A modular master regulator landscape controls cancer transcriptional identity
| Autor: | Alessandro Vasciaveo, Andrea Califano, Brennan Chu, Somnath Tagore, Sunny J. Jones, Cory Abate-Shen, Federico M. Giorgi, Evan O. Paull, Siyuan Zheng, Prem S. Subramaniam, Mariano J. Alvarez, Eugene F Douglass, Alvaro Aytes, Roel G.W. Verhaak |
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| Přispěvatelé: | Paull, Evan O, Aytes, Alvaro, Jones, Sunny J, Subramaniam, Prem S, Giorgi, Federico M, Douglass, Eugene F, Tagore, Somnath, Chu, Brennan, Vasciaveo, Alessandro, Zheng, Siyuan, Verhaak, Roel, Abate-Shen, Cory, Alvarez, Mariano J, Califano, Andrea |
| Rok vydání: | 2021 |
| Předmět: |
Transcription
Genetic Somatic cell multiomic Mice Nude cancer systems biology Computational biology Adenocarcinoma Biology Article General Biochemistry Genetics and Molecular Biology 03 medical and health sciences 0302 clinical medicine integrative genomic Cell Line Tumor Neoplasms cancer genetic Gene expression medicine Transcriptional regulation Animals Humans network analysi Gene Regulatory Networks transcriptional regulation genomic alteration 030304 developmental biology 0303 health sciences Genome Human Reproducibility of Results Cancer medicine.disease Phenotype Gene Expression Regulation Neoplastic HEK293 Cells Cancer systems biology Colonic Neoplasms Mutation Cancer cell Identity (object-oriented programming) pan-cancer analysi 030217 neurology & neurosurgery |
| Zdroj: | Cell |
| ISSN: | 0092-8674 |
| DOI: | 10.1016/j.cell.2020.11.045 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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