Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers.

Peng X, Chen Z, Farshidfar F, Xu X, Lorenzi PL, Wang Y, Cheng F, Tan L, Mojumdar K, Du D, Ge Z, Li J, Thomas GV, Birsoy K, Liu L, Zhang H, Zhao Z, Marchand C, Weinstein JN, Cancer Genome Atlas Research Network, Bathe OF, Liang H
Cell Rep. 2018 23 (1): 255-269.e4

PMID: 29617665 · PMCID: PMC5916795 · DOI:10.1016/j.celrep.2018.03.077

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1-master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility.

Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

MeSH Terms (9)

Cell Line, Tumor Core Binding Factor Alpha 2 Subunit Drug Resistance, Neoplasm HEK293 Cells Humans Metabolic Networks and Pathways Neoplasms Snail Family Transcription Factors Transcriptome

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