4.8 Article

A modular master regulator landscape controls cancer transcriptional identity

期刊

CELL
卷 184, 期 2, 页码 334-+

出版社

CELL PRESS
DOI: 10.1016/j.cell.2020.11.045

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资金

  1. National Cancer Institute's (NCI) Office of Cancer Target Discovery and Development (CTDboolean AND2) initiative [U01CA217858]
  2. NCI Outstanding Investigator Award [R35CA197745]
  3. NCI Research Centers for Cancer Systems Biology Consortium [U54CA209997]
  4. Prostate Cancer Foundation [18CHAL07]
  5. NIH R01 [R01CA173481, R01CA196662]
  6. NIH Instrumentation grants [S10OD012351, S10 OD021764]
  7. Spanish ISCIII-MINECO [PI19/00342, PI16/01070, EAURF/407003/XH]
  8. DOD Award [W81XWH-18-1-0193]
  9. CERCA Program/Generalitat de Catalunya
  10. FEDER/ERDF funds-a way to Build Europe
  11. DOD Early Investigator Research Award [W81XWH19-1-0337]
  12. [P30CA013696]

向作者/读者索取更多资源

Using a network-based approach, 407 master regulator proteins were identified to canalize individual cancer samples into 112 transcriptionally distinct tumor subtypes. These proteins were organized into 24 pan-cancer master regulator block modules regulating key cancer hallmarks and predictive of patient outcome. Genomic alterations were predicted to induce aberrant MR activity, providing insight into mechanisms linking tumor genetics and transcriptional identity.
Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive, Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations.

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