Oncotarget

Research Papers:

Identification of novel prognostic indicators for triple-negative breast cancer patients through integrative analysis of cancer genomics data and protein interactome data

Fan Zhang, Chunyan Ren, Hengqiang Zhao, Lei Yang, Fei Su, Ming-Ming Zhou, Junwei Han, Eric A. Sobie and Martin J. Walsh _

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Oncotarget. 2016; 7:71620-71634. https://doi.org/10.18632/oncotarget.12287

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Abstract

Fan Zhang1,*, Chunyan Ren2,*, Hengqiang Zhao1, Lei Yang1, Fei Su1, Ming-Ming Zhou2, Junwei Han1, Eric A. Sobie2, Martin J. Walsh2

1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, PR China

2Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA

*These authors have contributed equally to this work

Correspondence to:

Martin J. Walsh, email: martin.walsh@mssm.edu

Eric A. Sobie, email: eric.sobie@mssm.edu

Junwei Han, email: hanjunwei1981@163.com

Keywords: triple-negative breast cancer, landmark for cancer prognosis, GTPase, ubiquitination, oxidative damage

Received: July 27, 2016     Accepted: September 22, 2016     Published: September 27, 2016

ABSTRACT

Triple negative breast cancers (TNBCs) are highly heterogeneous and aggressive without targeted treatment. Here, we aim to systematically dissect TNBCs from a prognosis point of view by building a subnetwork atlas for TNBC prognosis through integrating multi-dimensional cancer genomics data from The Cancer Genome Atlas (TCGA) project and the interactome data from three different interaction networks. The subnetworks are represented as the protein-protein interaction modules perturbed by multiple genetic and epigenetic interacting mechanisms contributing to patient survival. Predictive power of these subnetwork-derived prognostic models is evaluated using Monte Carlo cross-validation and the concordance index (C-index). We uncover subnetwork biomarkers of low oncogenic GTPase activity, low ubiquitin/proteasome degradation, effective protection from oxidative damage, and tightly immune response are linked to better prognosis. Such a systematic approach to integrate massive amount of cancer genomics data into clinical practice for TNBC prognosis can effectively dissect the molecular mechanisms underlying TNBC patient outcomes and provide potential opportunities to optimize treatment and develop therapeutics.


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