Gene networks and expression quantitative trait loci associated with adjuvant chemotherapy response in high-grade serous ovarian cancer

Author:

Choi Jihoon,Topouza Danai G.,Tarnouskaya Anastasiya,Nesdoly Sean,Koti Madhuri,Duan Qing Ling

Abstract

Abstract Background A major impediment in the treatment of ovarian cancer is the relapse of chemotherapy-resistant tumors, which occurs in approximately 25% of patients. A better understanding of the biological mechanisms underlying chemotherapy resistance will improve treatment efficacy through genetic testing and novel therapies. Methods Using data from high-grade serous ovarian carcinoma (HGSOC) patients in the Cancer Genome Atlas (TCGA), we classified those who remained progression-free for 12 months following platinum-taxane combination chemotherapy as “chemo-sensitive” (N = 160) and those who had recurrence within 6 months as “chemo-resistant” (N = 110). Univariate and multivariate analysis of expression microarray data were used to identify differentially expressed genes and co-expression gene networks associated with chemotherapy response. Moreover, we integrated genomics data to determine expression quantitative trait loci (eQTL). Results Differential expression of the Valosin-containing protein (VCP) gene and five co-expression gene networks were significantly associated with chemotherapy response in HGSOC. VCP and the most significant co-expression network module contribute to protein processing in the endoplasmic reticulum, which has been implicated in chemotherapy response. Both univariate and multivariate analysis findings were successfully replicated in an independent ovarian cancer cohort. Furthermore, we identified 192 cis-eQTLs associated with the expression of network genes and 4 cis-eQTLs associated with BRCA2 expression. Conclusion This study implicates both known and novel genes as well as biological processes underlying response to platinum-taxane-based chemotherapy among HGSOC patients.

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Genetics,Oncology

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