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

Authors

Ashton C. Berger, Massachusetts Institute of Technology
Anil Korkut, University of Texas MD Anderson Cancer Center
Rupa S. Kanchi, University of Texas MD Anderson Cancer Center
Apurva M. Hegde, University of Texas MD Anderson Cancer Center
Walter Lenoir, University of Texas MD Anderson Cancer Center
Wenbin Liu, University of Texas MD Anderson Cancer Center
Yuexin Liu, University of Texas MD Anderson Cancer Center
Huihui Fan, Van Andel Research Institute
Hui Shen, Van Andel Research Institute
Visweswaran Ravikumar, University of Texas MD Anderson Cancer Center
Arvind Rao, University of Texas MD Anderson Cancer Center
Andre Schultz, University of Texas MD Anderson Cancer Center
Xubin Li, University of Texas MD Anderson Cancer Center
Pavel Sumazin, Baylor College of Medicine
Cecilia Williams, The Royal Institute of Technology (KTH)
Pieter Mestdagh, Universiteit Gent
Preethi H. Gunaratne, University of Houston
Christina Yau, Buck Institute for Age Research
Reanne Bowlby, British Columbia Cancer Agency
A. Gordon Robertson, British Columbia Cancer Agency
Daniel G. Tiezzi, Universidade de Sao Paulo - USP
Chen Wang, Mayo Medical School
Andrew D. Cherniack, Massachusetts Institute of Technology
Andrew K. Godwin, University of Kansas Medical Center
Nicole M. Kuderer, Advanced Cancer Research Group
Janet S. Rader, Medical College of Wisconsin
Rosemary E. Zuna, University of Oklahoma Health Sciences Center
Anil K. Sood, University of Texas MD Anderson Cancer Center
Alexander J. Lazar, University of Texas MD Anderson Cancer Center
Akinyemi I. Ojesina, The University of Alabama at Birmingham
Clement Adebamowo, University of Maryland School of Medicine
Sally N. Adebamowo, University of Maryland School of Medicine
Keith A. Baggerly, University of Texas MD Anderson Cancer Center

Document Type

Journal Article

Publication Date

4-9-2018

Journal

Cancer Cell

Volume

33

Issue

4

DOI

10.1016/j.ccell.2018.03.014

Keywords

breast cancer; cervical cancer; gynecologic cancer; omics; ovarian cancer; pan-gynecologic; TCGA; The Cancer Genome Atlas; uterine cancer; uterine carcinosarcoma

Abstract

© 2018 Elsevier Inc. 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. By performing molecular analyses of 2,579 TCGA gynecological (OV, UCEC, CESC, and UCS) and breast tumors, Berger et al. identify five prognostic subtypes using 16 key molecular features and propose a decision tree based on six clinically assessable features that classifies patients into the subtypes.

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