Abstract
Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66–5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57–5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.
Highlights
Ovarian cancer has the highest mortality rate of all gynecological cancers and the fifth highest mortality rate of all cancers in the world[1]
The end point of this study was the identification of a gene signature prognostic of overall survival after first-line chemotherapy in both low- and high-risk groups
Prognostic gene signatures based on chemoresistance, molecular subtyping, and debulking tumors in ovarian cancer have been reported by analysis of homogenous datasets[24,25,26,27]
Summary
Ovarian cancer has the highest mortality rate of all gynecological cancers and the fifth highest mortality rate of all cancers in the world[1]. The overall 5-year survival still remains at 30%7, 8, necessitating the need for better prognostic prediction of chemoresponse in ovarian cancer. Clinicopathological characteristics such as histological grade and the International Federation of Gynecology and Obstetrics (FIGO) staging system are considered as the most important prognostic indicators in ovarian cancer. They are insufficient for predicting survival time and chemoresponse[9, 10]. Our findings suggest an optimal treatment based on the molecular characteristics of ovarian cancer patients
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