A VEGF-dependent gene signature enriched in mesenchymal ovarian cancer predicts patient prognosis.

Xia Yin,Jin Liu,Zhuowei Gu,Hongxia Li,Wen Di,Qing Li,Boqiang Shen,Guanglei Zhuang,Xiaojie Wang,Qi Yang,Zhenfeng Zhang,Mei-Chun Cai,Ying Jing

doi:10.1038/srep31079

Abstract

We have previously reported surrogate biomarkers of VEGF pathway activities with the potential to provide predictive information for anti-VEGF therapies. The aim of this study was to systematically evaluate a new VEGF-dependent gene signature (VDGs) in relation to molecular subtypes of ovarian cancer and patient prognosis. Using microarray profiling and cross-species analysis, we identified 140-gene mouse VDGs and corresponding 139-gene human VDGs, which displayed enrichment of vasculature and basement membrane genes. In patients who received bevacizumab therapy and showed partial response, the expressions of VDGs (summarized to yield VDGs scores) were markedly decreased in post-treatment biopsies compared with pre-treatment baselines. In contrast, VDGs scores were not significantly altered following bevacizumab treatment in patients with stable or progressive disease. Analysis of VDGs in ovarian cancer showed that VDGs as a prognostic signature was able to predict patient outcome. Correlation estimation of VDGs scores and molecular features revealed that VDGs was overrepresented in mesenchymal subtype and BRCA mutation carriers. These findings highlighted the prognostic role of VEGF-mediated angiogenesis in ovarian cancer, and proposed a VEGF-dependent gene signature as a molecular basis for developing novel diagnostic strategies to aid patient selection for VEGF-targeted agents.

Highlights

Of bevacizumab (Avastin), a humanized VEGF blocking monoclonal antibody, in a range of solid tumor types, a series of clinical studies have been conducted to evaluate bevacizumab in patients with newly-diagnosed or recurrent ovarian cancer
We extended previous work of exploiting gene expression profiling approach for accurate detection of VEGF downstream biological activity, and designed a more stringent analytical protocol to identify and validate a reliable VEGF-dependent gene signature in preclinical tumor models and in human patients
We presented a detailed analysis of the VDGs in ovarian cancer by systematically interrogating The Cancer Genome Atlas (TCGA) HGS-OvCa expression data and four additional genome-wide transcriptome cohorts in the public domain

Summary

Introduction

Of bevacizumab (Avastin), a humanized VEGF blocking monoclonal antibody, in a range of solid tumor types, a series of clinical studies have been conducted to evaluate bevacizumab in patients with newly-diagnosed or recurrent ovarian cancer. Two further randomized phase III clinical trials (OCEANS and AURELIA) have proved the efficacy of bevacizumab in recurrent ovarian cancer[18,19]. Based on these results, bevacizumab received European and FDA regulatory approval for use in combination with chemotherapy to treat advanced-stage ovarian cancer. The increased PFS did not translate into a significant improvement in overall survival (OS) and robust biomarkers for predicting bevacizumab efficacy are currently lacking, which impedes patient selection and the optimal use of bevacizumab in ovarian cancer[20,21]. The selected gene set was able to inform on VEGF downstream bioactivity and predict clinical outcome in breast cancer following bevacizumab treatment[22]. Through further characterization of angiogenesis-related gene transcripts in mouse models and human samples, we established a novel VEGF-dependent gene signature and investigated its correlation with molecular subtypes of ovarian cancer and patient prognosis

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