Profound Tissue Specificity in Proliferation Control Underlies Cancer Drivers and Aneuploidy Patterns
| Autor: | Kathleen A. Scorsone, Stephen J. Elledge, Anthony C. Liang, Yuyang Li, Qikai Xu, Yumei Leng, Thomas F. Westbrook, Timothy D. Martin, Ronald J. Bernardi, Laura M. Sack, Ting Chen, Mamie Z. Li, Kamila Naxerova, Kwok-Kin Wong, Teresa Davoli, Eric C. Wooten |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Cell type Somatic cell Aneuploidy Genomics Mice SCID Computational biology Biology SCNA Chromosomes General Biochemistry Genetics and Molecular Biology Mice Open Reading Frames 03 medical and health sciences Mice Inbred NOD Cell Line Tumor Neoplasms medicine Animals Humans RNA Small Interfering Gene Cell Proliferation Gene Library Chromosome Mapping Cancer Oncogenes medicine.disease 030104 developmental biology Keratins Female RNA Interference E2F1 Transcription Factor Genetic screen |
| Zdroj: | Cell. 173:499-514.e23 |
| ISSN: | 0092-8674 |
| DOI: | 10.1016/j.cell.2018.02.037 |
| Popis: | Genomics has provided a detailed structural description of the cancer genome. Identifying oncogenic drivers that work primarily through dosage changes is a current challenge. Unrestrained proliferation is a critical hallmark of cancer. We constructed modular, barcoded libraries of human open reading frames (ORFs) and performed screens for proliferation regulators in multiple cell types. Approximately 10% of genes regulate proliferation, with most performing in an unexpectedly highly tissue-specific manner. Proliferation drivers in a given cell type showed specific enrichment in somatic copy number changes (SCNAs) from cognate tumors and helped predict aneuploidy patterns in those tumors, implying that tissue-type-specific genetic network architectures underlie SCNA and driver selection in different cancers. In vivo screening confirmed these results. We report a substantial contribution to the catalog of SCNA-associated cancer drivers, identifying 147 amplified and 107 deleted genes as potential drivers, and derive insights about the genetic network architecture of aneuploidy in tumors. |
| Databáze: | OpenAIRE |
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