| Literature DB >> 29622464 |
Ashton C Berger1, Anil Korkut2, Rupa S Kanchi2, Apurva M Hegde2, Walter Lenoir2, Wenbin Liu2, Yuexin Liu2, Huihui Fan3, Hui Shen3, Visweswaran Ravikumar2, Arvind Rao2, Andre Schultz2, Xubin Li2, Pavel Sumazin4, Cecilia Williams5, Pieter Mestdagh6, Preethi H Gunaratne7, Christina Yau8, Reanne Bowlby9, A Gordon Robertson9, Daniel G Tiezzi10, Chen Wang11, Andrew D Cherniack12, Andrew K Godwin13, Nicole M Kuderer14, Janet S Rader15, Rosemary E Zuna16, Anil K Sood17, Alexander J Lazar18, Akinyemi I Ojesina19, Clement Adebamowo20, Sally N Adebamowo21, Keith A Baggerly2, Ting-Wen Chen22, Hua-Sheng Chiu4, Steve Lefever6, Liang Liu23, Karen MacKenzie24, Sandra Orsulic25, Jason Roszik26, Carl Simon Shelley27, Qianqian Song23, Christopher P Vellano28, Nicolas Wentzensen29, John N Weinstein30, Gordon B Mills31, Douglas A Levine32, Rehan Akbani33.
Abstract
We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.Entities:
Keywords: TCGA; The Cancer Genome Atlas; breast cancer; cervical cancer; gynecologic cancer; omics; ovarian cancer; pan-gynecologic; uterine cancer; uterine carcinosarcoma
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Year: 2018 PMID： 29622464 PMCID： PMC5959730 DOI： 10.1016/j.ccell.2018.03.014
Source DB: PubMed Journal: Cancer Cell ISSN： 1535-6108 Impact factor: 31.743