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
KeywordsBreast Neoplasms, Databases, Genetic, DNA Copy Number Variations, Female, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Genetic Predisposition to Disease, Genital Neoplasms, Female, Humans, Mutation, Organ Specificity, Prognosis, Receptors, Estrogen, RNA, Long Noncoding
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
PubMed Central IDPMC5959730
Grant ListP30 CA016087 / CA / NCI NIH HHS / United States
U24 CA143858 / CA / NCI NIH HHS / United States
U54 HG003067 / HG / NHGRI NIH HHS / United States
U24 CA210950 / CA / NCI NIH HHS / United States
U01 CA217842 / CA / NCI NIH HHS / United States
U54 HG003079 / HG / NHGRI NIH HHS / United States
P50 CA136393 / CA / NCI NIH HHS / United States
P50 CA098258 / CA / NCI NIH HHS / United States
U24 CA143882 / CA / NCI NIH HHS / United States
U24 CA210957 / CA / NCI NIH HHS / United States
U54 HG003273 / HG / NHGRI NIH HHS / United States
U24 CA144025 / CA / NCI NIH HHS / United States
U24 CA143867 / CA / NCI NIH HHS / United States
U01 CA168394 / CA / NCI NIH HHS / United States
U24 CA210949 / CA / NCI NIH HHS / United States
U24 CA143883 / CA / NCI NIH HHS / United States
R01 CA163722 / CA / NCI NIH HHS / United States
U24 CA143799 / CA / NCI NIH HHS / United States
U24 CA199461 / CA / NCI NIH HHS / United States
U24 CA143843 / CA / NCI NIH HHS / United States
U24 CA210990 / CA / NCI NIH HHS / United States
P30 CA016672 / CA / NCI NIH HHS / United States
U24 CA143866 / CA / NCI NIH HHS / United States
P50 CA217685 / CA / NCI NIH HHS / United States
U24 CA143845 / CA / NCI NIH HHS / United States
U24 CA143840 / CA / NCI NIH HHS / United States
U24 CA143835 / CA / NCI NIH HHS / United States
U24 CA143848 / CA / NCI NIH HHS / United States

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