30 Citations (Scopus)

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. 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.

Original languageEnglish (US)
Pages (from-to)690-705.e9
JournalCancer Cell
Volume33
Issue number4
DOIs
StatePublished - Apr 9 2018

Fingerprint

Breast Neoplasms
Atlases
Long Noncoding RNA
Decision Trees
Genome
Neoplasms
Genes
Estrogen Receptors
Immunotherapy
Breast
Leukocytes
Therapeutics

Keywords

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

ASJC Scopus subject areas

  • Oncology
  • Cell Biology
  • Cancer Research

Cite this

A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers. / The Cancer Genome Atlas Research Network.

In: Cancer Cell, Vol. 33, No. 4, 09.04.2018, p. 690-705.e9.

Research output: Contribution to journalArticle

The Cancer Genome Atlas Research Network. / A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers. In: Cancer Cell. 2018 ; Vol. 33, No. 4. pp. 690-705.e9.
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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. 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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author = "{The Cancer Genome Atlas Research Network} and Berger, {Ashton C.} and Anil Korkut and Kanchi, {Rupa S.} and Hegde, {Apurva M.} and Walter Lenoir and Wenbin Liu and Yuexin Liu and Huihui Fan and Hui Shen and Visweswaran Ravikumar and Arvind Rao and Andre Schultz and Xubin Li and Pavel Sumazin and Cecilia Williams and Pieter Mestdagh and Gunaratne, {Preethi H.} and Christina Yau and Reanne Bowlby and Robertson, {A. Gordon} and Tiezzi, {Daniel G.} and Chen Wang and Cherniack, {Andrew D.} and Godwin, {Andrew K.} and Kuderer, {Nicole M.} and Rader, {Janet S.} and Zuna, {Rosemary E.} and Sood, {Anil K.} and Lazar, {Alexander J.} and Ojesina, {Akinyemi I.} and Clement Adebamowo and Adebamowo, {Sally N.} and Baggerly, {Keith A.} and Chen, {Ting Wen} and Chiu, {Hua Sheng} and Steve Lefever and Borad, {Mitesh J} and Vishal Chandan and John Cheville and Copland, {John A III} and Flotte, {Thomas J} and Michael Kendrick and Jean-Pierre Kocher and O'Neill, {Brian Patrick} and Patel, {Tushar C} and Petersen, {Gloria M} and Roberts, {Lewis Rowland} and Smallridge, {Robert Christian} and Melissa Stanton and Lizhi Zhang",
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AU - Kanchi, Rupa S.

AU - Hegde, Apurva M.

AU - Lenoir, Walter

AU - Liu, Wenbin

AU - Liu, Yuexin

AU - Fan, Huihui

AU - Shen, Hui

AU - Ravikumar, Visweswaran

AU - Rao, Arvind

AU - Schultz, Andre

AU - Li, Xubin

AU - Sumazin, Pavel

AU - Williams, Cecilia

AU - Mestdagh, Pieter

AU - Gunaratne, Preethi H.

AU - Yau, Christina

AU - Bowlby, Reanne

AU - Robertson, A. Gordon

AU - Tiezzi, Daniel G.

AU - Wang, Chen

AU - Cherniack, Andrew D.

AU - Godwin, Andrew K.

AU - Kuderer, Nicole M.

AU - Rader, Janet S.

AU - Zuna, Rosemary E.

AU - Sood, Anil K.

AU - Lazar, Alexander J.

AU - Ojesina, Akinyemi I.

AU - Adebamowo, Clement

AU - Adebamowo, Sally N.

AU - Baggerly, Keith A.

AU - Chen, Ting Wen

AU - Chiu, Hua Sheng

AU - Lefever, Steve

AU - Borad, Mitesh J

AU - Chandan, Vishal

AU - Cheville, John

AU - Copland, John A III

AU - Flotte, Thomas J

AU - Kendrick, Michael

AU - Kocher, Jean-Pierre

AU - O'Neill, Brian Patrick

AU - Patel, Tushar C

AU - Petersen, Gloria M

AU - Roberts, Lewis Rowland

AU - Smallridge, Robert Christian

AU - Stanton, Melissa

AU - Zhang, Lizhi

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N2 - 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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KW - breast cancer

KW - cervical cancer

KW - gynecologic cancer

KW - omics

KW - ovarian cancer

KW - pan-gynecologic

KW - TCGA

KW - The Cancer Genome Atlas

KW - uterine cancer

KW - uterine carcinosarcoma

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JO - Cancer Cell

JF - Cancer Cell

SN - 1535-6108

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