Oncometabolism

Last updated

Oncometabolism is the field of study that focuses on the metabolic changes that occur in cells that make up the tumor microenvironment (TME) and accompany oncogenesis and tumor progression toward a neoplastic state. [1]

Contents

Cells with increased growth and survivability differ from non-tumorigenic cells in terms of metabolism. [2] The Warburg Effect, which describes how cancer cells change their metabolism to become more oncogenic in order to proliferate and eventually invade other tissues in a process known as metastasis. [1]

The chemical reactions associated with oncometabolism are triggered by the alteration of oncogenes, which are genes that have the potential to cause cancer. [3] These genes can be functional and active during physiological conditions, producing normal amounts of metabolites. Their upregulation as a result of DNA damage can result in an overabundance of these metabolites, and lead to tumorigenesis. These metabolites are known as oncometabolites, and can act as biomarkers. [4]

Otto Heinrich Warburg, considered the "Father of Oncometabolism" for his early discoveries in the field Otto Warburg.jpg
Otto Heinrich Warburg, considered the "Father of Oncometabolism" for his early discoveries in the field

History

In the 1920s, Otto Heinrich Warburg discovered an intriguing bioenergetic phenotype shared by most tumor cells: a higher-than-normal reliance on lactic acid fermentation for energy generation. He is known as the "Father of Oncometabolism". [1] [2] Although the roots of this research field trace back to the 1920s, it was only recently recognized [1] Over the last decade, research on cancer progression has focused on the role of shifting metabolic pathways for both the cancer and immune cells, leading to an increase interest in characterizing the metabolic alterations that cells undergo in the TME. [5]

Warburg Effect

In the absence of hypoxic conditions (i.e. physiological levels of oxygen), cancer cells preferentially convert glucose to lactate, according to Otto H. Warburg, who believed that aerobic glycolysis was the key metabolic change in cancer cell malignancy. The "Warburg effect" was later coined to describe this metabolic shift. [6] Warburg thought this change in metabolism was due to mitochondrial "respiration injury", but this interpretation was questioned by other researchers in 1956 showing that intact and functional cytochromes detected in most tumor cells clearly speak against a general mitochondrial dysfunction. [7] Furthermore, Potter et al. and several other authors provided significant evidence that oxidative phosphorylation and a normal Krebs cycle persist in the vast majority malignant tumors, adding to the growing body of evidence that most cancers exhibit the Warburg effect while maintaining a proper mitochondrial respiration. [6] [8] Dang et al. [9] in 2008 provided evidence that the tumor tissue sections used in Warburg's experiments should have been thinner for the oxygen diffusion constants employed, implying that the tissue slices studied were partially hypoxic and the calculated critical diffusion distance was of 470 micrometers. [6] As a result, endless debates and discussions about Warburg's discovery took place and have piqued the interest of scientists all over the world, which has helped bring attention to cell metabolism in cancer and immune cells and the use of modern technology to discover what these pathways are and how they are modified as well as potential therapeutic targets.

Metabolic reprogramming

Simplified view of the aerobic glycolysis (Warburg's effect). Warburg's effect.png
Simplified view of the aerobic glycolysis (Warburg's effect).

Carcinogenic cells undergo a metabolic rewiring during oncogenesis, and oncometabolites play an important role. In cancer, there are several reprogrammed metabolic pathways that help cells survive when nutrients are scarce: Aerobic glycolysis, an increase in glycolytic flux, also known as the Warburg effect, allows glycolytic intermediates to supply subsidiary pathways to meet the metabolic demands of proliferating tumorigenic cells. [10] Another studied reprogrammed pathway is gain of function of the oncogene MYC. This gene encodes a transcription factor that boosts the expression of a number of genes involved in anabolic growth via mitochondrial metabolism. [11] Oncometabolite production is another example of metabolic deregulation. [12]

Oncometabolites

Oncometabolites are metabolites whose abundance increases markedly in cancer cells through loss-of-function or gain-of-function mutations in specific enzymes involved in their production, the accumulation of these endogenous metabolites initiates or sustains tumor growth and metastasis. [13] Cancer cells rely on aerobic glycolysis, which is reached through defects in enzymes involved in normal cell metabolism, this allows the cancer cells to meet their energy needs and divert acetyl-CoA from the TCA cycle to build essential biomolecules such as amino acids and lipids. [14] These defects cause an overabundance of endogenous metabolites, which are frequently involved in critical epigenetic changes and signaling pathways that have a direct impact on cancer cell metabolism. [15]

OncometaboliteRole Oncogenes Enzyme affectedAssociated malignanciesReferences
D-2-hydroxyglutarate Inhibits ATP synthase and mTOR signallingIDH1

IDH2

 Isocitrate dehydrogenase Brain cancer, Leukemia [15] [16] [17] [13]
Succinate Inhibits 2-oxoglutarate-dependent oxygenaseSDHA,SDHB,SDHC,SDHD,SDHAF1,SDHAF2 succinate dehydrogenase Renal and Thyroid tumors [15] [13]
Fumarate Inhibits 2-oxoglutarate-dependent oxygenaseFH Fumarate hydratase Leiomyomata, Renal cysts [15] [16] [13]
Glutamine**(Primary carbon-source for the biosynthesis of the oncometabolite 2-hydroxyglutarate) [18] [19]
Sarcosine Activates mTOR signalling pathwayGNMT Glycine-N-methyltransferase Pancreatic cancer, Hepatocellular carcinoma [18] [20] [21] [13] [22] [23]
Asparagine Anti-apoptotic agentASNS Asparagine synthetase Acute Lymphoblastic Leukemia [18] [13] [24]
Choline Methyl donor for DNA methylation which disrupts DNA repairPCYT1Aphosphate cytidylyltransferase 1 choline-αBreast, Brain and Prostate cancer [18] [13] [24]
LactateInduces local immunosuppressionLDHA Lactate dehydrogenase A Various types of cancer [25] [13] [26]

Epigenetics

Oncometabolite dysregulation and cancer progression are linked to epigenetic changes in cancer cells. Several mechanisms have been linked to D-2-hydroxyglutarate, succinate, and fumarate with the inhibition of α-KG–dependent dioxygenases, this causes epigenetic changes that affect the expression of genes involved in cell differentiation and the development of malignant characteristics. [27] The group of Timothy A. Chan [28] described a mechanism by which abnormal accumulation of the oncometabolite D-2-hydroxyglutarate in brain tumor samples increased DNA methylation, a process that has been shown to play a key role in oncogenesis. [29] On the other hand, in paraganglioma cells, succinate and fumarate were found to methylate histones, effectively silencing the genes PNMT and KRT19, which are involved in neuroendocrine differentiation and epithelial-mesenchymal transition, respectively. [30]

Biomarkers for cancer detection

The discovery of oncometabolites has ushered in a new era in cancer biology, one that has the potential to improve patient care. The discovery of new therapeutic and reliable markers that exploit vulnerabilities of cancer cells, are being used to targeting either upstream or downstream effectors of these pathways. [15] Oncometabolites can be used as diagnostic biomarkers and may be able to assist oncologists in making more precise decisions in early stages of tumorigenesis, particularly in predicting more aggressive tumor behavior. [4]

Isocitrate dehydrogenase

Crystallographic structure of protein isocitrate dehydrogenase. Isocitrate dehydrogenase.png
Crystallographic structure of protein isocitrate dehydrogenase.

The detection of D-2-hydroxyglutarate in glioma patients using proton magnetic resonance spectroscopy (MRS) has been shown to be a noninvasive procedure. The presence of IDH1 or IDH2 mutations was linked to the detection of this oncometabolite 100 percent of the time. [31] [27] IDH2/R140Q is a specific mutation that has shown promising results after its inhibition by the small molecule AGI-6780. [32] Therefore, limiting the supply of D-2-hydroxyglutarate by inhibiting the detected mutant IDH enzymes could be a good therapeutical approach to IDH-mutant cancers. [33]

Succinate dehydrogenase

IHC staining has been shown to be a useful diagnostic tool for prioritizing patients for SDH mutation testing in early stages of cancer. The absence of SDHB in IHC staining would be linked to the presence of SDH oncogene mutations. [34] The already commercialized drug decitabine (Dacogen®) could be an effective therapy to repress the migration capacities of SDHB-mutant cells, [30]

Fumarate hydratase

IHC staining for FH is used to detect lack of this protein in patients with papillary renal cell carcinoma type 2. [35] The lack of FH in renal carcinoma cells induces pro-survival metabolic adaptations where several cascades are affected. [36]

Glycine-N-methyltransferase

Downregulation of glycine-N-methyltransferase has been linked to hepatocellular carcinoma and pancreatic cancer. Serving this as a reliable marker for oncogenesis. [22] When compared to patients with deletions in GNMT, patients with no deletions early-stage pancreatic cancer had twice the median months overall survival. [23]

Applications

Oncometabolomics

Metabolomics can be applied to oncometabolism, since the changes in cancer's genomic, transcriptomic, and proteomic profiles can result in changes in downstream metabolic pathways. With this information we can elucidate the responsible pathways and oncometabolites for various diseases. Actually, through the use of this technique, the dysregulation of the pyruvate kinase enzyme in glucose metabolism was discovered in cancer cells. Another common used technique is glucose or glutamine labeled with 13C to show that the TCA cycle is used to generate large amounts of fatty acids (phospholipids) and to replenish the TCA cycle intermediates. [37] But oncometabolomics does not necessarily need to be used on cancer cells, but on cells immediately surrounding them in the TME. [38]

Metabolomics applied to cancer has the potential to significantly improve current oncological treatments and has a great diagnostic value, since metabolic changes are the prequel of phenotypic changes in cells (thus tissues and organs) making it suitable for early detection of difficult-to-detect cancers. [14] This also leads to a more personalized medicine and customize an individual's cancer treatment according to their specific oncometabolite profiles, which would allow for better cancer therapy customization or informed adjustments. [13] [39]

Software and libraries

Ingenuity Pathway Analysis (IPA)

Ingenuity Pathway Analysis (IPA) is a metabolic pathway analysis software package that helps researchers model, analyze, and comprehend complex biological systems by associating specific metabolites with potential metabolic pathways for data analysis. [40] This software has been used by researchers to elucidate regulatory networks on oncometabolites like hydroxyglutarate. [41]

Metabolights

Metabolights is an open-access database for metabolomics research that collects all experimental data from leading journals' metabolic experiments. [42] Since its initial release in 2012, the MetaboLights repository has seen consistent year-on-year growth. It is a resource that surged in response to the needs of the scientific community to easy access to metabolite data. [43] [44]

Research

Transmission electron microscopy of purified exosomes. Exosomas vesiculas Cardiomiocito.png
Transmission electron microscopy of purified exosomes.

Cancer research has been ongoing for centuries, trying to elucidate the origin of its cause. As cancer research evolves with time, the scientific community tends to pay more attention to cell metabolism and how to target these metabolic needs and changes that cells undergo during carcinogenesis. [45] There is growing evidence that metabolic dependencies in cancer are influenced by tissue environment, being this important to consider the TME for different in vitro and in vivo models to study oncometabolism in different cancer scenarios. [46]

There is extensive research on the modulation of BET proteins in cancer models of breast. These proteins appear to be involved in oncometabolism and targeting and uncoupling BRD4 actions in carcinogenic cells, as well as stopping pro-migratory signals and changing cytokine metabolism, particularly IL-6. [47] The same group has reported on the importance of exosomes in the TME and how these vesicles, shed by adipocytes, can carry a specific molecular cargo that causes metabolic changes in the cell, leading to pro-metastatic changes in the recipient breast cancer cells. [48]

Related Research Articles

<span class="mw-page-title-main">Metabolic pathway</span> Linked series of chemical reactions occurring within a cell

In biochemistry, a metabolic pathway is a linked series of chemical reactions occurring within a cell. The reactants, products, and intermediates of an enzymatic reaction are known as metabolites, which are modified by a sequence of chemical reactions catalyzed by enzymes. In most cases of a metabolic pathway, the product of one enzyme acts as the substrate for the next. However, side products are considered waste and removed from the cell. These enzymes often require dietary minerals, vitamins, and other cofactors to function.

<span class="mw-page-title-main">Succinic acid</span> Dicarboxylic acid

Succinic acid is a dicarboxylic acid with the chemical formula (CH2)2(CO2H)2. In living organisms, succinic acid takes the form of an anion, succinate, which has multiple biological roles as a metabolic intermediate being converted into fumarate by the enzyme succinate dehydrogenase in complex 2 of the electron transport chain which is involved in making ATP, and as a signaling molecule reflecting the cellular metabolic state.

<span class="mw-page-title-main">Tumor hypoxia</span> Situation where tumor cells have been deprived of oxygen

Tumor hypoxia is the situation where tumor cells have been deprived of oxygen. As a tumor grows, it rapidly outgrows its blood supply, leaving portions of the tumor with regions where the oxygen concentration is significantly lower than in healthy tissues. Hypoxic microenvironements in solid tumors are a result of available oxygen being consumed within 70 to 150 μm of tumour vasculature by rapidly proliferating tumor cells thus limiting the amount of oxygen available to diffuse further into the tumor tissue. In order to support continuous growth and proliferation in challenging hypoxic environments, cancer cells are found to alter their metabolism. Furthermore, hypoxia is known to change cell behavior and is associated with extracellular matrix remodeling and increased migratory and metastatic behavior.

<span class="mw-page-title-main">Insulin-like growth factor 1</span> Protein-coding gene in the species Homo sapiens

Insulin-like growth factor 1 (IGF-1), also called somatomedin C, is a hormone similar in molecular structure to insulin which plays an important role in childhood growth, and has anabolic effects in adults.

<span class="mw-page-title-main">Metabolomics</span> Scientific study of chemical processes involving metabolites

Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.

<span class="mw-page-title-main">Metabolome</span>

The metabolome refers to the complete set of small-molecule chemicals found within a biological sample. The biological sample can be a cell, a cellular organelle, an organ, a tissue, a tissue extract, a biofluid or an entire organism. The small molecule chemicals found in a given metabolome may include both endogenous metabolites that are naturally produced by an organism as well as exogenous chemicals that are not naturally produced by an organism.

<span class="mw-page-title-main">Isocitrate dehydrogenase</span> Class of enzymes

Isocitrate dehydrogenase (IDH) (EC 1.1.1.42) and (EC 1.1.1.41) is an enzyme that catalyzes the oxidative decarboxylation of isocitrate, producing alpha-ketoglutarate (α-ketoglutarate) and CO2. This is a two-step process, which involves oxidation of isocitrate (a secondary alcohol) to oxalosuccinate (a ketone), followed by the decarboxylation of the carboxyl group beta to the ketone, forming alpha-ketoglutarate. In humans, IDH exists in three isoforms: IDH3 catalyzes the third step of the citric acid cycle while converting NAD+ to NADH in the mitochondria. The isoforms IDH1 and IDH2 catalyze the same reaction outside the context of the citric acid cycle and use NADP+ as a cofactor instead of NAD+. They localize to the cytosol as well as the mitochondrion and peroxisome.

In oncology, the Warburg effect is the observation that most cancer cells produce energy predominantly not through the 'usual' citric acid cycle and oxidative phosphorylation in the mitochondria as observed in normal cells, but through a less efficient process of 'aerobic glycolysis' consisting of a high level of glucose uptake and glycolysis followed by lactic acid fermentation taking place in the cytosol, not the mitochondria, even in the presence of abundant oxygen. This observation was first published by Otto Heinrich Warburg, who was awarded the 1931 Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme". The precise mechanism and therapeutic implications of the Warburg effect, however, remain unclear.

<span class="mw-page-title-main">Tumor metabolome</span>

The study of the tumor metabolism, also known as tumor metabolome describes the different characteristic metabolic changes in tumor cells. The characteristic attributes of the tumor metabolome are high glycolytic enzyme activities, the expression of the pyruvate kinase isoenzyme type M2, increased channeling of glucose carbons into synthetic processes, such as nucleic acid, amino acid and phospholipid synthesis, a high rate of pyrimidine and purine de novo synthesis, a low ratio of Adenosine triphosphate and Guanosine triphosphate to Cytidine triphosphate and Uridine triphosphate, low Adenosine monophosphate levels, high glutaminolytic capacities, release of immunosuppressive substances and dependency on methionine.

<span class="mw-page-title-main">Papillary thyroid cancer</span> Medical condition

Papillary thyroid cancer is the most common type of thyroid cancer, representing 75 percent to 85 percent of all thyroid cancer cases. It occurs more frequently in women and presents in the 20–55 year age group. It is also the predominant cancer type in children with thyroid cancer, and in patients with thyroid cancer who have had previous radiation to the head and neck. It is often well-differentiated, slow-growing, and localized, although it can metastasize.

<span class="mw-page-title-main">Warburg hypothesis</span> Hypothesis explaining cancer

The Warburg hypothesis, sometimes known as the Warburg theory of cancer, postulates that the driver of tumorigenesis is an insufficient cellular respiration caused by insult to mitochondria. The term Warburg effect in oncology describes the observation that cancer cells, and many cells grown in vitro, exhibit glucose fermentation even when enough oxygen is present to properly respire. In other words, instead of fully respiring in the presence of adequate oxygen, cancer cells ferment. The Warburg hypothesis was that the Warburg effect was the root cause of cancer. The current popular opinion is that cancer cells ferment glucose while keeping up the same level of respiration that was present before the process of carcinogenesis, and thus the Warburg effect would be defined as the observation that cancer cells exhibit glycolysis with lactate production and mitochondrial respiration even in the presence of oxygen.

The Cancer Genome Atlas (TCGA) is a project to catalogue the genetic mutations responsible for cancer using genome sequencing and bioinformatics. The overarching goal was to apply high-throughput genome analysis techniques to improve the ability to diagnose, treat, and prevent cancer through a better understanding of the genetic basis of the disease.

<span class="mw-page-title-main">Folliculin</span> Protein-coding gene

The tumor suppressor gene FLCN encodes the protein folliculin, also known as Birt–Hogg–Dubé syndrome protein, which functions as an inhibitor of Lactate Dehydrogenase-A and a regulator of the Warburg effect. Folliculin (FLCN) is also associated with Birt–Hogg–Dubé syndrome, which is an autosomal dominant inherited cancer syndrome in which affected individuals are at risk for the development of benign cutaneous tumors (folliculomas), pulmonary cysts, and kidney tumors.

<span class="mw-page-title-main">IDH2</span>

Isocitrate dehydrogenase [NADP], mitochondrial is an enzyme that in humans is encoded by the IDH2 gene.

<span class="mw-page-title-main">PKM2</span> Protein-coding gene in the species Homo sapiens

Pyruvate kinase isozymes M1/M2 (PKM1/M2), also known as pyruvate kinase muscle isozyme (PKM), pyruvate kinase type K, cytosolic thyroid hormone-binding protein (CTHBP), thyroid hormone-binding protein 1 (THBP1), or opa-interacting protein 3 (OIP3), is an enzyme that in humans is encoded by the PKM2 gene.

α-Hydroxyglutaric acid Chemical compound

α-Hydroxyglutaric acid is an alpha hydroxy acid form of glutaric acid.

<span class="mw-page-title-main">Hereditary leiomyomatosis and renal cell cancer syndrome</span> Medical condition

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) or Reed's syndrome is rare autosomal dominant disorder associated with benign smooth muscle tumors and an increased risk of renal cell carcinoma. It is characterised by multiple cutaneous leiomyomas and, in women, uterine leiomyomas. It predisposes for renal cell cancer, an association denominated hereditary leiomyomatosis and renal cell cancer, and it is also associated with increased risk of uterine leiomyosarcoma. The syndrome is caused by a mutation in the fumarate hydratase gene, which leads to an accumulation of fumarate. The inheritance pattern is autosomal dominant and screening can typically begin in childhood.

<span class="mw-page-title-main">Cancer epigenetics</span> Field of study in cancer research

Cancer epigenetics is the study of epigenetic modifications to the DNA of cancer cells that do not involve a change in the nucleotide sequence, but instead involve a change in the way the genetic code is expressed. Epigenetic mechanisms are necessary to maintain normal sequences of tissue specific gene expression and are crucial for normal development. They may be just as important, if not even more important, than genetic mutations in a cell's transformation to cancer. The disturbance of epigenetic processes in cancers, can lead to a loss of expression of genes that occurs about 10 times more frequently by transcription silencing than by mutations. As Vogelstein et al. points out, in a colorectal cancer there are usually about 3 to 6 driver mutations and 33 to 66 hitchhiker or passenger mutations. However, in colon tumors compared to adjacent normal-appearing colonic mucosa, there are about 600 to 800 heavily methylated CpG islands in the promoters of genes in the tumors while these CpG islands are not methylated in the adjacent mucosa. Manipulation of epigenetic alterations holds great promise for cancer prevention, detection, and therapy. In different types of cancer, a variety of epigenetic mechanisms can be perturbed, such as the silencing of tumor suppressor genes and activation of oncogenes by altered CpG island methylation patterns, histone modifications, and dysregulation of DNA binding proteins. There are several medications which have epigenetic impact, that are now used in a number of these diseases.

<span class="mw-page-title-main">Tumor microenvironment</span> Surroundings of tumors including nearby cells and blood vessels

The tumor microenvironment (TME) is the environment around a tumor, including the surrounding blood vessels, immune cells, fibroblasts, signaling molecules and the extracellular matrix (ECM). The tumor and the surrounding microenvironment are closely related and interact constantly. Tumors can influence the microenvironment by releasing extracellular signals, promoting tumor angiogenesis and inducing peripheral immune tolerance, while the immune cells in the microenvironment can affect the growth and evolution of cancerous cells.

Metabolite damage can occur through enzyme promiscuity or spontaneous chemical reactions. Many metabolites are chemically reactive and unstable and can react with other cell components or undergo unwanted modifications. Enzymatically or chemically damaged metabolites are always useless and often toxic. To prevent toxicity that can occur from the accumulation of damaged metabolites, organisms have damage-control systems that:

  1. Reconvert damaged metabolites to their original, undamaged form
  2. Convert a potentially harmful metabolite to a benign one
  3. Prevent damage from happening by limiting the build-up of reactive, but non-damaged metabolites that can lead to harmful products

References

  1. 1 2 3 4 Urbano AM (January 2021). "Otto Warburg: The journey towards the seminal discovery of tumor cell bioenergetic reprogramming". Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1867 (1): 165965. doi: 10.1016/j.bbadis.2020.165965 . PMID   32949769. S2CID   221807074.
  2. 1 2 Oliveira PJ, Urbano AM (February 2021). ""Oncometabolism: The switchboard of cancer - An editorial"". Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1867 (2): 166031. doi: 10.1016/j.bbadis.2020.166031 . PMID   33310398. S2CID   229175329.
  3. ↑ Cooper CS (1990). "The Role of Oncogene Activation in Chemical Carcinogenesis". Chemical Carcinogenesis and Mutagenesis II. Handbook of Experimental Pharmacology. Vol. 94. Berlin, Heidelberg: Springer Berlin Heidelberg. pp. 319–352. doi:10.1007/978-3-642-74778-6_12. ISBN   978-3-642-74780-9.
  4. 1 2 Dando I, Pozza ED, Ambrosini G, Torrens-Mas M, Butera G, Mullappilly N, et al. (August 2019). "Oncometabolites in cancer aggressiveness and tumour repopulation". Biological Reviews of the Cambridge Philosophical Society. 94 (4): 1530–1546. doi:10.1111/brv.12513. PMID   30972955. S2CID   108294182.
  5. ↑ Biswas SK (September 2015). "Metabolic Reprogramming of Immune Cells in Cancer Progression". Immunity. 43 (3): 435–449. doi: 10.1016/j.immuni.2015.09.001 . PMID   26377897.
  6. 1 2 3 Vaupel P, Schmidberger H, Mayer A (July 2019). "The Warburg effect: essential part of metabolic reprogramming and central contributor to cancer progression". International Journal of Radiation Biology. 95 (7): 912–919. doi:10.1080/09553002.2019.1589653. PMID   30822194. S2CID   73502809.
  7. ↑ Pascale RM, Calvisi DF, Simile MM, Feo CF, Feo F (September 2020). "The Warburg Effect 97 Years after Its Discovery". Cancers. 12 (10): 2819. doi: 10.3390/cancers12102819 . PMC   7599761 . PMID   33008042.
  8. ↑ Potter M, Newport E, Morten KJ (October 2016). "The Warburg effect: 80 years on". Biochemical Society Transactions. 44 (5): 1499–1505. doi:10.1042/bst20160094. PMC   5095922 . PMID   27911732.
  9. ↑ Dang, et al. The interplay between MYC and HIF in cancer. Nature Reviews Cancer volume 8, pages51–56 (2008).
  10. ↑ Lunt SY, Vander Heiden MG (2011-11-10). "Aerobic glycolysis: meeting the metabolic requirements of cell proliferation". Annual Review of Cell and Developmental Biology. 27 (1): 441–464. doi:10.1146/annurev-cellbio-092910-154237. hdl: 1721.1/78654 . PMID   21985671.
  11. ↑ Van Dang C (October 2015). "Abstract IA05: Targeting MYC-mediated cancer metabolism". Molecular Cancer Research. American Association for Cancer Research. 13 (10_Supplement): IA05. doi:10.1158/1557-3125.myc15-ia05.
  12. ↑ DeBerardinis RJ, Chandel NS (May 2016). "Fundamentals of cancer metabolism". Science Advances. 2 (5): e1600200. Bibcode:2016SciA....2E0200D. doi:10.1126/sciadv.1600200. PMC   4928883 . PMID   27386546.
  13. 1 2 3 4 5 6 7 8 9 Wishart DS (July 2016). "Emerging applications of metabolomics in drug discovery and precision medicine". Nature Reviews. Drug Discovery. 15 (7): 473–484. doi:10.1038/nrd.2016.32. PMID   26965202. S2CID   5265996.
  14. 1 2 Gupta S, Chawla K (August 2013). "Oncometabolomics in cancer research". Expert Review of Proteomics. 10 (4): 325–336. doi:10.1586/14789450.2013.828947. PMID   23992416. S2CID   19476401.
  15. 1 2 3 4 5 Collins RR, Patel K, Putnam WC, Kapur P, Rakheja D (December 2017). "Oncometabolites: A New Paradigm for Oncology, Metabolism, and the Clinical Laboratory". Clinical Chemistry. 63 (12): 1812–1820. doi: 10.1373/clinchem.2016.267666 . PMID   29038145.
  16. 1 2 Yang M, Soga T, Pollard PJ, Adam J (2012). "The emerging role of fumarate as an oncometabolite". Frontiers in Oncology. 2: 85. doi: 10.3389/fonc.2012.00085 . PMC   3408580 . PMID   22866264.
  17. ↑ Garber K (July 2010). "Oncometabolite? IDH1 discoveries raise possibility of new metabolism targets in brain cancers and leukemia". Journal of the National Cancer Institute. 102 (13): 926–928. doi: 10.1093/jnci/djq262 . PMID   20576929.
  18. 1 2 3 4 Khatami F, Aghamir SM, Tavangar SM (September 2019). "Oncometabolites: A new insight for oncology". Molecular Genetics & Genomic Medicine. 7 (9): e873. doi:10.1002/mgg3.873. PMC   6732276 . PMID   31321921.
  19. ↑ Salamanca-Cardona L, Shah H, Poot AJ, Correa FM, Di Gialleonardo V, Lui H, et al. (December 2017). "In Vivo Imaging of Glutamine Metabolism to the Oncometabolite 2-Hydroxyglutarate in IDH1/2 Mutant Tumors". Cell Metabolism. 26 (6): 830–841.e3. doi:10.1016/j.cmet.2017.10.001. PMC   5718944 . PMID   29056515.
  20. ↑ Khan AP, Rajendiran TM, Ateeq B, Asangani IA, Athanikar JN, Yocum AK, et al. (May 2013). "The role of sarcosine metabolism in prostate cancer progression". Neoplasia. 15 (5): 491–501. doi:10.1593/neo.13314. PMC   3638352 . PMID   23633921.
  21. ↑ Rodrigo MA, Strmiska V, Horackova E, Buchtelova H, Michalek P, Stiborova M, et al. (February 2018). "Sarcosine influences apoptosis and growth of prostate cells via cell-type specific regulation of distinct sets of genes". The Prostate. 78 (2): 104–112. doi:10.1002/pros.23450. PMID   29105933. S2CID   3015270.
  22. 1 2 Chen M, Yang MH, Chang MM, Tyan YC, Chen YA (September 2019). "Tumor suppressor gene glycine N-methyltransferase and its potential in liver disorders and hepatocellular carcinoma". Toxicology and Applied Pharmacology. 378: 114607. doi:10.1016/j.taap.2019.114607. PMID   31170416. S2CID   174817577.
  23. 1 2 Heinzman Z, Schmidt C, Sliwinski MK, Goonesekere NC (March 2021). "The Case for GNMT as a Biomarker and a Therapeutic Target in Pancreatic Cancer". Pharmaceuticals. 14 (3): 209. doi: 10.3390/ph14030209 . PMC   7998508 . PMID   33802396.
  24. 1 2 Chiu M, Taurino G, Bianchi MG, Kilberg MS, Bussolati O (2020-01-09). "Asparagine Synthetase in Cancer: Beyond Acute Lymphoblastic Leukemia". Frontiers in Oncology. 9: 1480. doi: 10.3389/fonc.2019.01480 . PMC   6962308 . PMID   31998641.
  25. ↑ Feng Y, Xiong Y, Qiao T, Li X, Jia L, Han Y (December 2018). "Lactate dehydrogenase A: A key player in carcinogenesis and potential target in cancer therapy". Cancer Medicine. 7 (12): 6124–6136. doi:10.1002/cam4.1820. PMC   6308051 . PMID   30403008.
  26. ↑ Valvona CJ, Fillmore HL, Nunn PB, Pilkington GJ (January 2016). "The Regulation and Function of Lactate Dehydrogenase A: Therapeutic Potential in Brain Tumor". Brain Pathology. 26 (1): 3–17. doi:10.1111/bpa.12299. PMC   8029296 . PMID   26269128.
  27. 1 2 Yang M, Soga T, Pollard PJ (September 2013). "Oncometabolites: linking altered metabolism with cancer". The Journal of Clinical Investigation. 123 (9): 3652–3658. doi:10.1172/jci67228. PMC   3754247 . PMID   23999438.
  28. ↑ Turcan S, Rohle D, Goenka A, Walsh LA, Fang F, Yilmaz E, et al. (February 2012). "IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype". Nature. 483 (7390): 479–483. Bibcode:2012Natur.483..479T. doi:10.1038/nature10866. PMC   3351699 . PMID   22343889.
  29. ↑ Jones PA, Baylin SB (February 2007). "The epigenomics of cancer". Cell. 128 (4): 683–692. doi:10.1016/j.cell.2007.01.029. PMC   3894624 . PMID   17320506.
  30. 1 2 Letouzé E, Martinelli C, Loriot C, Burnichon N, Abermil N, Ottolenghi C, et al. (June 2013). "SDH mutations establish a hypermethylator phenotype in paraganglioma". Cancer Cell. 23 (6): 739–752. doi: 10.1016/j.ccr.2013.04.018 . PMID   23707781.
  31. ↑ Choi C, Ganji SK, DeBerardinis RJ, Hatanpaa KJ, Rakheja D, Kovacs Z, et al. (January 2012). "2-hydroxyglutarate detection by magnetic resonance spectroscopy in IDH-mutated patients with gliomas". Nature Medicine. 18 (4): 624–629. doi:10.1038/nm.2682. PMC   3615719 . PMID   22281806.
  32. ↑ Wang F, Travins J, DeLaBarre B, Penard-Lacronique V, Schalm S, Hansen E, et al. (May 2013). "Targeted inhibition of mutant IDH2 in leukemia cells induces cellular differentiation". Science. 340 (6132): 622–626. Bibcode:2013Sci...340..622W. doi:10.1126/science.1234769. PMID   23558173. S2CID   9292787.
  33. ↑ Ye D, Guan KL, Xiong Y (February 2018). "Metabolism, Activity, and Targeting of D- and L-2-Hydroxyglutarates". Trends in Cancer. 4 (2): 151–165. doi:10.1016/j.trecan.2017.12.005. PMC   5884165 . PMID   29458964.
  34. ↑ van Nederveen FH, Gaal J, Favier J, Korpershoek E, Oldenburg RA, de Bruyn EM, et al. (August 2009). "An immunohistochemical procedure to detect patients with paraganglioma and phaeochromocytoma with germline SDHB, SDHC, or SDHD gene mutations: a retrospective and prospective analysis". The Lancet. Oncology. 10 (8): 764–771. doi:10.1016/S1470-2045(09)70164-0. PMC   4718191 . PMID   19576851.
  35. ↑ Trpkov K, Hes O, Agaimy A, Bonert M, Martinek P, Magi-Galluzzi C, et al. (July 2016). "Fumarate Hydratase-deficient Renal Cell Carcinoma Is Strongly Correlated With Fumarate Hydratase Mutation and Hereditary Leiomyomatosis and Renal Cell Carcinoma Syndrome". The American Journal of Surgical Pathology. 40 (7): 865–875. doi:10.1097/pas.0000000000000617. hdl: 2158/1116837 . PMID   26900816. S2CID   205917783.
  36. ↑ Schmidt C, Sciacovelli M, Frezza C (February 2020). "Fumarate hydratase in cancer: A multifaceted tumour suppressor". Seminars in Cell & Developmental Biology. 98: 15–25. doi:10.1016/j.semcdb.2019.05.002. PMC   6974395 . PMID   31085323.
  37. ↑ Benjamin DI, Cravatt BF, Nomura DK (November 2012). "Global profiling strategies for mapping dysregulated metabolic pathways in cancer". Cell Metabolism. 16 (5): 565–577. doi:10.1016/j.cmet.2012.09.013. PMC   3539740 . PMID   23063552.
  38. ↑ Chaudhri VK, Salzler GG, Dick SA, Buckman MS, Sordella R, Karoly ED, et al. (June 2013). "Metabolic alterations in lung cancer-associated fibroblasts correlated with increased glycolytic metabolism of the tumor". Molecular Cancer Research. 11 (6): 579–592. doi:10.1158/1541-7786.mcr-12-0437-t. PMC   3686965 . PMID   23475953.
  39. ↑ Wishart DS (June 2015). "Is Cancer a Genetic Disease or a Metabolic Disease?". eBioMedicine. 2 (6): 478–479. doi:10.1016/j.ebiom.2015.05.022. PMC   4535307 . PMID   26288805.
  40. ↑ Koo I, Wei X, Zhang X (2014). Analysis of metabolomic profiling data acquired on GC-MS. Methods in Enzymology. Vol. 543. Elsevier. pp. 315–324. doi:10.1016/B978-0-12-801329-8.00016-7. ISBN   9780128013298. PMID   24924140.
  41. ↑ Liu L, Hu K, Feng J, Wang H, Fu S, Wang B, et al. (January 2021). "The oncometabolite R-2-hydroxyglutarate dysregulates the differentiation of human mesenchymal stromal cells via inducing DNA hypermethylation". BMC Cancer. 21 (1): 36. doi: 10.1186/s12885-020-07744-x . PMC   7791852 . PMID   33413208.
  42. ↑ "MetaboLights - Metabolomics experiments and derived information". www.ebi.ac.uk. Retrieved 2021-11-08.
  43. ↑ Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O'Donovan C (January 2020). "MetaboLights: a resource evolving in response to the needs of its scientific community". Nucleic Acids Research. 48 (D1): D440–D444. doi:10.1093/nar/gkz1019. PMC   7145518 . PMID   31691833.
  44. ↑ Haug K, Salek RM, Conesa P, Hastings J, de Matos P, Rijnbeek M, et al. (January 2013). "MetaboLights--an open-access general-purpose repository for metabolomics studies and associated meta-data". Nucleic Acids Research. 41 (Database issue): D781–D786. doi:10.1093/nar/gks1004. PMC   3531110 . PMID   23109552.
  45. ↑ Park JH, Pyun WY, Park HW (October 2020). "Cancer Metabolism: Phenotype, Signaling and Therapeutic Targets". Cells. 9 (10): 2308. doi: 10.3390/cells9102308 . PMC   7602974 . PMID   33081387.
  46. ↑ Luengo A, Gui DY, Vander Heiden MG (September 2017). "Targeting Metabolism for Cancer Therapy". Cell Chemical Biology. 24 (9): 1161–1180. doi:10.1016/j.chembiol.2017.08.028. PMC   5744685 . PMID   28938091.
  47. ↑ Andrieu G, Tran AH, Strissel KJ, Denis GV (November 2016). "BRD4 Regulates Breast Cancer Dissemination through Jagged1/Notch1 Signaling". Cancer Research. 76 (22): 6555–6567. doi:10.1158/0008-5472.CAN-16-0559. PMC   5290198 . PMID   27651315.
  48. ↑ Jafari N, Kolla M, Meshulam T, Shafran JS, Qiu Y, Casey AN, et al. (November 2021). "Adipocyte-derived exosomes may promote breast cancer progression in type 2 diabetes". Science Signaling. 14 (710): eabj2807. doi:10.1126/scisignal.abj2807. ISSN   1945-0877. PMC   8765301 . PMID   34813359. S2CID   244529960.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.