An integrated genomics approach identifies drivers of proliferation in luminal-subtype human breast cancer

Charles Perou and colleagues apply a panel of 52 published gene expression signatures of human breast tumors to expression data from The Cancer Genome Project to identify new proliferation drivers. They find genomic regions that are uniquely amplified in highly proliferative luminal breast tumors, i...

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Bibliographic Details
Published in:Nature genetics Vol. 46; no. 10; pp. 1051 - 1059
Main Authors: Gatza, Michael L, Silva, Grace O, Parker, Joel S, Fan, Cheng, Perou, Charles M
Format: Journal Article
Language:English
Published: New York Nature Publishing Group US 01.10.2014
Nature Publishing Group
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ISSN:1061-4036, 1546-1718, 1546-1718
Online Access:Get full text
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Summary:Charles Perou and colleagues apply a panel of 52 published gene expression signatures of human breast tumors to expression data from The Cancer Genome Project to identify new proliferation drivers. They find genomic regions that are uniquely amplified in highly proliferative luminal breast tumors, including some that are correlated with poor prognosis. Elucidating the molecular drivers of human breast cancers requires a strategy that is capable of integrating multiple forms of data and an ability to interpret the functional consequences of a given genetic aberration. Here we present an integrated genomic strategy based on the use of gene expression signatures of oncogenic pathway activity ( n = 52) as a framework to analyze DNA copy number alterations in combination with data from a genome-wide RNA-mediated interference screen. We identify specific DNA amplifications and essential genes within these amplicons representing key genetic drivers, including known and new regulators of oncogenesis. The genes identified include eight that are essential for cell proliferation ( FGD5 , METTL6 , CPT1A , DTX3 , MRPS23 , EIF2S2 , EIF6 and SLC2A10 ) and are uniquely amplified in patients with highly proliferative luminal breast tumors, a clinical subset of patients for which few therapeutic options are effective. This general strategy has the potential to identify therapeutic targets within amplicons through an integrated use of genomic data sets.
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ISSN:1061-4036
1546-1718
1546-1718
DOI:10.1038/ng.3073