The DOI matches its Crossref record; 128 of the 128 references it cites were found in a registry or an index; none of the 72 sources its claims cite is checked for support yet.
Metabolic reprogramming and cancer progression
Open accessAbstract
Metabolism as cancer progresses: Numerous cancer-specific alterations in metabolism have been identified but have not yet resulted in an effective anti cancer therapeutic. In a Review, Faubert et al. discuss how metabolism changes as cancer develops from a small, premalignant lesion to an aggressive primary tumor and then metastasizes. Metabolic vulnerabilities likely change with cancer progression, making the identification of general cancer-associated metabolic features difficult. The authors propose that a more targeted approach to tissues and vulnerabilities identified in patients may be more effective. Science , this issue p. eaaw5473
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In the paper
“Metabolic reprogramming precedes liver cancer in mice with MYC expression in hepatocytes (23).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [23] Hu S, 13C-pyruvate imaging reveals alterations in glycolysis that precede c-Myc-induced tumor formation and regression. Cell Metab. 14, 131– 142 (2011). doi: 10.1016/j.cmet.2011.04.012 21723511 PMC3858338 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“Mutations in isocitrate dehydrogenase isoform-1 (IDH1) and IDH2 generate the oncometabolite D-2-hydroxyglutarate (D-2HG), which inhibits epigenetic enzymes including histone demethylases and the Ten-eleven translocation (TET) family of 5-methylcytosine hydroxylases.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [25] Figueroa ME, Leukemic IDH1 and IDH2 mutations result in a hypermethylation phenotype, disrupt TET2 function, and impair hematopoietic differentiation. Cancer Cell 18, 553– 567 (2010). doi: 10.1016/j.ccr.2010.11.015 21130701 PMC4105845 source
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In the paper
“The dormancy period between arrival of metastatic cells in a distant organ and appearance of macrometastasis varies widely.”
§ Metabolic reprogramming and cancer progression > Metastatic cancer
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In the paper
“Despite ubiquitous expression of the metabolic enzyme succinate dehydrogenase (SDH), germline mutations in subunits of this complex cause cancer only in a few sites, including neuroendocrine tissues (paraganglioma), the adrenal gland (pheochromocytoma), and the stomach and small intestine (gastrointestinal stromal tumors) (8–10).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [8] Baysal BE, Mutations in SDHD, a mitochondrial complex II gene, in hereditary paraganglioma. Science 287, 848– 851 (2000). doi: 10.1126/science.287.5454.848 10657297 source
- Not checked yetcites [9] Benn DE, Novel succinate dehydrogenase subunit B (SDHB) mutations in familial phaeochromocytomas and paragangliomas, but an absence of somatic SDHB mutations in sporadic phaeochromocytomas. Oncogene 22, 1358– 1364 (2003). doi: 10.1038/sj.onc.1206300 12618761 source
- Not checked yetcites [10] Hao HX, SDH5, a gene required for flavination of succinate dehydrogenase, is mutated in paraganglioma. Science 325, 1139– 1142 (2009). doi: 10.1126/science.1175689 19628817 PMC3881419 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“Second, as the approaches used to assess metabolic phenotypes have become more informative, it has become clear that human tumors are metabolically heterogeneous.”
§ Metabolic reprogramming and cancer progression > Abstract > OUTLOOK
What the sources say
- Not checked yetcites [2] Kim J, DeBerardinis RJ, Mechanisms and implications of metabolic heterogeneity in cancer. Cell Metab. 30, 434– 446 (2019). doi: 10.1016/j.cmet.2019.08.013 31484055 PMC6730674 source
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In the paper
“Therefore, classifying tumors according to the oncogenic driver rather than the tissue of origin may obscure metabolic differences imposed by the original metabolic state of the tissue.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“In the case of the classical tumor suppressor gene TP53, germline mutations result in a somewhat different tissue distribution of cancers than sporadic TP53-mutant cancers in patients who lack germline mutations (7).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [7] Malkin D, Germ line p53 mutations in a familial syndrome of breast cancer, sarcomas, and other neoplasms. Science 250, 1233– 1238 (1990). doi: 10.1126/science.1978757 1978757 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, chronic mitochondrial dysfunction in CCPAP may phenocopy loss of von Hippel-Lindau (VHL), the most commonly mutated tumor suppressor in clear cell renal cell carcinoma (ccRCC).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“In mice, oncogenic neuroblastoma Ras viral oncogene homolog (NRas) cooperates with mutations in the epigenetic regulator enhancer of zeste homolog 2 (Ezh2) to produce aggressive leukemias.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [28] Gu Z, Loss of EZH2 reprograms BCAA metabolism to drive leukemic transformation. Cancer Discov. 9, 1228– 1247 (2019). doi: 10.1158/2159-8290.CD-19-0152 31189531 PMC6726547 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“suggesting an indefinite period of dormancy in immunocompetent hosts (101).”
§ Metabolic reprogramming and cancer progression > Metastatic cancer
What the sources say
- Not checked yetcites [101] Armanios MY, Transmission of glioblastoma multiforme following bilateral lung transplantation from an affected donor: Case study and review of the literature. Neuro-oncol. 6, 259– 263 (2004). doi: 10.1215/S1152851703000474 15279719 PMC1871995 source
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- It may state two separate claims as one. 31
- Probably not a substantial claim. 4
None of the sources cited for this claim have been checked yet.
In the paper
“Oncogenic KRas increases the levels of acetyl coenzyme A (CoA) and reactive oxygen species (ROS) before the development of ADM, and inhibiting these phenotypes blocks ADM (19, 20).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [19] Liou GY, Mutant KRas-induced mitochondrial oxidative stress in acinar cells upregulates EGFR signaling to drive formation of pancreatic precancerous lesions. Cell Rep. 14, 2325– 2336 (2016). doi: 10.1016/j.celrep.2016.02.029 26947075 PMC4794374 source
- Not checked yetcites [20] Carrer A, Acetyl-CoA metabolism supports multistep pancreatic tumorigenesis. Cancer Discov. 9, 416– 435 (2019). doi: 10.1158/2159-8290.CD-18-0567 30626590 PMC6643997 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“But an alternative tracer, methyl-4-deoxy-4-[18F]-fluoro-α-d-glucopyranoside (Me4FDG), is taken up by SGLT and can identify AAH and low-grade adenocarcinomas of the lung (24).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [24] Scafoglio CR, Sodium-glucose transporter 2 is a diagnostic and therapeutic target for early-stage lung adenocarcinoma. Sci. Transl. Med. 10, eaat5933 (2018). doi: 10.1126/scitranslmed.aat5933 30429355 PMC6428683 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A major theme arising from recent research is that pathways that stimulate the growth of localized, treatment-naïve tumors are distinct from and in some cases irrelevant to the activities that drive mortality by supporting metastasis and therapy resistance.”
§ Metabolic reprogramming and cancer progression > Abstract > ADVANCES
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In the paper
“Many epidemiological studies report associations between obesity and cancer, and a large prospective analysis of more than 900,000 Americans found greater than a 50% increase in cancer mortality in patients with the highest body mass index (15, 16).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [15] Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ, Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N. Engl. J. Med. 348, 1625– 1638 (2003). doi: 10.1056/NEJMoa021423 12711737 source
- Not checked yetcites [16] Lauby-Secretan B, Body fatness and cancer-Viewpoint of the IARC Working Group. N. Engl. J. Med. 375, 794– 798 (2016). doi: 10.1056/NEJMsr1606602 27557308 PMC6754861 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“SGLT2 does not transport the common cancer imaging tracer 18fluoro-2-deoxyglucose (FDG), and thus, these lesions are poor candidates for FDG-PET (positron emission tomography) imaging.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Microenvironmental and genetic factors appear to induce selective pressures that drive clonal evolution within tumors, and this can create or eliminate metabolic liabilities while facilitating cancer progression.”
§ Metabolic reprogramming and cancer progression > Abstract > ADVANCES
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These studies demonstrate the functional and therapeutic relevance of metabolic reprogramming early in tumorigenesis.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Silencing Bcat1 reduces leukemia initiation, and overexpressing this enzyme promotes NRas-driven leukemia initiation even in cells that lack Ezh2 mutations (28).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [28] Gu Z, Loss of EZH2 reprograms BCAA metabolism to drive leukemic transformation. Cancer Discov. 9, 1228– 1247 (2019). doi: 10.1158/2159-8290.CD-19-0152 31189531 PMC6726547 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Other studies in humans and mice report metabolic changes in premalignant colonic polyps, some of which are retained in adenocarcinomas (21, 22).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [21] Backshall A, Detection of metabolic alterations in non-tumor gastrointestinal tissue of the Apc(Min/+) mouse by (1) H MAS NMR spectroscopy. J. Proteome Res. 8, 1423– 1430 (2009). doi: 10.1021/pr800793w 19159281 source
- Not checked yetcites [22] Phillips CM, Upregulation of cystathionine-β-synthase in colonic epithelia reprograms metabolism and promotes carcinogenesis. Cancer Res. 77, 5741– 5754 (2017). doi: 10.1158/0008-5472.CAN-16-3480 28923859 PMC5668191 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“In early-stage, premalignant liver, MYC drives enhanced conversion of pyruvate to alanine, whereas later-stage malignant lesions convert pyruvate to lactate.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [23] Hu S, 13C-pyruvate imaging reveals alterations in glycolysis that precede c-Myc-induced tumor formation and regression. Cell Metab. 14, 131– 142 (2011). doi: 10.1016/j.cmet.2011.04.012 21723511 PMC3858338 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Diabetes increases the frequency of KRAS variants in human pancreas, possibly through the effects of chronic hyperglycemia on nucleotide balance (17).”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [17] Hu CM, High glucose triggers nucleotide imbalance through O-GlcNacylation of key enzymes and induces KRAS mutation in pancreatic cells. Cell Metab. 29, 1334– 1349.e10 (2019). doi: 10.1016/j.cmet.2019.02.005 30853214 source
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The emerging view of cancer metabolism is that it is flexible and context-specific, with few fixed, broadly applicable liabilities.”
§ Metabolic reprogramming and cancer progression > Abstract > OUTLOOK
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Transgenic MYC induces metabolic changes in both liver tumors and lung tumors but activates glutamine catabolism in lung tumors and glutamine synthesis in liver tumors.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [5] Yuneva MO, The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type. Cell Metab. 15, 157– 170 (2012). doi: 10.1016/j.cmet.2011.12.015 22326218 PMC3282107 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Nevertheless, a detailed molecular analysis revealed a low genomic burden of point mutations and copy-number variants, no recurrent nonsynonymous mutations, and a DNA methylation pattern that resembles the nonmalignant kidney.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [13] Xu J, Abnormal oxidative metabolism in a quiet genomic background underlies clear cell papillary renal cell carcinoma. eLife 8, e38986 (2019). doi: 10.7554/eLife.38986 30924768 PMC6459676 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“These tumors bear metabolomic signatures that suggest oxidative stress, suppressed oxidative metabolism, and depletion of mitochondrial DNA and RNA.”
§ Metabolic reprogramming and cancer progression > Premalignant lesions
What the sources say
- Not checked yetcites [13] Xu J, Abnormal oxidative metabolism in a quiet genomic background underlies clear cell papillary renal cell carcinoma. eLife 8, e38986 (2019). doi: 10.7554/eLife.38986 30924768 PMC6459676 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Placing mice on a low-carbohydrate, ketogenic diet blunts the hyperglycemia and insulin release that accompany PI3K inhibition, and this improves the efficacy of PI3K inhibitors on tumor growth (113).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [113] Hopkins BD, Suppression of insulin feedback enhances the efficacy of PI3K inhibitors. Nature 560, 499– 503 (2018). doi: 10.1038/s41586-018-0343-4 30051890 PMC6197057 source
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None of the sources cited for this claim have been checked yet.
In the paper
“Recently described OXPHOS inhibitors display enhanced toxicity against cultured cancer cells compared with either nontransformed cells or other cancer cells with metabolic properties that allow them to compensate for OXPHOS impairment (116, 117). It is encouraging that these agents also suppress growth of susceptible tumors in mice, using doses that are well-tolerated over the short term.”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [116] Molina JR, An inhibitor of oxidative phosphorylation exploits cancer vulnerability. Nat. Med. 24, 1036– 1046 (2018). doi: 10.1038/s41591-018-0052-4 29892070 source
- Not checked yetcites [117] Shi Y, Gboxin is an oxidative phosphorylation inhibitor that targets glioblastoma. Nature 567, 341– 346 (2019). doi: 10.1038/s41586-019-0993-x 30842654 PMC6655586 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“In human prostate cancer, tumor grade correlates with MCT1 expression and with imaging of 13C-lactate after injection of hyperpolarized 13C-pyruvate (122).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [122] Granlund KL, Hyperpolarized MRI of human prostate cancer reveals increased lactate with tumor grade driven by monocarboxylate transporter 1. Cell Metab. 31, 105– 114.e3 (2020). doi: 10.1016/j.cmet.2019.08.024 31564440 PMC6949382 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“PI3K inhibitors suppress glucose uptake by the muscle and other tissues, resulting in elevated blood glucose and pancreatic insulin release after administration of the drug. The insulin surge reactivates PI3K signaling in the tumor, limiting the efficacy of PI3K inhibitors on tumor growth.”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [113] Hopkins BD, Suppression of insulin feedback enhances the efficacy of PI3K inhibitors. Nature 560, 499– 503 (2018). doi: 10.1038/s41586-018-0343-4 30051890 PMC6197057 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Evidence also indicates that metabolic phenotypes evolve as cancer progresses, with new dependencies emerging in the context of therapy resistance and metastasis.”
§ Metabolic reprogramming and cancer progression > Concluding remarks
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes? Based: unclearIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Glutamine addiction is a common feature of cultured cancer cells, and early attempts to target this pathway in vivo used the glutamine analog 6-diazo-5-oxo-l-norleucine (DON). By inhibiting a myriad of enzymes that use glutamine as a substrate, DON kills cancer cells but is unacceptably toxic to the gastrointestinal tract and other tissues, limiting its clinical development.”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Glutamine addiction is a common feature of cultured cancer cells.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The insights reviewed above indicate that cancer cell metabolism is flexible and heterogeneous”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“OXPHOS also promotes resistance to the antimetabolite cytarabine in mouse models of AML (115). Cells persisting after cytarabine treatment and preexisting cells with innate cytarabine resistance both displayed enhanced OXPHOS. Cytarabine treatment in AML-bearing mice spares cells with high levels of OXPHOS, and cytarabine-resistant cells are susceptible to OXPHOS inhibitors (115).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [115] Farge T, Chemotherapy-resistant human acute myeloid leukemia cells are not enriched for leukemic stem cells but require oxidative metabolism. Cancer Discov. 7, 716– 735 (2017). doi: 10.1158/2159-8290.CD-16-0441 28416471 PMC5501738 source
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In the paper
“A new probe, 4-[18F]fluorobenzyl-triphenylphosphonium (18F-BnTP), accumulates in tumors in proportion to their reliance on OXPHOS (123). In mouse models of lung cancer, 18F-BnTP imaging predicts sensitivity to OXPHOS inhibition, regardless of whether or not the tumors take up 18FDG.”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [123] Momcilovic M, In vivo imaging of mitochondrial membrane potential in non-small-cell lung cancer. Nature 575, 380– 384 (2019). doi: 10.1038/s41586-019-1715-0 31666695 PMC7328016 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“First, 2-HG accumulation in IDH1- and IDH2-mutant tumors is a rare example in which the metabolite directly reports the oncogenic driver and potential therapy (Fig. 4). Proton magnetic resonance spectroscopy can noninvasively track 2-HG abundance in IDH-mutant gliomas, predicting both disease progression and response to therapy through longitudinal 2-HG measurements (120).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [120] Choi C, Prospective longitudinal analysis of 2-hydroxyglutarate magnetic resonance spectroscopy identifies broad clinical utility for the management of patients with IDH-mutant glioma. J. Clin. Oncol. 34, 4030– 4039 (2016). doi: 10.1200/JCO.2016.67.1222 28248126 PMC5477829 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Lactate export by the cancer cells induces neighboring fibroblasts to secrete hepatocyte growth factor, which activates its receptor tyrosine kinase c-MET on cancer cells. Consequently, the cancer cells sustain oncogenic signaling even in the presence of EGFR inhibitors (111).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [111] Apicella M, Increased lactate secretion by cancer cells sustains non-cell-autonomous adaptive resistance to MET and EGFR targeted therapies. Cell Metab. 28, 848– 865.e6 (2018). doi: 10.1016/j.cmet.2018.08.006 30174307 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Clinical efficacy of mutant IDH1 and −2 inhibitors has been demonstrated in AML patients, with clinical trials in solid tumors now under way.”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“In chronic lymphocytic leukemia, acquired resistance to venetoclax–an inhibitor of the antiapoptotic protein B cell lymphoma-2 (BCL-2)–involves increased mitochondrial mass and enhanced OXPHOS (114). Inhibiting OXPHOS increases venetoclax sensitivity in culture and in vivo.”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [114] Guièze R, Mitochondrial reprogramming underlies resistance to BCL-2 inhibition in lymphoid malignancies. Cancer Cell 36, 369– 384.e13 (2019). doi: 10.1016/j.ccell.2019.08.005 31543463 PMC6801112 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Recent work in cancer metabolism has focused on assessing metabolic phenotypes in native microenvironments in humans and mice. This has produced a greater appreciation for metabolic heterogeneity among tumors, expanding the scope of metabolic dependencies beyond the classical pathways that dominate metabolism in culture.”
§ Metabolic reprogramming and cancer progression > Concluding remarks
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, most metabolic therapies lack biomarkers, and conventional molecular analyses such as DNA and RNA sequencing usually prove to be inadequate surrogates for metabolism.”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Conventional molecular analyses such as DNA and RNA sequencing are inadequate surrogates for metabolism.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Once dormant cells begin to proliferate, anabolic pathways involving biomass assimilation are presumably activated to support progression to macrometastasis (Fig. 3).”
§ Metabolic reprogramming and cancer progression > Metastatic cancer
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“In addition to its epigenetic effects, D-2HG inhibits enzymes from the canonical metabolic network (104). Such enzymes include transaminases that produce glutamate for glutathione biosynthesis, rendering IDH-mutant gliomas susceptible to treatments that deplete glutamate and enhance oxidative stress (105).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [104] Lu C, IDH mutation impairs histone demethylation and results in a block to cell differentiation. Nature 483, 474– 478 (2012). doi: 10.1038/nature10860 22343901 PMC3478770 source
- Not checked yetcites [105] McBrayer SK, Transaminase inhibition by 2-hydroxyglutarate impairs glutamate biosynthesis and redox homeostasis in glioma. Cell 175, 101– 116.e25 (2018). doi: 10.1016/j.cell.2018.08.038 30220459 PMC6219629 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“FH and SDH mutations also create truncal metabolic aberrations. These mutations induce permanent restructuring of the TCA cycle and result in numerous metabolic liabilities in preclinical models (106–108).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [106] Frezza C, Haem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase. Nature 477, 225– 228 (2011). doi: 10.1038/nature10363 21849978 source
- Not checked yetcites [107] Lussey-Lepoutre C, Loss of succinate dehydrogenase activity results in dependency on pyruvate carboxylation for cellular anabolism. Nat. Commun. 6, 8784 (2015). doi: 10.1038/ncomms9784 26522426 PMC4632646 source
- Not checked yetcites [108] Adam J, A role for cytosolic fumarate hydratase in urea cycle metabolism and renal neoplasia. Cell Rep. 3, 1440– 1448 (2013). doi: 10.1016/j.celrep.2013.04.006 23643539 PMC3675675 source
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In the paper
“Intravenous infusion of 13C-lactate into human non-small-cell lung cancer patients and mice bearing patient-derived melanomas identified tumors with a propensity for future metastasis, which required MCT1-dependent lactate transport in the mice (58, 100).”
§ Metabolic reprogramming and cancer progression > Targeting metabolic liabilities
What the sources say
- Not checked yetcites [58] Faubert B, Lactate metabolism in human lung tumors. Cell 171, 358– 371.e9 (2017). doi: 10.1016/j.cell.2017.09.019 28985563 PMC5684706 source
- Not checked yetcites [100] Tasdogan A, Metabolic heterogeneity confers differences in melanoma metastatic potential. Nature 577, 115– 120 (2020). doi: 10.1038/s41586-019-1847-2 31853067 PMC6930341 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper relies on this without support.
Death from cancer is determined largely by metastasis rather than by localized growth of the primary tumor.
“Death from cancer is determined largely by metastasis rather than localized tumor growth at the primary site.”
The paper relies on this without support.
Metabolic reprogramming is a hallmark of malignancy.
“Metabolic reprogramming is a hallmark of malignancy first recognized a century ago.”
The paper relies on this without support.
Tumor cells require many of the same pathways and adaptations available to nonmalignant tissues, so few metabolic activities are truly confined to tumors.
“First, tumor cells require many of the same pathways and adaptations available to nonmalignant tissues, indicating that few metabolic activities are truly confined to tumors.”
The paper relies on this without support.
Glutamine addiction is a common feature of cultured cancer cells.
“Glutamine addiction is a common feature of cultured cancer cells”
The paper relies on this without support.
Conventional molecular analyses such as DNA and RNA sequencing are inadequate surrogates for metabolism.
“conventional molecular analyses such as DNA and RNA sequencing usually prove to be inadequate surrogates for metabolism.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This could be explained by the fact that loss of LKB1 sustains KRAS-mediated proliferation through autophagy and increased synthesis of essential macromolecules, even under nutrient-deprived conditions68.”
From The metabolic landscape of RAS-driven cancers from biology to therapy (2021) · cites this paper as [68]
In the citing paper
“Both hallmarks exhibit clear commonalities, but there are also some differences or even antagonisms between aging-associated deregulated nutrient sensing and cancer-associated deregulation of cellular energy metabolism.[204][205][206]”
From Meta-hallmarks of aging and cancer (2023) · cites this paper as [205]
In the citing paper
“In non-transformed cells of well-oxygenated tissues and even in tumor cells which are located near to blood vessels, an oxidative phenotype, the reverse utilization of lactic acid (reverse Warburg effect) can be observed [36].”
From Hypoxia Signaling in Cancer: From Basics to Clinical Practice (2021) · cites this paper as [36]
Citations
Cites
1 retracted
Zhang, H., Wong, C. C. L., Wei, H., Gilkes, D. M., Korangath, P., Chaturvedi, P., Schito, L., Chen, J., Krishnamachary, B., Winnard, P. T., et al. (2012) · Oncogene · doi:10.1038/onc.2011.365 · Cited by 326
RetractedUnderstanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation
Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009) · Science · doi:10.1126/science.1160809 · Cited by 16,197
Nishimura, R., Osako, T., Nishiyama, Y., Tashima, R., Nakano, M., Fujisue, M., Toyozumi, Y., & Arima, N. (2013) · Oncology · doi:10.1159/000353099 · Cited by 13,239
Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
Gerlinger, M., Rowan, A. J., Horswell, S., Larkin, J., Endesfelder, D., Gronroos, E., Martinez, P., Matthews, N., Stewart, A., Tarpey, P., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1113205 · Cited by 7,774 · cited 1×
“In ccRCC, sequencing multiple regions of primary tumors revealed that most somatically acquired mutations are not present in all areas (57).”
BackgroundOverweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. Adults
Calle, E. E., Rodriguez, C., Walker-Thurmond, K., & Thun, M. J. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa021423 · Cited by 7,696
mTOR Signaling in Growth, Metabolism, and Disease
Saxton, R. A., & Sabatini, D. M. (2017) · Cell · doi:10.1016/j.cell.2017.02.004 · Cited by 7,555
The emerging hallmarks of cancer metabolism
Pavlova, N. N., & Thompson, C. B. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2015.12.006 · Cited by 5,926 · cited 1×
“A central concept in cancer metabolism is that malignant cells acquire an enhanced ability to feed themselves by activating nutrient uptake mechanisms (33).”
BackgroundGerm Line p53 Mutations in a Familial Syndrome of Breast Cancer, Sarcomas, and Other Neoplasms
Malkin, D., Li, F. P., Strong, L. C., Fraumeni, J. F., Nelson, C. E., Kim, D. H., Kassel, J., Gryka, M. A., Bischoff, F. Z., Tainsky, M. A., et al. (1990) · Science · doi:10.1126/science.1978757 · Cited by 3,765
Body Fatness and Cancer — Viewpoint of the IARC Working Group
Lauby-Secretan, B., Scoccianti, C., Loomis, D., Grosse, Y., Bianchini, F., & Straif, K. (2016) · New England Journal of Medicine · doi:10.1056/nejmsr1606602 · Cited by 3,596
Isolation of rare circulating tumour cells in cancer patients by microchip technology
Nagrath, S., Sequist, L. V. D., Maheswaran, S., Bell, D. W., Irimia, D., Ulkus, L., Smith, M. R., Kwak, E. L., Digumarthy, S. R., Muzikansky, A., et al. (2007) · Nature · doi:10.1038/nature06385 · Cited by 3,595
Fundamentals of Cancer Metabolism
DeBerardinis, R. J., & Chandel, N. S. (2016) · Science Advances · doi:10.1126/sciadv.1600200 · Cited by 3,013
Self-citationFigueroa, M. E., Abdel-Wahab, O., Lu, C., Ward, P. S., Patel, J., Shih, A., Li, Y., Bhagwat, N., Vasanthakumar, A., Fernandez, H. F., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.11.015 · Cited by 2,766
Hoadley, K. A., Yau, C., Hinoue, T., Wolf, D. M., Lazar, A. J., Drill, E., Shen, R., Taylor, A. M., Cherniack, A. D., Thorsson, V., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.022 · Cited by 2,546 · cited 1×
“A study that classified thousands of human tumors found that tissue of origin was a major factor defining DNAmethylation and gene expression patterns (3).”
BackgroundAdipocytes promote ovarian cancer metastasis and provide energy for rapid tumor growth
Nieman, K. M., Kenny, H. A., Penicka, C. V., Ladanyi, A., Buell-Gutbrod, R., Zillhardt, M. R., Romero, I. L., Carey, M. S., Mills, G. B., Hotamisligil, G. S., et al. (2011) · Nature Medicine · doi:10.1038/nm.2492 · Cited by 2,279
Gao, P., Tchernyshyov, I., Chang, T.-C., Lee, Y.-S., Kita, K., Ochi, T., Zeller, K. I., De Marzo, A. M., Van Eyk, J. E., Mendell, J. T., et al. (2009) · Nature · doi:10.1038/nature07823 · Cited by 2,124
mTOR Signaling in Growth, Metabolism, and Disease
Saxton, R. A., & Sabatini, D. M. (2017) · Cell · doi:10.1016/j.cell.2017.03.035 · Cited by 2,112
Succinate links TCA cycle dysfunction to oncogenesis by inhibiting HIF-α prolyl hydroxylase
Selak, M. A., Armour, S. M., MacKenzie, E. D., Boulahbel, H., Watson, D. G., Mansfield, K. D., Pan, Y., Simon, M. C., Thompson, C. B., & Gottlieb, E. (2005) · Cancer Cell · doi:10.1016/j.ccr.2004.11.022 · Cited by 2,108 · cited 1×
“Metabolite accumulation in the setting of dysfunctional mitochondria can inhibit VHL-dependent degradation of hypoxia-inducible factor-a (HIF-a) subunits, creating a pseudohypoxic state that mimics VHL loss (14).”
BackgroundMetastatic colonization by circulating tumour cells
Massagué, J., & Obenauf, A. C. (2016) · Nature · doi:10.1038/nature17038 · Cited by 2,062
Oncogenic Kras maintains pancreatic tumors through regulation of anabolic glucose metabolism
Ying, H., Kimmelman, A. C., Lyssiotis, C. A., Hua, S., Chu, G. C., Fletcher-Sananikone, E., Locasale, J. W., Son, J., Zhang, H., Coloff, J. L., et al. (2012) · Cell · doi:10.1016/j.cell.2012.01.058 · Cited by 2,043
TIGAR, a p53-Inducible Regulator of Glycolysis and Apoptosis
Bensaad, K., Tsuruta, A., Selak, M. A., Vidal, M. N. C., Nakano, K., Bartrons, R., Gottlieb, E., & Vousden, K. H. (2006) · Cell · doi:10.1016/j.cell.2006.05.036 · Cited by 2,019
IDH mutation impairs histone demethylation and results in a block to cell differentiation
Lu, C., Ward, P. S., Kapoor, G. S., Rohle, D., Turcan, S., Abdel-Wahab, O., Edwards, C. R., Khanin, R., Figueroa, M. E., Melnick, A., et al. (2012) · Nature · doi:10.1038/nature10860 · Cited by 1,985
IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype
Turcan, S., Rohle, D., Goenka, A., Walsh, L. A., Fang, F., Yilmaz, E., Campos, C., Fabius, A. W. M., Lu, C., Ward, P. S., et al. (2012) · Nature · doi:10.1038/nature10866 · Cited by 1,974
Drug-tolerant persister cancer cells are vulnerable to GPX4 inhibition
Hangauer, M. J., Viswanathan, V. S., Ryan, M. J., Bole, D., Eaton, J. K., Matov, A., Galeas, J., Dhruv, H. D., Berens, M. E., Schreiber, S. L., et al. (2017) · Nature · doi:10.1038/nature24297 · Cited by 1,799
Macropinocytosis of protein is an amino acid supply route in Ras-transformed cells
Commisso, C., Davidson, S. M., Soydaner-Azeloglu, R. G., Parker, S. J., Kamphorst, J. J., Hackett, S., Grabocka, E., Nofal, M., Drebin, J. A., Thompson, C. B., et al. (2013) · Nature · doi:10.1038/nature12138 · Cited by 1,683
Mutations in SDHD , a Mitochondrial Complex II Gene, in Hereditary Paraganglioma
Baysal, B. E., Ferrell, R. E., Willett-Brozick, J. E., Lawrence, E. C., Myssiorek, D., Bosch, A., Mey, A. V. D., Taschner, P. E. M., Rubinstein, W. S., Myers, E. N., et al. (2000) · Science · doi:10.1126/science.287.5454.848 · Cited by 1,638
The Multiple Leiomyoma Consortium (2002) · Nature Genetics · doi:10.1038/ng849 · Cited by 1,635
Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice
Sonveaux, P., Végran, F., Schroeder, T., Wergin, M., Verrax, J., Rabbani, Z. N., Saedeleer, C. J. D., Kennedy, K. M., Diepart, C., Jordan, B. F., et al. (2008) · Journal of Clinical Investigation · doi:10.1172/jci36843 · Cited by 1,635
Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia
Stein, E. M., DiNardo, C. D., Pollyea, D. A., Fathi, A. T., Roboz, G. J., Altman, J. K., Stone, R. M., DeAngelo, D. J., Levine, R. L., Flinn, I. W., et al. (2017) · Blood · doi:10.1182/blood-2017-04-779405 · Cited by 1,516
Targeting metastasis-initiating cells through the fatty acid receptor CD36
Pascual, G., Avgustinova, A., Mejetta, S., Martín, M., Castellanos‐Martín, A., Attolini, C. S., Berenguer, A., Prats, N., Toll, A., Hueto-Madrid, J. A., et al. (2016) · Nature · doi:10.1038/nature20791 · Cited by 1,477
ROS-Generating Mitochondrial DNA Mutations Can Regulate Tumor Cell Metastasis
Ishikawa, K., Takenaga, K., Akimoto, M., Koshikawa, N., Yamaguchi, A., Imanishi, H., Nakada, K., Honma, Y., & Hayashi, J.-I. (2008) · Science · doi:10.1126/science.1156906 · Cited by 1,444
LeBleu, V. S., O’Connell, J. T., Herrera, K. N. G., Wikman, H., Pantel, K., Haigis, M. C., de Carvalho, F. M., Damascena, A. S., Chinen, L. T. D., Rocha, R. M., et al. (2014) · Nature Cell Biology · doi:10.1038/ncb3039 · Cited by 1,438
Lactate Metabolism in Human Lung Tumors
Faubert, B., Li, K. Y., Cai, L., Hensley, C. T., Kim, J., Zacharias, L. G., Yang, C., Do, Q. N., Doucette, S., Burguete, D., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.019 · Cited by 1,343
Self-citationHIF-1 mediates metabolic responses to intratumoral hypoxia and oncogenic mutations
Semenza, G. L. (2013) · Journal of Clinical Investigation · doi:10.1172/jci67230 · Cited by 1,335
Metabolic Imaging of Patients with Prostate Cancer Using Hyperpolarized [1- 13 C]Pyruvate
Nelson, S. J., Kurhanewicz, J. V., Vigneron, D. B., Larson, P. E. Z., Harzstark, A. L., Ferrone, M., Criekinge, M. V., Chang, J. W., Bok, R., Park, I., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3006070 · Cited by 1,289
Oxidative stress inhibits distant metastasis by human melanoma cells
Piskounova, E., Agathocleous, M., Murphy, M. M., Hu, Z., Huddlestun, S. E., Zhao, Z., Leitch, A. M., Johnson, T. M., DeBerardinis, R. J., & Morrison, S. J. (2015) · Nature · doi:10.1038/nature15726 · Cited by 1,269
Self-citationOncogene ablation-resistant pancreatic cancer cells depend on mitochondrial function
Viale, A., Pettazzoni, P., Lyssiotis, C. A., Ying, H., Sánchez, N., Marchesini, M., Carugo, A., Green, T., Seth, S., Giuliani, V., et al. (2014) · Nature · doi:10.1038/nature13611 · Cited by 1,259
Multistep Nature of Metastatic Inefficiency
Luzzi, K. J., MacDonald, I. C., Schmidt, E. E., Kerkvliet, N. I., Morris, V. L., Chambers, A. F., & Groom, A. C. (1998) · American Journal Of Pathology · doi:10.1016/s0002-9440(10)65628-3 · Cited by 1,246
Glutamine blockade induces divergent metabolic programs to overcome tumor immune evasion
Leone, R. D., Zhao, L., Englert, J. M., Sun, I.-M., Oh, M.-H., Sun, I.-H., Arwood, M. L., Bettencourt, I. A., Patel, C. H., Wen, J., et al. (2019) · Science · doi:10.1126/science.aav2588 · Cited by 1,169 · cited 1×
“But a recent DON analog, JHU083, is a prodrug that is activated in the tumor microenvironment, improving the therapeutic window (118).”
BackgroundMetabolic heterogeneity in human lung tumors
Hensley, C. T., Faubert, B., Yuan, Q., Lev-Cohain, N., Jin, E., Kim, J., Jiang, L., Ko, B., Skelton, R., Loudat, L., et al. (2016) · Cell · doi:10.1016/j.cell.2015.12.034 · Cited by 1,138
Self-citationPancreatic stellate cells support tumour metabolism through autophagic alanine secretion
Sousa, C. M., Biancur, D. E., Wang, X., Halbrook, C. J., Sherman, M. H., Zhang, L., Kremer, D., Hwang, R. F., Witkiewicz, A. K., Ying, H., et al. (2016) · Nature · doi:10.1038/nature19084 · Cited by 1,122
c-Myc transactivation of LDH-A : Implications for tumor metabolism and growth
Shim, H., Dolde, C., Lewis, B. C., Wu, C.-S., Dang, G., Jungmann, R. A., Dalla-Favera, R., & Dang, C. V. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.13.6658 · Cited by 1,092
LKB1 modulates lung cancer differentiation and metastasis
Ji, H., Ramsey, M. R., Hayes, D. N., Fan, C., McNamara, K., Kozlowski, P., Torrice, C., Wu, M. C., Shimamura, T., Perera, S. A., et al. (2007) · Nature · doi:10.1038/nature06030 · Cited by 1,064
Baccelli, I., Schneeweiß, A., Riethdorf, S., Stenzinger, A., Schillert, A., Vogel, V., Klein, C., Saini, M., Bäuerle, T., Wallwiener, M., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2576 · Cited by 1,050
Antioxidant and oncogene rescue of metabolic defects caused by loss of matrix attachment
Schafer, Z. T., Grassian, A. R., Song, L., Jiang, Z., Gerhart-Hines, Z., Irie, H. Y., Gao, S., Puigserver, P., & Brugge, J. S. (2009) · Nature · doi:10.1038/nature08268 · Cited by 1,031
Skoulidis, F., Byers, L. A., Diao, L., Papadimitrakopoulou, V. A., Tong, P., Izzo, J., Behrens, C., Kadara, H., Parra, E. R., Canales, J. R., et al. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-1236 · Cited by 936
An inhibitor of oxidative phosphorylation exploits cancer vulnerability
Molina, J. R., Sun, Y., Protopopova, M., Gera, S., Bandi, M., Bristow, C., McAfoos, T., Morlacchi, P., Ackroyd, J., Agip, A.-N. A., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0052-4 · Cited by 928
Glucose Deprivation Contributes to the Development of KRAS Pathway Mutations in Tumor Cells
Yun, J., Rago, C., Cheong, I., Pagliarini, R., Angenendt, P., Rajagopalan, H., Schmidt, K., Willson, J. K. V., Markowitz, S., Zhou, S., et al. (2009) · Science · doi:10.1126/science.1174229 · Cited by 914
Farge, T., Saland, E., de Toni, F., Aroua, N., Hosseini, M., Perry, R., Bosc, C., Sugita, M., Stuani, L., Fraisse, M., et al. (2017) · Cancer Discovery · doi:10.1158/2159-8290.cd-16-0441 · Cited by 912
Kamphorst, J. J., Nofal, M., Commisso, C., Hackett, S. R., Lu, W., Grabocka, E., Vander Heiden, M. G., Miller, G., Drebin, J. A., Bar-Sagi, D., et al. (2015) · Cancer Research · doi:10.1158/0008-5472.can-14-2211 · Cited by 893
Antioxidants Accelerate Lung Cancer Progression in Mice
Sayin, V. I., Ibrahim, M. X., Larsson, E., Nilsson, J. A., Lindahl, P., & Bergo, M. O. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3007653 · Cited by 867
Subtypes of Breast Cancer Show Preferential Site of Relapse
Smid, M., Wang, Y., Zhang, Y., Sieuwerts, A. M., Yu, J. X., Klijn, J. G. M., Foekens, J. A., & Martens, J. W. M. (2008) · Cancer Research · doi:10.1158/0008-5472.can-07-5644 · Cited by 827
Metastatic Latency and Immune Evasion through Autocrine Inhibition of WNT
Malladi, S., Macalinao, D. G., Jin, X., He, L., Basnet, H., Zou, Y., de Stanchina, E., & Massagué, J. (2016) · Cell · doi:10.1016/j.cell.2016.02.025 · Cited by 791
Tumor metastasis: moving new biological insights into the clinic
Wan, L., Pantel, K., & Kang, Y. (2013) · Nature Medicine · doi:10.1038/nm.3391 · Cited by 763
Suppression of insulin feedback enhances the efficacy of PI3K inhibitors
Hopkins, B. D., Pauli, C., Du, X., Wang, D. G., Li, X., Wu, D., Amadiume, S. C., Goncalves, M. D., Hodakoski, C., Lundquist, M. R., et al. (2018) · Nature · doi:10.1038/s41586-018-0343-4 · Cited by 706 · cited 1×
“the efficacy of PI3K inhibitors on tumor growth (113).”
BackgroundSDH5 , a Gene Required for Flavination of Succinate Dehydrogenase, Is Mutated in Paraganglioma
Hao, H.-X., Khalimonchuk, O., Schraders, M., Dephoure, N., Bayley, J.-P., Kunst, H., Devilee, P., Cremers, C. W. R. J., Schiffman, J. D., Bentz, B. G., et al. (2009) · Science · doi:10.1126/science.1175689 · Cited by 702 · cited 1×
“1016/S0002-9440(10)65628-3; pmid: 9736035”
The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type
Yuneva, M. O., Fan, T. W. M., Allen, T. D., Higashi, R. M., Ferraris, D. V., Tsukamoto, T., Matés, J. M., Alonso, F. J., Wang, C., Seo, Y., et al. (2012) · Cell Metabolism · doi:10.1016/j.cmet.2011.12.015 · Cited by 639
Antioxidants can increase melanoma metastasis in mice
Le Gal, K., Ibrahim, M. X., Wiel, C., Sayin, V. I., Akula, M. K., Karlsson, C., Dalin, M. G., Akyürek, L. M., Lindahl, P., Nilsson, J., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aad3740 · Cited by 632
Mechanisms and Implications of Metabolic Heterogeneity in Cancer
Kim, J., & DeBerardinis, R. J. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.08.013 · Cited by 606
Self-citationThe Two Faces of Reactive Oxygen Species in Cancer
Reczek, C. R., & Chandel, N. S. (2017) · Annual Review of Cancer Biology · doi:10.1146/annurev-cancerbio-041916-065808 · Cited by 602 · cited 1×
“The exact role of ROS may depend on the stage and type of cancer (85).”
BackgroundShackelford, D. B., Abt, E., Gerken, L., Vasquez, D. S., Seki, A., Leblanc, M., Wei, L., Fishbein, M. C., Czernin, J., Mischel, P. S., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2012.12.008 · Cited by 585
Reductive carboxylation supports redox homeostasis during anchorage-independent growth
Jiang, L., Shestov, A. A., Swain, P., Yang, C., Parker, S. J., Wang, Q. A., Terada, L. S., Adams, N. D., McCabe, M. T., Pietrak, B., et al. (2016) · Nature · doi:10.1038/nature17393 · Cited by 582
Self-citationBACH1 Stabilization by Antioxidants Stimulates Lung Cancer Metastasis
Wiel, C., Le Gal, K., Ibrahim, M. X., Jahangir, C. A., Kashif, M., Yao, H., Ziegler, D. V., Xu, X., Ghosh, T., Mondal, T., et al. (2019) · Cell · doi:10.1016/j.cell.2019.06.005 · Cited by 579
Nrf2 Activation Promotes Lung Cancer Metastasis by Inhibiting the Degradation of Bach1
Lignitto, L., LeBoeuf, S. E., Homer, H., Jiang, S., Askenazi, M., Karakousi, T. R., Pass, H. I., Bhutkar, A. J., Tsirigos, A., Ueberheide, B., et al. (2019) · Cell · doi:10.1016/j.cell.2019.06.003 · Cited by 573
A Mitochondrial Switch Promotes Tumor Metastasis
Porporato, P. E., Payen, V. L., Pérez‐Escuredo, J., Saedeleer, C. J. D., Danhier, P., Copetti, T., Dhup, S., Tardy, M., Vazeille, T., Bouzin, C., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.06.043 · Cited by 571
Vanharanta, S., & Massagué, J. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.09.007 · Cited by 563
Autophagy is required for glucose homeostasis and lung tumor maintenance
Karsli-Uzunbas, G., Guo, J. Y., Price, S., Teng, X., Laddha, S. V., Khor, S., Kalaany, N. Y., Jacks, T., Chan, C. S., Rabinowitz, J. D., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-0363 · Cited by 560
PDK1-Dependent Metabolic Reprogramming Dictates Metastatic Potential in Breast Cancer
Dupuy, F., Tabariès, S., Andrzejewski, S., Dong, Z., Blagih, J., Annis, M. G., Omeroglu, A., Gao, D., Leung, S., Amir, E., et al. (2015) · Cell Metabolism · doi:10.1016/j.cmet.2015.08.007 · Cited by 558
Stott, S. L., Lee, R. J., Nagrath, S., Yu, M., Miyamoto, D. T., Ulkus, L., Inserra, E. K., Ulman, M. J., Springer, S. U., Nakamura, Z. M., et al. (2010) · Science Translational Medicine · doi:10.1126/scitranslmed.3000403 · Cited by 548
Metabolic Regulation of T Cell Longevity and Function in Tumor Immunotherapy
Kishton, R. J., Sukumar, M., & Restifo, N. P. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.06.016 · Cited by 548
Asparagine bioavailability governs metastasis in a model of breast cancer
Knott, S., Wagenblast, E., Khan, S., Kim, S. Y., Soto, M., Wagner, M., Turgeon, M., Fish, L., Erard, N., Gable, A. L., et al. (2018) · Nature · doi:10.1038/nature25465 · Cited by 539
Metastatic Patterns of Cancers: Results From a Large Autopsy Study
diSibio, G., & French, S. W. (2008) · Archives of Pathology & Laboratory Medicine · doi:10.5858/2008-132-931-mpocrf · Cited by 527
The landscape of cancer cell line metabolism
Li, H., Ning, S., Ghandi, M., Kryukov, G. V., Gopal, S., Deik, A., Souza, A., Pierce, K. A., Keskula, P., Hernandez, D., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0404-8 · Cited by 511
Metabolic heterogeneity confers differences in melanoma metastatic potential
Tasdogan, A., Faubert, B., Ramesh, V., Ubellacker, J. M., Shen, B., Solmonson, A., Murphy, M. M., Gu, Z., Gu, W., Martin, M., et al. (2020) · Nature · doi:10.1038/s41586-019-1847-2 · Cited by 509
Self-citationHaem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase
Frezza, C., Zheng, L., Folger, O., Rajagopalan, K. N., MacKenzie, E. D., Jerby, L., Micaroni, M., Chaneton, B., Adam, J., Hedley, A., et al. (2011) · Nature · doi:10.1038/nature10363 · Cited by 503
Self-citationA murine lung cancer co-clinical trial identifies genetic modifiers of therapeutic response
Chen, Z., Cheng, K., Walton, Z., Wang, Y., Ebi, H., Shimamura, T., Liu, Y., Tupper, T., Ouyang, J., Li, J., et al. (2012) · Nature · doi:10.1038/nature10937 · Cited by 446
Macrophage-Released Pyrimidines Inhibit Gemcitabine Therapy in Pancreatic Cancer
Halbrook, C. J., Pontious, C., Kovalenko, I., Lapienyte, L., Dreyer, S., Lee, H.-J., Thurston, G., Zhang, Y., Lazarus, J., Sajjakulnukit, P., et al. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.02.001 · Cited by 419
Acid production in glycolysis-impaired tumors provides new insights into tumor metabolism.
Helmlinger, G., Sckell, A., Dellian, M., Forbes, N. S., & Jain, R. K. (2002) · PubMed · Cited by 417
Tumor metastasis to lymph nodes requires YAP-dependent metabolic adaptation
Lee, C., Jeong, S., Jang, C., Bae, H., Kim, Y. H., Park, I., Kim, S. K., & Koh, G. Y. (2019) · Science · doi:10.1126/science.aav0173 · Cited by 408
Heterogeneity of tumor-induced gene expression changes in the human metabolic network
Hu, J., Locasale, J. W., Bielas, J. H., O'Sullivan, J., Sheahan, K., Cantley, L. C., Heiden, M. G. V., & Vitkup, D. (2013) · Nature Biotechnology · doi:10.1038/nbt.2530 · Cited by 407
Cameron, M. D., Schmidt, E. E., Kerkvliet, N. I., Nadkarni, K. V., Morris, V. L., Groom, A. C., Chambers, A. F., & MacDonald, I. C. (2000) · PubMed · Cited by 400
McBrayer, S. K., Mayers, J. R., DiNatale, G. J., Shi, D. D., Khanal, J., Chakraborty, A. A., Sarosiek, K. A., Briggs, K. J., Robbins, A. K., Sewastianik, T., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.038 · Cited by 368
NUFIP1 is a ribosome receptor for starvation-induced ribophagy
Wyant, G. A., Abu-Remaileh, M., Frenkel, E. M., Laqtom, N. N., Dharamdasani, V., Lewis, C. A., Chan, S. H., Heinze, I., Ori, A., & Sabatini, D. M. (2018) · Science · doi:10.1126/science.aar2663 · Cited by 363
Mitochondrial Reprogramming Underlies Resistance to BCL-2 Inhibition in Lymphoid Malignancies
Guièze, R., Liu, V. M., Rosebrock, D., Jourdain, A. A., Hernández-Sánchez, M., Martinez Zurita, A., Sun, J., Ten Hacken, E., Baranowski, K., Thompson, P. A., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.08.005 · Cited by 361
LKB1 loss links serine metabolism to DNA methylation and tumorigenesis
Kottakis, F., Nicolay, B. N., Roumane, A., Karnik, R., Gu, H., Nagle, J. M., Boukhali, M., Hayward, M. C., Li, Y. Y., Chen, T., et al. (2016) · Nature · doi:10.1038/nature20132 · Cited by 348
Naumov, G. N., MacDonald, I. C., Weinmeister, P. M., Kerkvliet, N. I., Nadkarni, K. V., Wilson, S. M., Morris, V. L., Groom, A. C., & Chambers, A. F. (2002) · PubMed · Cited by 341
Phosphatidylinositol 3-kinase, growth disorders, and cancer
Goncalves, M. D., Hopkins, B. D., & Cantley, L. C. (2018) · New England Journal of Medicine · doi:10.1056/nejmra1704560 · Cited by 327
Glutamine-based PET imaging facilitates enhanced metabolic evaluation of gliomas in vivo
Venneti, S., Dunphy, M. P., Zhang, H., Pitter, K. L., Zanzonico, P., Campos, C., Carlin, S., Rocca, G. L., Lyashchenko, S. K., Plöessl, K., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aaa1009 · Cited by 326
CPS1 maintains pyrimidine pools and DNA synthesis in KRAS/LKB1-mutant lung cancer cells
Kim, J., Hu, Z., Cai, L., Li, K., Choi, E., Faubert, B., Bezwada, D., Rodriguez-Canales, J., Villalobos, P., Lin, Y.-F., et al. (2017) · Nature · doi:10.1038/nature22359 · Cited by 325
Self-citationGboxin is an oxidative phosphorylation inhibitor that targets glioblastoma
Shi, Y., Lim, S. K., Liang, Q., Iyer, S. V., Wang, H.-Y., Wang, Z., Xie, X., Sun, D., Chen, Y.-J., Tabar, V., et al. (2019) · Nature · doi:10.1038/s41586-019-0993-x · Cited by 325
Molecular Profiling Reveals Unique Immune and Metabolic Features of Melanoma Brain Metastases
Fischer, G. M., Jalali, A., Kircher, D. A., Lee, W., McQuade, J. L., Haydu, L. E., Joon, A. Y., Reuben, A., de Macêdo, M. P., Carapeto, F. C. L., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-1489 · Cited by 324
Self-citationPark, J. H., Vithayathil, S. A., Kumar, S., Sung, P., Dobrolecki, L. E., Putluri, V., Bhat, V. B., Bhowmik, S. K., Gupta, V. K., Arora, K., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.02.004 · Cited by 316
Acetyl-CoA Metabolism Supports Multistep Pancreatic Tumorigenesis
Carrer, A., Trefely, S., Zhao, S., Campbell, S. L., Norgard, R. J., Schultz, K. C., Sidoli, S., Parris, J. L. D., Affronti, H. C., Sivanand, S., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-0567 · Cited by 313
The landscape of metastatic progression patterns across major human cancers
Budczies, J., von Winterfeld, M., Klauschen, F., Bockmayr, M. L., Lennerz, J. K., Denkert, C., Wolf, T. A., Warth, A., Dietel, M., Anagnostopoulos, I., et al. (2014) · Oncotarget · doi:10.18632/oncotarget.2677 · Cited by 311
Breast cancer cells rely on environmental pyruvate to shape the metastatic niche
Elia, I., Rossi, M., Stegen, S., Broekaert, D., Doglioni, G., van Gorsel, M., Boon, R., Escalona‐Noguero, C., Torrekens, S., Verfaillie, C. M., et al. (2019) · Nature · doi:10.1038/s41586-019-0977-x · Cited by 311
Apicella, M., Giannoni, E., Fiore, S., Ferrari, K. J., Fernández-Pérez, D., Isella, C., Granchi, C., Minutolo, F., Sottile, A., Comoglio, P. M., et al. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.08.006 · Cited by 299
Galan-Cobo, A., Sitthideatphaiboon, P., Qu, X., Poteete, A., Pisegna, M. A., Tong, P., Chen, P.-H., Boroughs, L. K., Rodriguez, M. L. M., Zhang, W., et al. (2019) · Cancer Research · doi:10.1158/0008-5472.can-18-3527 · Cited by 292
Self-citationApoptosis: an early event in metastatic inefficiency.
Wong, C. W., Lee, A., Shientag, L., Yu, J. H., Dong, Y., Kao, G., Al‐Mehdi, A. B., Bernhard, E. J., & Muschel, R. J. (2001) · PubMed · Cited by 276
Liou, G.-Y., Döppler, H., DelGiorno, K. E., Zhang, L., Leitges, M., Crawford, H. C., Murphy, M. P., & Storz, P. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.02.029 · Cited by 270
Hu, S., Balakrishnan, A., Bok, R. A., Anderton, B., Larson, P. E. Z., Nelson, S. J., Kurhanewicz, J., Vigneron, D. B., & Goga, A. (2011) · Cell Metabolism · doi:10.1016/j.cmet.2011.04.012 · Cited by 245
Lussey-Lepoutre, C., Hollinshead, K. E. R., Ludwig, C., Menara, M., Morin, A., Castro-Vega, L.-J., Parker, S. J., Janin, M., Martinelli, C., Ottolenghi, C., et al. (2015) · Nature Communications · doi:10.1038/ncomms9784 · Cited by 227
UDP-glucose accelerates SNAI1 mRNA decay and impairs lung cancer metastasis
Wang, X., Liu, R., Zhu, W., Chu, H., Yu, H. T., Wei, P., Wu, X., Zhu, H., Gao, H., Liang, J., et al. (2019) · Nature · doi:10.1038/s41586-019-1340-y · Cited by 215
In vivo imaging of mitochondrial membrane potential in non-small-cell lung cancer
Momcilovic, M., Jones, A., Bailey, S. T., Waldmann, C. M., Li, R., Lee, J. T., Abdelhady, G., Gomez, A., Holloway, T., Schmid, E., et al. (2019) · Nature · doi:10.1038/s41586-019-1715-0 · Cited by 214
Sulkowski, P. L., Sundaram, R. K., Oeck, S., Corso, C. D., Liu, Y., Noorbakhsh, S., Niger, M., Boeke, M., Ueno, D., Kalathil, A. N., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0170-4 · Cited by 213
Metabolic Diversity in Human Non-Small Cell Lung Cancer Cells
Chen, P.-H., Cai, L., Huffman, K. E., Yang, C., Kim, J., Faubert, B., Boroughs, L. K., Ko, B., Sudderth, J., McMillan, E. A., et al. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.08.028 · Cited by 209
Self-citationChoi, C., Raisanen, J. M., Ganji, S. K., Zhang, S., McNeil, S. S., An, Z., Madan, A., Hatanpaa, K. J., Vemireddy, V., Sheppard, C. A., et al. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2016.67.1222 · Cited by 201
Kim, S. M., Nguyen, T. T., Ravi, A., Kubiniok, P., Finicle, B. T., Jayashankar, V., Malacrida, L., Hou, J., Robertson, J., Gao, D., et al. (2018) · Cancer Discovery · doi:10.1158/2159-8290.cd-17-1215 · Cited by 199
Scafoglio, C. R., Villegas, B., Abdelhady, G., Bailey, S. T., Liu, J., Shirali, A. S., Wallace, W. D., Magyar, C. E., Grogan, T. R., Elashoff, D., et al. (2018) · Science Translational Medicine · doi:10.1126/scitranslmed.aat5933 · Cited by 176
Labbé, D. P., Zadra, G., Yang, M., Reyes, J. M., Lin, C. Y., Cacciatore, S., Ebot, E. M., Creech, A. L., Giunchi, F., Fiorentino, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12298-z · Cited by 174
Loss of EZH2 Reprograms BCAA Metabolism to Drive Leukemic Transformation
Gu, Z., Liu, Y., Cai, F., Patrick, M., Zmajkovic, J., Cao, H., Zhang, Y., Tasdogan, A., Chen, M., Qi, L., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-19-0152 · Cited by 173
Self-citationValvezan, A. J., Turner, M., Belaïd, A., Lam, H. C., Miller, S. K., McNamara, M. C., Baglini, C. V., Housden, B. E., Perrimon, N., Kwiatkowski, D. J., et al. (2017) · Cancer Cell · doi:10.1016/j.ccell.2017.09.013 · Cited by 163
Liu, Y., Marks, K. M., Cowley, G. S., Carretero, J., Liu, Q., Nieland, T. J. F., Xu, C., Cohoon, T. J., Gao, P., Zhang, Y., et al. (2013) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0015 · Cited by 152
Phillips, C. M., Zatarain, J. R., Nicholls, M. E., Porter, C., Widen, S. G., Thanki, K., Johnson, P., Jawad, M. U., Moyer, M. P., Randall, J. W., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-3480 · Cited by 139
Granlund, K. L., Tee, S.-S., Vargas, H. A., Lyashchenko, S. K., Reznik, E., Fine, S., Laudone, V., Eastham, J. A., Touijer, K. A., Reuter, V. E., et al. (2020) · Cell Metabolism · doi:10.1016/j.cmet.2019.08.024 · Cited by 138
Pro-metastatic signaling by c-Met through RAC-1 and reactive oxygen species (ROS)
Ferraro, D. A., Corso, S., Fasano, E., Panieri, E., Santangelo, R., Borrello, S., Giordano, S., Pani, G., & Galeotti, T. (2006) · Oncogene · doi:10.1038/sj.onc.1209409 · Cited by 135
Hu, C.-M., Tien, S.-C., Hsieh, P.-K., Jeng, Y.-M., Chang, M.-C., Chang, Y.-T., Chen, Y.-J., Chen, Y.-J., Lee, E. Y.-H. P., & Lee, W.-H. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.02.005 · Cited by 123
Levine, A. J., Jenkins, N. A., & Copeland, N. G. (2019) · Cancer Cell · doi:10.1016/j.ccell.2018.11.009 · Cited by 121
Calles, A., Sholl, L. M., Rodig, S. J., Pelton, A. K., Hornick, J. L., Butaney, M., Lydon, C., Dahlberg, S. E., Oxnard, G. R., Jackman, D. M., et al. (2015) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-3112 · Cited by 115
Benn, D. E., Croxson, M. S., Tucker, K., Bambach, C. P., Richardson, A. L., Delbridge, L., Pullan, P. T., Hammond, J., Marsh, D. J., & Robinson, B. G. (2003) · Oncogene · doi:10.1038/sj.onc.1206300 · Cited by 108
Metabolic dysregulation in monogenic disorders and cancer — finding method in madness
Erez, A., & DeBerardinis, R. J. (2015) · Nature Reviews Cancer · doi:10.1038/nrc3949 · Cited by 105
Self-citationZhou, R., Pantel, A. R., Li, S., Lieberman, B. P., Plöessl, K., Choi, H., Blankemeyer, E. R., Lee, H. S., Kung, H. F., Mach, R. H., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-1945 · Cited by 99
A role for cytosolic fumarate hydratase in urea cycle metabolism and renal neoplasia
Adam, J., Yang, M., Bauerschmidt, C., Kitagawa, M., O’Flaherty, L., Maheswaran, P., Özkan, G., Sahgal, N., Baban, D., Kato, K., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.04.006 · Cited by 97
Armanios, M. Y., Grossman, S. A., Yang, S. C., White, B., Perry, A., Burger, P. C., & Orens, J. B. (2004) · Neuro-Oncology · doi:10.1215/s1152851703000474 · Cited by 80
Varghese, H. J., Davidson, M. T. M., MacDonald, I. C., Wilson, S. M., Nadkarni, K. V., Groom, A. C., & Chambers, A. F. (2002) · PubMed · Cited by 60
Analyzing Tumor Metabolism In Vivo
Faubert, B., & DeBerardinis, R. J. (2016) · Annual Review of Cancer Biology · doi:10.1146/annurev-cancerbio-050216-121954 · Cited by 44
Self-citationXu, J., Reznik, E., Lee, H.-J., Gundem, G., Jonsson, P., Sarungbam, J., Bialik, A., Sanchez-Vega, F., Creighton, C. J., Hoekstra, J., et al. (2019) · eLife · doi:10.7554/elife.38986 · Cited by 43
Transmission of Glioblastoma Multiforme After Bilateral Lung Transplantation
Chen, H., Shah, A. S., Girgis, R. E., & Grossman, S. A. (2008) · Journal of Clinical Oncology · doi:10.1200/jco.2008.16.3543 · Cited by 42
Backshall, A., Alferez, D., Teichert, F., Wilson, I. D., Wilkinson, R. W., Goodlad, R. A., & Keun, H. C. (2009) · Journal of Proteome Research · doi:10.1021/pr800793w · Cited by 42
Zhou, R., Bagga, P., Nath, K., Hariharan, H., Mankoff, D. A., & Reddy, R. D. (2018) · Cancer Research · doi:10.1158/0008-5472.can-17-3988 · Cited by 27
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Metadata
- Authors
- Faubert, B., Solmonson, A., & DeBerardinis, R. J.
- Affiliations
- Children's Medical Center (US)
- Corresponding author
- Faubert, Brandon
- Solmonson, Ashley
- DeBerardinis, Ralph J.
- Venue
- Science
- Published
- 2020-04-10
- Volume
- 368
- Issue
- 6487
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7227780
- OpenAlex
- W3015450697
- Semantic Scholar
- 3290d4791010bd52ce6a6e7fd0cd47eb3758c274
- Cited by
- 2,740
- References
- 128
- Citations by year
- 2026: 539 · 2025: 664 · 2024: 475 · 2023: 386 · 2022: 370 · 2021: 241 · 2020: 65
- FWCI
- 27.41
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (R35 CA220449)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (F32HD096786)
- Canadian HIV Trials Network, Canadian Institutes of Health Research ((MFE140911)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolism, Diabetes, and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Lipids, and Metabolism
- Keywords
- metabolic reprogramming, cancer metabolism, tumor progression, metabolic heterogeneity, metastasis, primary tumor, cancer therapy
- MeSH terms
- Animals, Humans, Neoplasm Invasiveness, Neoplasm Metastasis, Neoplasms, Precancerous Conditions, Disease Progression, Mice, Molecular Targeted Therapy
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