A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.

TitleA Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.
Publication TypeJournal Article
Year of Publication2018
AuthorsBerger, AC, Korkut, A, Kanchi, RS, Hegde, AM, Lenoir, W, Liu, W, Liu, Y, Fan, H, Shen, H, Ravikumar, V, Rao, A, Schultz, A, Li, X, Sumazin, P, Williams, C, Mestdagh, P, Gunaratne, PH, Yau, C, Bowlby, R, A Robertson, G, Tiezzi, DG, Wang, C, Cherniack, AD, Godwin, AK, Kuderer, NM, Rader, JS, Zuna, RE, Sood, AK, Lazar, AJ, Ojesina, AI, Adebamowo, C, Adebamowo, SN, Baggerly, KA, Chen, T-W, Chiu, H-S, Lefever, S, Liu, L, MacKenzie, K, Orsulic, S, Roszik, J, Shelley, CSimon, Song, Q, Vellano, CP, Wentzensen, N, Weinstein, JN, Mills, GB, Levine, DA, Akbani, R
Corporate AuthorsCancer Genome Atlas Research Network
JournalCancer Cell
Volume33
Issue4
Pagination690-705.e9
Date Published2018 Apr 09
ISSN1878-3686
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.

DOI10.1016/j.ccell.2018.03.014
Alternate JournalCancer Cell
PubMed ID29622464