capillaries during angiogenesis. White blood cells migrate to the sites of inflammation to kill bacteria. Cancer cell metastasis involves their migration through the blood vessel wall to invade surrounding tissues.

Please Click on the Following Powerpoint Presentation for Lesson 4 on the Cytoskeleton, Actin, and Filaments

CLICK ON LINK BELOW

cell signaling 5 lesson

This post will be updated with further information when we get into Lesson 6 and complete our discussion on the Cytoskeleton

Please see the following articles on Actin and the Cytoskeleton in Cellular Signaling

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

This article, constitutes a broad, but not complete review of the emerging discoveries of the critical role of calcium signaling on cell motility and, by extension, embryonic development, cancer metastasis, changes in vascular compliance at the junction between the endothelium and the underlying interstitial layer.  The effect of calcium signaling on the heart in arrhtmogenesis and heart failure will be a third in this series, while the binding of calcium to troponin C in the synchronous contraction of the myocardium had been discussed by Dr. Lev-Ari in Part I.

Universal MOTIFs essential to skeletal muscle, smooth muscle, cardiac syncytial muscle, endothelium, neovascularization, atherosclerosis and hypertension, cell division, embryogenesis, and cancer metastasis. The discussion will be presented in several parts:
1.  Biochemical and signaling cascades in cell motility
2.  Extracellular matrix and cell-ECM adhesions
3.  Actin dynamics in cell-cell adhesion
4.  Effect of intracellular Ca++ action on cell motility
5.  Regulation of the cytoskeleton
6.  Role of thymosin in actin-sequestration
7.  T-lymphocyte signaling and the actin cytoskeleton

 

Identification of Biomarkers that are Related to the Actin Cytoskeleton

In this article the Dr. Larry Bernstein covers two types of biomarker on the function of actin in cytoskeleton mobility in situ.

  • First, is an application in developing the actin or other component, for a biotarget and then, to be able to follow it as

(a) a biomarker either for diagnosis, or

(b) for the potential treatment prediction of disease free survival.

  • Second, is mostly in the context of MI, for which there is an abundance of work to reference, and a substantial body of knowledge about

(a) treatment and long term effects of diet, exercise, and

(b) underlying effects of therapeutic drugs.

Microtubule-Associated Protein Assembled on Polymerized Microtubules

(This article has a great 3D visualization of a microtuble structure as well as description of genetic diseases which result from mutations in tubulin and effects on intracellular trafficking of proteins.

A latticework of tiny tubes called microtubules gives your cells their shape and also acts like a railroad track that essential proteins travel on. But if there is a glitch in the connection between train and track, diseases can occur. In the November 24, 2015 issue of PNAS, Tatyana Polenova, Ph.D., Professor of Chemistry and Biochemistry, and her team at the University of Delaware (UD), together with John C. Williams, Ph.D., Associate Professor at the Beckman Research Institute of City of Hope in Duarte, California, reveal for the first time — atom by atom — the structure of a protein bound to a microtubule. The protein of focus, CAP-Gly, short for “cytoskeleton-associated protein-glycine-rich domains,” is a component of dynactin, which binds with the motor protein dynein to move cargoes of essential proteins along the microtubule tracks. Mutations in CAP-Gly have been linked to such neurological diseases and disorders as Perry syndrome and distal spinal bulbar muscular dystrophy.

 

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2019 Koch Institute Symposium – Machine Learning and Cancer, June 14, 2019, 8:00 AM-5:00 PM ET MIT Kresge Auditorium, 48 Massachusetts Ave, Cambridge, MA

Announcement

Aviva Lev-Ari, PhD, RN,

Founder and Director of LPBI Group will be in attendance covering the event in REAL TIME

@pharma_BI

@AVIVA1950

 

Machine Learning and Cancer

The 18th Annual Koch Institute Summer Symposium on June 14, 2019 at MIT’s Kresge Auditorium will focus on Machine Learning and Cancer.

Both fields are undergoing dramatic changes, and their integration holds great promise for cancer research, diagnostics, and therapeutics. Cancer treatment and research have advanced rapidly with an increasing reliance on data-driven decisions. The volume, complexity, and diversity of research and clinical data—from genomics and single-cell molecular and image-based profiles to histopathology, clinical imaging, and medical records—far surpasses the capacity of individual scientists and physicians. However, they offer a remarkable opportunity to new approaches for data science and machine learning to provide holistic and intelligible interpretations to trained experts and patients alike. These advances will make it possible to provide far better diagnostics, discover possible chemical pathways for de novo synthesis of therapeutic compounds, predict accurately the risk of individuals for development of specific cancers years before metastatic spread, and determine the combination of agents that will stimulate immune rejection of a tumor or selectively induce the death of all cells in a tumor.

The symposium will address these issues through three sessions:

  • Machine Learning in Cancer Research: the Need and the Opportunity
  • Machine Learning to Decipher Cellular and Molecular Mechanisms in Cancer
  • Machine Learning into the Clinic

Sessions will be followed by a panel discussion of broadly informed experts moderated by MIT President Emerita Susan Hockfield.

Introductory remarks will be given by symposium co-chairs and Koch Institute faculty members Regina Barzilay, Aviv Regev and Phillip Sharp.

 

Keynote Speakers | Machine Learning in Cancer Research: the Need and the Opportunity

James P. Allison, PhD

MD Anderson Cancer Center

Regina Barzilay, PhD

MIT Computer Science and Artificial Intelligence Lab, Koch Institute for Integrative Cancer Research at MIT

Aviv Regev, PhD

Broad Institute, Koch Institute for Integrative Cancer Research at MIT

 

Session Speakers

Michael R. Angelo, MD, PhD

Stanford Unviersity

Andrew Beck

PathAI

Stephen H. Friend, MD, PhD

Sage Bionetworks

Tommi Jaakkola, PhD

MIT Computer Science and Artificial Intelligence Lab

Dana Pe’er, PhD

Memorial Sloan Kettering Cancer Center

Peter Sorger, PhD

Harvard Medical School

Olga Troyanskaya, PhD

Princeton University

Brian Wolpin, MD

Dana-Farber Cancer Institute

 

Panel Discussion | Big Data, Computation and the Future of Health Care

James (Jay) Bradner, MD

Novartis

Clifford A. Hudis, MD

American Society of Clinical Oncology

Constance D. Lehman, MD, PhD

Massachusetts General Hospital

Norman (Ned) Sharpless, MD

National Cancer Institute

 

Moderator: Susan Hockfield, PhD

Koch Institute for Integrative Cancer Research at MIT

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SOURCE

From: 2019 Koch Institute Symposium <ki-events@mit.edu>

Reply-To: <ki-events@mit.edu>

Date: Tuesday, March 12, 2019 at 11:30 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: Invitation to the 2019 Koch Institute Symposium – Machine Learning and Cancer

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THE 3RD STAT4ONC ANNUAL SYMPOSIUM

APRIL 25-27, 2019

HILTON, HARTFORD, CONNECTICUT
315 Trumbull St, Hartford, CT 06103
Reporter: Stephen J. Williams, Ph.D.

SYMPOSIUM OBJECTIVES

The three-day symposium aims to bring oncologists and statisticians together to share new research, discuss novel ideas, ask questions and provide solutions for cancer clinical trials. In the era of big data, precision medicine, and genomics and immune-based oncology, it is crucial to provide a platform for interdisciplinary dialogues among clinical and quantitative scientists. The Stat4Onc Annual Symposium serves as a venue for oncologists and statisticians to communicate their views on trial design and conduct, drug development, and translations to patient care. To be discussed includes big data and genomics for oncology clinical trials, novel dose-finding designs, drug combinations, immune oncology clinical trials, and umbrella/basket oncology trials. An important aspect of Stat4Onc is the participation of researchers across academia, industry, and regulatory agency.

Meeting Agenda will be announced coming soon. For Updated Agenda and Program Speakers please CLICK HERE

The registration of the symposium is via NESS Society PayPal. Click here to register.

Other  2019 Conference Announcement Posts on this Open Access Journal Include:

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Lesson 4 Cell Signaling And Motility: G Proteins, Signal Transduction: Curations and Articles of reference as supplemental information: #TUBiol3373

Curator: Stephen J. Williams, Ph.D.

Below please find the link to the Powerpoint presentation for lesson #4 for #TUBiol3373.  The lesson first competes the discussion on G Protein Coupled Receptors, including how cells terminate cell signals.  Included are mechanisms of receptor desensitization.  Please NOTE that desensitization mechanisms like B arrestin decoupling of G proteins and receptor endocytosis occur after REPEATED and HIGH exposures to agonist.  Hydrolysis of GTP of the alpha subunit of G proteins, removal of agonist, and the action of phosphodiesterase on the second messenger (cAMP or cGMP) is what results in the downslope of the effect curve, the termination of the signal after agonist-receptor interaction.

 

Click below for PowerPoint of lesson 4

Powerpoint for lesson 4

 

Please Click below for the papers for your Group presentations

paper 1: Membrane interactions of G proteins and other related proteins

paper 2: Macaluso_et_al-2002-Journal_of_Cellular_Physiology

paper 3: Interactions of Ras proteins with the plasma membrane

paper 4: Futosi_et_al-2016-Immunological_Reviews

 

Please find related article on G proteins and Receptor Tyrosine Kinases on this Open Access Online Journal

G Protein–Coupled Receptor and S-Nitrosylation in Cardiac Ischemia and Acute Coronary Syndrome

Action of Hormones on the Circulation

Newer Treatments for Depression: Monoamine, Neurotrophic Factor & Pharmacokinetic Hypotheses

VEGF activation and signaling, lysine methylation, and activation of receptor tyrosine kinase

 

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Tumor Ammonia Recycling: How Cancer Cells Use Glutamate Dehydrogenase to Recycle Tumor Microenvironment Waste Products for Biosynthesis

Reporter: Stephen J. Williams, PhD

A feature of the tumorigenic process is the rewiring of the metabolic processes that provides a tumor cell the ability to grow and thrive in conditions of limiting nutrients as well as the ability to utilize waste products in salvage pathways for production of new biomass (amino acids, nucleic acids etc.) required for cellular growth and division 1-8.  A Science article from Spinelli et al. 9 (and corresponding Perspective article in the same issue by Dr. Chi V. Dang entitled Feeding Frenzy for Cancer Cells 10) describes the mechanism by which estrogen-receptor positive (ER+) breast cancer cells convert glutamine to glutamate, release ammonia  into the tumor microenvironment, diffuses into tumor cells and eventually recycle this ammonia by reductive amination of a-ketoglutarate by glutamate dehydrogenase (GDH) to produce glutamic acid and subsequent other amino acids needed for biomass production.   Ammonia can accumulate in the tumor microenvironment in poorly vascularized tumor. Thus ammonia becomes an important nitrogen source for tumor cells.

Mammalian cells have a variety of mechanisms to metabolize ammonia including

  • Glutamate synthetase (GS) in the liver can incorporate ammonia into glutamate to form glutamine
  • glutamate dehydrogenase (GDH) converts glutamate to a-ketoglutarate and ammonia under allosteric regulation (discussed in a post on this site by Dr. Larry H. Berstein; subsection Drugging Glutaminolysis)
  • the reverse reaction of GDH, which was found to occur in ER+ breast cancer cells, a reductive amination of a-ketoglutarate to glutamate11, is similar to the reductive carboxylation of a-ketoglutarate to citrate by isocitrate dehydrogenase (IDH) for fatty acid synthesis (IDH is overexpressed in many tumor types including cancer stem cells 12-15), and involved in immune response and has been developed as a therapeutic target for various cancers. IDH mutations were shown to possess the neomorphic activity to generate the oncometabolite, 2-hydroxyglutarate (2HG) 16-18. With a single codon substitution, the kinetic properties of the mutant IDH isozyme are significantly altered, resulting in an obligatory sequential ordered reaction in the reverse direction 19.

 

In the Science paper, Spinelli et al. report that ER+ breast cancer cells have the ability to utilize ammonia sources from their surroundings in order to produce amino acids and biomass as these ER+ breast cancer cells have elevated levels of GS and GDH with respect to other breast cancer histotypes.

GDH was elevated in ER+ luminal cancer cells and the quiescent epithelial cells in organoid culture

However proliferative cells were dependent on transaminases, which transfers nitrogen from glutamate to pyruvate or oxaloacetate to form a-ketoglutarate and alanine or aspartate. a-ketoglutarate is further metabolized in the citric acid cycle.

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 1.    Reductive amination and transamination reactions of glutamic acid.  Source http://www.biologydiscussion.com/organism/metabolism-organism/incorporation-of-ammonia-into-organic-compounds/50870

Spinelli et al. showed GDH is necessary for ammonia reductive incorporation into a-ketoglutarate and also required for ER+ breast cancer cell growth in immunocompromised mice.

In addition, as commented by Dr. Dang in his associated Perspectives article, (quotes indent)

The metabolic tumor microenvironment produced by resident cells, such as fibroblasts and macrophages, can create an immunosuppressive environment 20.  Hence, it will be of great interest to further understand whether products such as ammonia could affect tumor immunity or induce autophagy  (end quote indent)

 

 

 

Figure 2.  Tumor ammonia recycling.  Source:  From Chi V. Dang Feeding Frenzy for cancer cells.  Rights from RightsLink (copyright.com)

Metabolic recycling of ammonia via glutamate dehydrogenase supports breast cancer biomass

Jessica B. Spinelli1,2, Haejin Yoon1, Alison E. Ringel1, Sarah Jeanfavre2, Clary B. Clish2, Marcia C. Haigis1 *

1.      1Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA. 2.      2Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

* *Corresponding author. Email: marcia_haigis@hms.harvard.edu

Science  17 Nov 2017:Vol. 358, Issue 6365, pp. 941-946 DOI: 10.1126/science.aam9305

Abstract

Ammonia is a ubiquitous by-product of cellular metabolism; however, the biological consequences of ammonia production are not fully understood, especially in cancer. We found that ammonia is not merely a toxic waste product but is recycled into central amino acid metabolism to maximize nitrogen utilization. In our experiments, human breast cancer cells primarily assimilated ammonia through reductive amination catalyzed by glutamate dehydrogenase (GDH); secondary reactions enabled other amino acids, such as proline and aspartate, to directly acquire this nitrogen. Metabolic recycling of ammonia accelerated proliferation of breast cancer. In mice, ammonia accumulated in the tumor microenvironment and was used directly to generate amino acids through GDH activity. These data show that ammonia is not only a secreted waste product but also a fundamental nitrogen source that can support tumor biomass.

 

 

References

1          Strickaert, A. et al. Cancer heterogeneity is not compatible with one unique cancer cell metabolic map. Oncogene 36, 2637-2642, doi:10.1038/onc.2016.411 (2017).

2          Hui, S. et al. Glucose feeds the TCA cycle via circulating lactate. Nature 551, 115-118, doi:10.1038/nature24057 (2017).

3          Mashimo, T. et al. Acetate is a bioenergetic substrate for human glioblastoma and brain metastases. Cell 159, 1603-1614, doi:10.1016/j.cell.2014.11.025 (2014).

4          Sousa, C. M. et al. Erratum: Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature 540, 150, doi:10.1038/nature19851 (2016).

5          Sousa, C. M. et al. Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature 536, 479-483, doi:10.1038/nature19084 (2016).

6          Commisso, C. et al. Macropinocytosis of protein is an amino acid supply route in Ras-transformed cells. Nature 497, 633-637, doi:10.1038/nature12138 (2013).

7          Hanahan, D. & Weinberg, R. A. The hallmarks of cancer. Cell 100, 57-70 (2000).

8          Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646-674, doi:10.1016/j.cell.2011.02.013 (2011).

9          Spinelli, J. B. et al. Metabolic recycling of ammonia via glutamate dehydrogenase supports breast cancer biomass. Science 358, 941-946, doi:10.1126/science.aam9305 (2017).

10        Dang, C. V. Feeding frenzy for cancer cells. Science 358, 862-863, doi:10.1126/science.aaq1070 (2017).

11        Smith, T. J. & Stanley, C. A. Untangling the glutamate dehydrogenase allosteric nightmare. Trends in biochemical sciences 33, 557-564, doi:10.1016/j.tibs.2008.07.007 (2008).

12        Metallo, C. M. et al. Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia. Nature 481, 380-384, doi:10.1038/nature10602 (2011).

13        Garrett, M. et al. Metabolic characterization of isocitrate dehydrogenase (IDH) mutant and IDH wildtype gliomaspheres uncovers cell type-specific vulnerabilities. Cancer & metabolism 6, 4, doi:10.1186/s40170-018-0177-4 (2018).

14        Calvert, A. E. et al. Cancer-Associated IDH1 Promotes Growth and Resistance to Targeted Therapies in the Absence of Mutation. Cell reports 19, 1858-1873, doi:10.1016/j.celrep.2017.05.014 (2017).

15        Sciacovelli, M. & Frezza, C. Metabolic reprogramming and epithelial-to-mesenchymal transition in cancer. The FEBS journal 284, 3132-3144, doi:10.1111/febs.14090 (2017).

16        Dang, L. et al. Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature 462, 739-744, doi:10.1038/nature08617 (2009).

17        Gross, S. et al. Cancer-associated metabolite 2-hydroxyglutarate accumulates in acute myelogenous leukemia with isocitrate dehydrogenase 1 and 2 mutations. The Journal of experimental medicine 207, 339-344, doi:10.1084/jem.20092506 (2010).

18        Ward, P. S. et al. The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate. Cancer cell 17, 225-234, doi:10.1016/j.ccr.2010.01.020 (2010).

19        Rendina, A. R. et al. Mutant IDH1 enhances the production of 2-hydroxyglutarate due to its kinetic mechanism. Biochemistry 52, 4563-4577, doi:10.1021/bi400514k (2013).

20        Zhang, X. et al. IDH mutant gliomas escape natural killer cell immune surveillance by downregulation of NKG2D ligand expression. Neuro-oncology 18, 1402-1412, doi:10.1093/neuonc/now061 (2016).

 

Other articles on this Open Access Journal on Cancer Metabolism Include:

 

Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

 

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

 

 

Protein-binding, Protein-Protein interactions & Therapeutic Implications [7.3]

Is the Warburg effect an effect of deregulated space occupancy of methylome?

Therapeutic Implications for Targeted Therapy from the Resurgence of Warburg ‘Hypothesis’

New Insights on the Warburg Effect [2.2]

The Inaugural Judith Ann Lippard Memorial Lecture in Cancer Research: PI 3 Kinase & Cancer Metabolism

Renal (Kidney) Cancer: Connections in Metabolism at Krebs cycle and Histone Modulation

Warburg Effect and Mitochondrial Regulation- 2.1.3

Refined Warburg Hypothesis -2.1.2

 

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