ArticleNature communications2018
Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 175 papers, 2 of them syntheses that pooled it.
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Who cites it
175 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Metabolism of pancreatic neuroendocrine tumors: what can omics tell us?Frontiers in endocrinology · 2023Pooled it
- Statistical genomics in rare cancer.Seminars in cancer biology · 2020Pooled it
- Integrative multi-omics analysis uncovers tumor-immune-gut axis influencing immunotherapy outcomes in ovarian cancer.Nature communications · 2024Trial
- Identification and validation of a plasma metabolomics-based model for risk stratification of intrahepatic cholangiocarcinoma.Journal of cancer research and clinical oncology · 2023Trial
- Metabolic rewiring of the dendritic cell-T cell axis: tumour-derived barriers and therapeutic opportunities.Experimental & molecular medicine · 2026Review
- Cleavage of the RNA polymerase II general transcription factor TFIIB tunes transcription during stress.Genes & development · 2026Article
- NPAS3-regulated astrocyte mitochondrial bioenergetics is required for cognition.Science advances · 2026Article
- Identification of metabolism-associated molecular classification and prognostic genes for medulloblastoma based on bioinformatics analysis.Clinics (Sao Paulo, Brazil) · 2026Article
- Metabolic profiling defines glioblastoma subtypes with distinct prognoses and therapeutic vulnerabilities.Neuro-oncology · 2026Article
- Molecular classification and construction of prognostic risk model via machine learning based on metabolic-related genes in hepatocellular carcinoma.Translational cancer research · 2026Article
- Palmatine ameliorates MASLD in type 2 diabetes by modulating hepatic apoptosis and inflammation.Scientific reports · 2026Article
- Integrated multi-omics analysis reveals comprehensive metabolism-driven tumor heterogeneity and immune microenvironment in hepatocellular carcinomas.Scientific reports · 2026Article
- Multi-Modal Metabolomics Deciphers Pan-Cancer Metabolic Landscapes and Spatial-Niche-Specific Alternations.Metabolites · 2026Article
- BiTE-secreting T cells rationally combine with PD-1 blockade and vaccine boosting to reshape antitumor immunity in ovarian cancer.Molecular therapy : the journal of the American Society of Gene Therapy · 2026Article
- Transcriptomic profiling of epigenetic regulators and metabolic reprogramming in human cholangiocarcinoma.Frontiers in cell and developmental biology · 2026Article
- Article
- The impact of epigenetics on tumor metabolism: Friend or foe in drug response?Frontiers in epigenetics and epigenomics · 2026Review
- HOXC-AS1: A Key Biomarker for Prognosis and Immunotherapy in Lung Adenocarcinoma.Current computer-aided drug design · 2026Article
- Revealing sphingolipid metabolism genes as biomarkers for the diagnosis of invasive pituitary adenomas in silico and in vivo.European journal of medical research · 2025Article
- Serum untargeted metabolomics analysis of colorectal cancer.BMC cancer · 2025Article
115 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Understanding metabolic dysregulation in different disease settings is vital for the safe and effective incorporation of metabolism-targeted therapeutics in the clinic. Here, using transcriptomic data for 10,704 tumor and normal samples from The Cancer Genome Atlas, across 26 disease sites, we present a novel bioinformatics pipeline that distinguishes tumor from normal tissues, based on differential gene expression for 114 metabolic pathways. We confirm pathway dysregulation in separate patient populations, demonstrating the robustness of our approach. Bootstrapping simulations were then applied to assess the biological significance of these alterations. We provide distinct examples of the types of analysis that can be accomplished with this tool to understand cancer specific metabolic dysregulation, highlighting novel pathways of interest, and patterns of metabolic flux, in both common and rare disease sites. Further, we show that Master Metabolic Transcriptional Regulators explain why metabolic differences exist, can segregate patient populations, and predict responders to different metabolism-targeted therapeutics.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.