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
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
0 of 72 cited sources checked · 0 supported · 0 flagged
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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe 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
“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
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
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
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ 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
“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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
- 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
Load-bearingStrength:plain· not yet calibratedTests✓ 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
“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
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
“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
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
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
“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
Flagged first, then by citations
Cited by
Sorted by citations
Items 501–600 of 1,002
Hypoxia-driven metabolic reprogramming of adipocytes fuels cancer cell proliferation
Aird, R., Wills, J. C., Roby, K. F., Bénézech, C., Stimson, R. H., Wabitsch, M., Pollard, J. W., Finch, A. J., & Michailidou, Z. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.989523 · Cited by 29
Dai, T., Rosario, S. R., Katsuta, E., Dessai, A. S., Paterson, E. J., Novickis, A. T., Gomez, E. C., Zhu, B., Liu, S., Wang, H., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111756 · Cited by 29
Liu, Y., Sun, L., Guo, H., Zhou, S., Wang, C., Ji, C., Meng, F., Liang, S., Zhang, B., Yuan, Y., et al. (2022) · Oncogene · doi:10.1038/s41388-022-02551-z · Cited by 29
Wang, W., Zhang, L., Liu, Z., Zhang, Y., Zhu, J., Liu, M., Ren, J., & Qu, X. (2023) · Advanced Materials · doi:10.1002/adma.202211866 · Cited by 29
Boese, A. C., Kang, J., Hwang, J. S., Kim, J. H., Eun, K., Malin, C. M., Magliocca, K. R., Pan, C., Jin, L., & Kang, S. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2217332120 · Cited by 29
Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis
Liu, W., Ma, J., Zhang, J., Cao, J., Hu, X., Huang, Y., Wang, R., Wu, J., Di, W. J., Qian, K., et al. (2024) · EMBO Molecular Medicine · doi:10.1038/s44321-024-00033-1 · Cited by 30
Molecular characterization and clinical relevance of metabolic signature subtypes in gastric cancer
Chen, H. H., Jing, C., Shang, L., Zhu, X., Zhang, R., Liu, Y., Wang, M., Xu, K., Ma, T., Jing, H., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114424 · Cited by 30
Shi, Z., Zeng, Y., Luo, J., Wang, X., Ma, G., Zhang, T., & Huang, P. (2024) · ACS Nano · doi:10.1021/acsnano.4c05938 · Cited by 28
Wang, X. T., Qu, Y., Ji, J., Liu, H., Luo, H., Li, J., & Han, X. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.113470 · Cited by 30
Metabolic reprogramming of neutrophils in the tumor microenvironment: Emerging therapeutic targets
Huang, S., Shi, J., Shen, J., & Fan, X. (2025) · Cancer Letters · doi:10.1016/j.canlet.2025.217466 · Cited by 33
Overcoming cancer treatment resistance: Unraveling the role of cancer-associated fibroblasts
Wang, X., Zhou, Y., Wang, Y., Yang, J., Li, Z., Liu, F. L., Wang, A., Gao, Z., Wu, C. H., & Yin, H. (2025) · Journal of the National Cancer Center · doi:10.1016/j.jncc.2025.03.002 · Cited by 32
Cheng, Y., Liu, B., Xin, J., Wu, X., Li, W., Shang, J., Wu, J., Zhang, Z., Xu, B., Du, M., et al. (2025) · Nature Aging · doi:10.1038/s43587-025-00842-0 · Cited by 29
Tang, Y., Tang, R., Tang, M., Huang, P., Liao, Z., Zhou, J., Zhou, L., Su, M., Chen, P., Jiang, J., et al. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2020.604534 · Cited by 28
Glutamine anaplerosis is required for amino acid biosynthesis in human meningiomas
Ijare, O. B., Hambarde, S., da Costa, F. H. B., Lopez, S., Sharpe, M. A., Helekar, S. A., Hangel, G. J., Bogner, W., Widhalm, G., Bachoo, R. M., et al. (2021) · Neuro-Oncology · doi:10.1093/neuonc/noab219 · Cited by 28
Metabolic reprogramming in the arsenic carcinogenesis
Ruan, Y., Fang, X. H., Guo, T., Liu, Y., Hu, Y., Wang, X., Hu, Y., Gao, L., Li, Y., Pi, J., et al. (2021) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2021.113098 · Cited by 28
Qiu, Z., Wang, X., Yang, Z., Liao, S., Dong, W., Sun, T., Wu, H., Zhang, Q., Pan, Z., Lam, S. M., et al. (2022) · Cell Death and Disease · doi:10.1038/s41419-022-04968-6 · Cited by 30
Jiang, F., Luo, F., Zeng, N., Mao, Y., Tang, X., Wang, J., Hu, Y., & Wu, C. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.902143 · Cited by 28
Zhang, R., Li, R., Zhang, L., Chen, G., Mo, L., Jiang, R., Xu, X., Wang, X., Zhao, Y., Zhang, L., et al. (2023) · ACS Nano · doi:10.1021/acsnano.3c01743 · Cited by 28
Host mitochondria: more than an organelle in SARS-CoV-2 infection
Shoraka, S., Samarasinghe, A. E., Ghaemi, A., & Mohebbi, S. R. (2023) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2023.1228275 · Cited by 29
Giles, B., Nakhjavani, M., Wiesa, A., Knight, T., Shigdar, S. L., & Samarasinghe, R. M. (2023) · Cancers · doi:10.3390/cancers15174376 · Cited by 27
Filipe, E. C., Velayuthar, S., Philp, A. M., Nobis, M., Latham, S. L., Parker, A. L., Murphy, K. J., Wyllie, K., Major, G. S., Contreras, O., et al. (2024) · Advanced Science · doi:10.1002/advs.202307963 · Cited by 26
Low, J. C. M., Cao, J., Hesse, F., Wright, A. J., Tsyben, A., Alshamleh, I., Mair, R. J., & Brindle, K. M. (2024) · Cancer Research · doi:10.1158/0008-5472.can-23-2552 · Cited by 27
Metal-organic frameworks derived emerging theranostic platforms
Zheng, N., Li, K., He, L., Wang, Q., Yang, B., Mao, C., Tang, W., Liu, S., & Liu, S. (2024) · Nano Today · doi:10.1016/j.nantod.2024.102404 · Cited by 27
Tumor Metabolic Reprogramming and Ferroptosis: The Impact of Glucose, Protein, and Lipid Metabolism
Zhu, K., Cai, Y., Lan, L., & Luo, N. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252413413 · Cited by 33
N7-methylguanosine modification in cancers: from mechanisms to therapeutic potential
Wu, Q., Fu, X., Liu, G., He, X., Li, Y., & Ou, C. (2025) · Journal of Hematology & Oncology · doi:10.1186/s13045-025-01665-7 · Cited by 29
Targeting PI3K inhibitor resistance in breast cancer with metabolic drugs
Gremke, N., Besong, I., Stroh, A., von Wichert, L., Witt, M., Elmshäuser, S., Wanzel, M., Fromm, M. F., Taudte, R. V., Schmatloch, S., et al. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02180-4 · Cited by 31
Liu, X., Sun, H., Liang, J., Yu, H., Xue, M., Li, Y., Li, W., Xu, Y., Ling, B., & Dingqing, F. (2025) · Journal of Translational Medicine · doi:10.1186/s12967-025-06235-6 · Cited by 27
Bi, G., Bian, Y., Liang, J., Yin, J., Li, R., Zhao, M., Huang, Y., Lu, T., Zhan, C., Fan, H. X., et al. (2021) · Journal of Translational Medicine · doi:10.1186/s12967-021-02889-0 · Cited by 29
Chen, Y., Tian, Y., Jin, G., Cui, Z., Guo, W., Zhang, X., & Liu, X. (2021) · Human & Experimental Toxicology · doi:10.1177/09603271211021476 · Cited by 27
The Cellular Prion Protein and the Hallmarks of Cancer
Mouillet‐Richard, S., Ghazi, A., & Laurent‐Puig, P. (2021) · Cancers · doi:10.3390/cancers13195032 · Cited by 27
Bifarin, O. O., Gaul, D. A., Sah, S., Arnold, R. S., Ogan, K., Master, V. A., Roberts, D. L., Bergquist, S. H., Petros, J. A., Edison, A. S., et al. (2021) · Cancers · doi:10.3390/cancers13246253 · Cited by 28
GFI1B acts as a metabolic regulator in hematopoiesis and acute myeloid leukemia
Liu, L., Patnana, P. K., Xie, X., Frank, D., Nimmagadda, S. C., Su, M., Zhang, D., Koenig, T., Rosenbauer, F., Liebmann, M., et al. (2022) · Leukemia · doi:10.1038/s41375-022-01635-9 · Cited by 28
Zhang, Z., Bao, C., Jiang, L., Wang, S., Wang, K., Lu, C., & Fang, H. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2022.1054233 · Cited by 30
PRMT3 regulates the progression of invasive micropapillary carcinoma of the breast
Zhi, R., Wu, K., Zhang, J., Liu, H., Niu, C., Li, S., & Fu, L. (2023) · Cancer Science · doi:10.1111/cas.15724 · Cited by 28
Cellular Stress: Modulator of Regulated Cell Death
Lamichhane, P. P., & Samir, P. (2023) · Biology · doi:10.3390/biology12091172 · Cited by 30
Ren, J., Ren, B., Liu, X., Cui, M., Fang, Y., Wang, X., Zhou, F., Gu, M., Xiao, R., Bai, J., et al. (2024) · Cancer Letters · doi:10.1016/j.canlet.2024.216649 · Cited by 30
Shining a light on metabolic vulnerabilities in non-small cell lung cancer
Dowling, C. M., Zhang, H., Chonghaile, T. N., & Wong, K.-K. (2021) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2020.188462 · Cited by 26
Targeted therapies in bladder cancer: signaling pathways, applications, and challenges
Peng, M., Chu, X., Peng, Y., Li, D., Zhang, Z., Wang, W., Zhou, X., Xiao, D., & Yang, X. (2023) · MedComm · doi:10.1002/mco2.455 · Cited by 30
Guo, S., Liu, Y., Sun, Y., Zhou, H., Gao, Y., Wang, P., Zhi, H., Zhang, Y., Gan, J., & Ning, S. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c01473 · Cited by 33
Muranaka, H., Akinsola, R., Billet, S., Pandol, S. J., Hendifar, A. E., Bhowmick, N. A., & Gong, J. (2024) · Cancers · doi:10.3390/cancers16051057 · Cited by 27
Qiao, Y., Jia, X., Wang, Y., Liu, L., Zhang, M., & Jiang, X. (2024) · Nanoscale Horizons · doi:10.1039/d4nh00070f · Cited by 26
Single cell atlas reveals multilayered metabolic heterogeneity across tumour types
Zhou, Z. C., Dong, D., Yuan, Y., Luo, J., Liu, X., Chen, L.-Y., Wang, G., & Yin, Y. (2024) · EBioMedicine · doi:10.1016/j.ebiom.2024.105389 · Cited by 27
Cai, L., Hammond, N. G., Tasdogan, A., Alsamraae, M., Yang, C., Cameron, R. B., Quan, P., Solmonson, A., Gu, W., Pachnis, P., et al. (2025) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-1319 · Cited by 28
Self-citationm6A/IGF2BP3-driven serine biosynthesis fuels AML stemness and metabolic vulnerability
Huang, F., Wang, Y., Zhang, X., Gao, W., Li, J., Yang, Y., Mo, H., Prince, E. A., Long, Y., Hu, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58966-1 · Cited by 26
Reprogramming immunity with itaconate: metabolic mechanisms and therapeutic perspectives
Gao, H., Ding, M., Liu, Y., Wang, Y., Zhao, S., Chen, J., Chen, Z., & Wang, G. (2025) · Inflammation Research · doi:10.1007/s00011-025-02087-4 · Cited by 33
The yin and yang of mitochondrial Ca2+ signaling in cell physiology and pathology
Filadi, R., & Greotti, E. (2020) · Cell Calcium · doi:10.1016/j.ceca.2020.102321 · Cited by 28
Metabolism in the Tumour-Bone Microenvironment
Whitburn, J., & Edwards, C. M. (2021) · Current Osteoporosis Reports · doi:10.1007/s11914-021-00695-7 · Cited by 26
Song, I.-S., Jeong, Y. J., Jung, Y., Park, Y., Shim, S., Kim, S. J., Eom, D., Hong, S., Lee, P. C.-W., Kim, S.-U., et al. (2021) · Redox Biology · doi:10.1016/j.redox.2021.102190 · Cited by 28
Zhao, Y., Sun, H., Li, X., Liu, Q., Liu, Y., Hou, Y., & Jin, W. (2022) · Cell Death and Disease · doi:10.1038/s41419-022-04537-x · Cited by 26
Liu, L., Jia Rui, W. U., Shi, M., Wang, F., Lu, H., Liu, J., Chen, W., Yu, G., Liu, D., Yang, J., et al. (2022) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2021.08.016 · Cited by 26
Changes in Pulmonary Microenvironment Aids Lung Metastasis of Breast Cancer
Wu, M., Liang, Y., & Zhang, X. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.860932 · Cited by 28
Ren, Y., He, S., Feng, S., & Yang, W. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.916364 · Cited by 26
Liang, J., Liu, Q., Xia, L., Lin, J., Oyang, L., Tan, S., Peng, Q., Jiang, X., Xu, X., Wu, N., et al. (2022) · Cancer Science · doi:10.1111/cas.15652 · Cited by 26
Critical roles and clinical perspectives of RNA methylation in cancer
Li, G., Yao, Q., Liu, P., Zhang, H., Liu, Y., Li, S., Shi, Y., Li, Z., & Zhu, W. (2024) · MedComm · doi:10.1002/mco2.559 · Cited by 29
Patel, C. B., Beinat, C., Xie, Y., Chang, E., & Gambhir, S. S. (2020) · Neoplasia · doi:10.1016/j.neo.2020.11.003 · Cited by 26
Li, J., Gao, R., & Zhang, J. (2022) · Clinical Breast Cancer · doi:10.1016/j.clbc.2022.11.006 · Cited by 25
Zhang, E., Ding, C., Li, S., Aikemu, B., Zhou, X., Fan, X., Sun, J. P., Yang, X. Y., & Zheng, M. (2023) · Cancer Cell International · doi:10.1186/s12935-023-02892-z · Cited by 26
Ma, Y., Huang, X., Wang, Y., Lei, Y., Yu, J., Yu, S., Gao, Y., Yang, J. J., Zhao, F., Yu, H., et al. (2023) · Advanced Science · doi:10.1002/advs.202305907 · Cited by 25
Liu, X., Wang, W., Zhang, X., Liang, J., Dingqing, F., Li, Y., Xue, M., & Ling, B. (2024) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2024.102155 · Cited by 28
Wang, M., Yi, H., Zhan, Z., Feng, Z., Yang, G., Zheng, Y., & Zhang, D. (2024) · Aggregate · doi:10.1002/agt2.622 · Cited by 25
TRIM50 inhibits glycolysis and the malignant progression of gastric cancer by ubiquitinating PGK1
Gu, C., Xia, Y., Lu, C., Qiu, S., Wang, J., Zhang, L., Lv, J., Jiang, T., Fang, L., Xu, P., et al. (2024) · International Journal of Biological Sciences · doi:10.7150/ijbs.97091 · Cited by 25
PHGDH activation fuels glioblastoma progression and radioresistance via serine synthesis pathway
Liu, X., Liu, B., Wang, J., Liu, H., Wu, J., Qi, Y., Liu, Y., Zhu, H., Li, C., Liu, Y., et al. (2025) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-025-03361-3 · Cited by 27
Nutrient requirements of organ-specific metastasis in breast cancer
Abbott, K. L., Subudhi, S., Ferreira, R., Gültekin, Y., Steinbuch, S. C., Munim, M. B., Ramesh, D. L., Honeder, S. E., Kumar, A. S., Wu, M., et al. (2026) · Nature · doi:10.1038/s41586-025-09898-9 · Cited by 35
Discovery of an interplay between the gut microbiota and esophageal squamous cell carcinoma in mice.
Cheung, M. K., Yue, G. G., Tsui, K.-Y., Gomes, A. J., Kwan, H. S., Chiu, P. W. Y., & Lau, C. B. (2020) · PubMed Central · Cited by 25
Zhang, X., Chen, M., Ni, X., Wang, Y., Zheng, X. Y., Zhang, H., Xu, S. J., & Yang, C. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.571143 · Cited by 25
Pan, D., Zheng, X., Zhang, L., Li, X., Zhu, G., Gong, M., Kopytynski, M., Zhou, L., Yi, Y., Zhu, H., et al. (2022) · Advanced Materials · doi:10.1002/adma.202109036 · Cited by 25
Personalized Medicine for Prostate Cancer: Is Targeting Metabolism a Reality?
Fidelito, G., Watt, M. J., & Taylor, R. A. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2021.778761 · Cited by 27
Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer
Corchado‐Cobos, R., García‐Sancha, N., Mendiburu‐Eliçabe, M., Gómez-Vecino, A., Jiménez‐Navas, A., Pérez‐Baena, M. J., Holgado-Madruga, M., Mao, J., Cañueto, J., Castillo‐Lluva, S., et al. (2022) · Cancers · doi:10.3390/cancers14020322 · Cited by 27
Kusi, M., Zand, M., Lin, L., Chen, M., Lopez, A., Lin, C.-L., Wang, C., Lucio, N. L. L., Kirma, N. B., Ruan, J., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110220 · Cited by 28
Zuo, Q., Mogol, A. N., Liu, Y.-J., Casiano, A. S., Chien, C., Drnevich, J. M., Imir, O. B., Kulkoyluoglu‐Cotul, E., Park, N. H., Shapiro, D. J., et al. (2022) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-21-0781 · Cited by 25
Zhao, H., Jiang, Y., Lin, F., Zhong, M., Tan, J., Zhou, Y., Liu, L., Li, G., Deng, M., & Xu, B. (2022) · Experimental Hematology and Oncology · doi:10.1186/s40164-022-00282-1 · Cited by 25
Perri, F., Scarpati, G. D. V., Pontone, M., Marciano, M. L., Ottaiano, A., Cascella, M., Sabbatino, F., Guida, A., Santorsola, M., Maiolino, P., et al. (2022) · Cancers · doi:10.3390/cancers14153560 · Cited by 25
Li, R., Wilson, K. F., & Cerione, R. A. (2022) · Cell Death Discovery · doi:10.1038/s41420-022-01156-5 · Cited by 25
Interplay of cGAS with micronuclei: Regulation and diseases
Guo, X., Hintzsche, H., Xu, W., Ni, J., Xue, J., & Wang, X. (2022) · Mutation Research/Reviews in Mutation Research · doi:10.1016/j.mrrev.2022.108440 · Cited by 25
Roh, J., Im, M., Chae, Y., Kang, J., & Kim, W. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232314808 · Cited by 25
Li, Y., Mo, H., Jia, S., Wang, J., Ma, Y., Liu, X., & Tu, K. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1066773 · Cited by 25
Cancer plasticity: Investigating the causes for this agility
Saha, S., Pradhan, N., Neha, B., Mahadevappa, R., Minocha, S., & Kumar, S. (2022) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2022.12.005 · Cited by 27
Targeting cancer metabolic vulnerabilities for advanced therapeutic efficacy
Muluh, T. A., Shu, X., & Ying, Y. (2023) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2023.114658 · Cited by 26
Yan, Z., Li, L., Fu, D., Wu, W., Qiao, N., Huang, Y., Jiang, L., Wu, D., Hu, Y., Zhang, H., et al. (2023) · Frontiers of Medicine · doi:10.1007/s11684-022-0972-8 · Cited by 27
ANXA6: a key molecular player in cancer progression and drug resistance
Cao, J., Wan, S., Chen, S., & Li, Y. (2023) · Discover Oncology · doi:10.1007/s12672-023-00662-x · Cited by 25
Hany, D., Vafeiadou, V., & Picard, D. (2023) · Science Advances · doi:10.1126/sciadv.add3685 · Cited by 25
Spermine is a natural suppressor of AR signaling in castration-resistant prostate cancer
Li, X., Li, F., Ye, F., Guo, H., Chen, W., Jin, J., Wang, Y., Dai, P., Shi, H., Tao, H., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112798 · Cited by 25
Farhana, A., Alsrhani, A., Khan, Y. S., & Rasheed, Z. (2023) · Cancers · doi:10.3390/cancers15153836 · Cited by 25
Luo, X., Wei, M., Li, W., Zhao, H., Kasim, V., & Wu, S. (2023) · International Journal of Biological Sciences · doi:10.7150/ijbs.86279 · Cited by 26
SMARCA5 reprograms AKR1B1-mediated fructose metabolism to control leukemogenesis
Yu, P.-C., Hou, D., Chang, B., Liu, N., Xu, C., Chen, X., Hu, C.-L., Liu, T., Wang, X., Zhang, Q., et al. (2024) · Developmental Cell · doi:10.1016/j.devcel.2024.04.023 · Cited by 24
Wang, B., Wang, Z., Zhou, Z., Liu, G., Jiang, Z., Zheng, M., & Geng, W. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02302-0 · Cited by 24
Gong, S., Tetti, M., Reincke, M., & Williams, T. A. (2021) · Cancers · doi:10.3390/cancers13153716 · Cited by 24
Kushwaha, P. P., Verma, S., Shankar, E., Lin, S. H., & Gupta, S. (2021) · Molecular Carcinogenesis · doi:10.1002/mc.23383 · Cited by 25
Perspectives of lipid metabolism reprogramming in head and neck squamous cell carcinoma: An overview
Miao, X., Wang, B., Chen, K., Ding, R., Wu, J., Pan, Y., Ji, P., Ye, B., & Xiang, M. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.1008361 · Cited by 26
Poddar, A., Rao, S. R., Prithviraj, P., Kannourakis, G., & Jayachandran, A. (2022) · Current Oncology · doi:10.3390/curroncol29100540 · Cited by 24
Harnessing bioactive nanomaterials in modulating tumor glycolysis-associated metabolism
Gu, Z., & Yu, C. (2022) · Journal of Nanobiotechnology · doi:10.1186/s12951-022-01740-y · Cited by 24
Chianese, U., Papulino, C., Ali, A. H., Ciardiello, F., Cappabianca, S., Altucci, L., Carafa, V., & Benedetti, R. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-03874-5 · Cited by 24
RETRACTED: The Emerging Role of Epigenetics in Metabolism and Endocrinology
Sibuh, B. Z., Quazi, S., Panday, H., Parashar, R., Jha, N. K., Mathur, R., Jha, S. K., Taneja, P., & Jha, A. K. (2023) · Biology · doi:10.3390/biology12020256 · Cited by 24
RetractedCheng, S., Zhang, D., Feng, J., Hu, Q., Tan, A., Xie, Z., Chen, Q., Huang, H., Wei, Y., Ouyang, Z., et al. (2023) · Research · doi:10.34133/research.0087 · Cited by 24
Tang, Y. R., Li, W., Li, Q., Zhang, X., Zhang, L., Miyagishi, M., Zhao, H., Wu, S., & Kasim, V. (2023) · Oncogenesis · doi:10.1038/s41389-023-00464-4 · Cited by 26
Casiano, A. S., Mehta, D., Danciu, O. C., Patel, H., Banks, L., Zaidi, A., Buckley, J., Rauscher, G. H., Schulte, L., Weller, L., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-39215-1 · Cited by 24
Epstein–Barr Virus Promotes Oral Squamous Cell Carcinoma Stemness through the Warburg Effect
Heawchaiyaphum, C., Yoshiyama, H., Iizasa, H., Burassakarn, A., Tumurgan, Z., Ekalaksananan, T., & Pientong, C. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241814072 · Cited by 24
Tippetts, T. S., Sieber, M., & Solmonson, A. (2023) · Development · doi:10.1242/dev.201610 · Cited by 25
Self-citationFilament formation drives catalysis by glutaminase enzymes important in cancer progression
Feng, S., Aplin, C., Nguyen, T. T., Milano, S. K., & Cerione, R. A. (2024) · Nature Communications · doi:10.1038/s41467-024-46351-3 · Cited by 24
Catechol‐Isolated Atomically Dispersed Nanocatalysts for Self‐Motivated Cocatalytic Tumor Therapy
Wang, Y., Qiu, S., Wang, L., Ji, P., Guo, Y., Yao, H., Wei, C., Huo, M., & Shi, J. (2023) · Angewandte Chemie International Edition · doi:10.1002/anie.202316858 · Cited by 24
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review