Jump to content

Oncometabolism

From Wikipedia, the free encyclopedia

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]

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

History

[edit]

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

[edit]

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

[edit]
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

[edit]

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]

Oncometabolite Role Oncogenes Enzyme affected Associated malignancies References
D-2-hydroxyglutarate Inhibits ATP synthase and mTOR signalling IDH1

IDH2

Isocitrate dehydrogenase Brain cancer, Leukemia [15][16][17][13]
Succinate Inhibits 2-oxoglutarate-dependent oxygenase SDHA,SDHB,SDHC,SDHD,SDHAF1,SDHAF2 succinate dehydrogenase Renal and Thyroid tumors [15][13]
Fumarate Inhibits 2-oxoglutarate-dependent oxygenase FH 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 pathway GNMT Glycine-N-methyltransferase Pancreatic cancer, Hepatocellular carcinoma [18][20][21][13][22][23]
Asparagine Anti-apoptotic agent ASNS Asparagine synthetase Acute Lymphoblastic Leukemia [18][13][24]
Choline Methyl donor for DNA methylation which disrupts DNA repair PCYT1A phosphate cytidylyltransferase 1 choline-α Breast, Brain and Prostate cancer [18][13][24]
Lactate Induces local immunosuppression LDHA Lactate dehydrogenase A Various types of cancer[25] [13][26]

Epigenetics

[edit]

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

[edit]

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

[edit]
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

[edit]

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

[edit]

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

[edit]

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

[edit]

Oncometabolomics

[edit]

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

[edit]

Ingenuity Pathway Analysis (IPA)

[edit]

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

[edit]

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

[edit]
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]

References

[edit]
  1. ^ a b c d 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. ^ a b 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. ^ a b 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. ^ a b c 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. 13 (10_Supplement). American Association for Cancer Research: 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. ^ a b c d e f g h i 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. ^ a b 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. ^ a b c d e 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. ^ a b 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. ^ a b c d 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. ^ a b 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. ^ a b 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. ^ a b 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. ^ a b 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. ^ a b 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.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Oncometabolism&oldid=1262892124"