Journal
MOLECULAR CANCER THERAPEUTICS
Volume 14, Issue 6, Pages 1495-1503Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1535-7163.MCT-15-0039
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Funding
- Australian National Health and Medical Research Council [566603, 1043884]
- Emer Casey Foundation
- Cancer Council of Victoria Postgraduate Scholarship
- Australian Cancer Research Foundation (ACRF)
- Victorian Department of Industry, Innovation and Regional Development (DIIRD)
- Australian Phenomics Network (APN)
- Australian Government's Education Investment Fund through the Super Science Initiative
- Australasian Genomics Technologies Association (AMATA)
- Brockhoff Foundation
- Peter MacCallum Cancer Centre Foundation
- Canadian Institutes of Health Research Proof of Principle Grant
- Cancer Research UK (CRUK)
- Bristol-Myers-Squibb
- Eve Appeal - National Institute for Health Research University College London Hospitals Biomedical Research Centre
- STOP CANCER
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Identification of genomic alterations defining ovarian carcinoma subtypes may aid the stratification of patients to receive targeted therapies. We characterized high-grade serous ovarian carcinoma (HGSC) for the association of amplified and over-expressed genes with clinical outcome using gene expression data from 499 HGSC patients in the Ovarian Tumor Tissue Analysis cohort for 11 copy number amplified genes: ATP13A4, BMP8B, CACNA1C, CCNE1, DYRK1B, GAB2, PAK4, RAD21, TPX2, ZFP36, and URI. The Australian Ovarian Cancer Study and The Cancer Genome Atlas datasets were also used to assess the correlation between gene expression, patient survival, and tumor classification. In a multivariate analysis, high GAB2 expression was associated with improved overall and progression-free survival (P = 0.03 and 0.02), whereas high BMP8B and ATP13A4 were associated with improved progression-free survival (P = 0.004 and P = 0.02). GAB2 overexpression and copy number gain were enriched in the AOCS C4 subgroup. High GAB2 expression correlated with enhanced sensitivity in vitro to the dual PI3K/mTOR inhibitor PF-04691502 and could be used as a genomic marker for identifying patients who will respond to treatments inhibiting PI3K signaling. (C) 2015 AACR.
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