Integrated Biological Networks Associated with Platinum-Based Chemotherapy Response in High-Grade Serous Ovarian Cancer

Abstract

Ovarian cancer is the 8th most common gynecological cancer and the 7th leading cause of cancer death in women, as it has the lowest 5-year survival rate of all common female reproductive system cancers. The first-line standard of care for ovarian cancer patients is primary debulking surgery and platinum-based chemotherapy. However, 20-30% of patients are resistant to this treatment. Previous studies have identified genes correlated with chemotherapy response in ovarian cancer, but the underlying mechanisms of resistance remain poorly understood. This study reports novel genes and biological networks associated with platinum-based chemotherapy response as measured by the patient platinum-free interval, using transcriptomics data from high-grade serous ovarian cancer (HGSOC) patients from The Cancer Genome Atlas. Univariate analysis of patient gene expression was used to identify differentially expressed genes and miRNAs. A machine-learning multivariate approach was then used to determine co-expression based connections among transcripts using both mRNA and miRNA-sequence data. Next, novel integrated networks were constructed, indicating potential regulation of mRNA co-expression networks by miRNAs. DNA sequence variants that potentially regulate gene expression, known as expression quantitative trait loci (eQTL), were detected through integrative analysis of mRNA expression and genome-wide polymorphism datasets from this ovarian cancer cohort. This study identified 92 differentially expressed mRNAs that indicate a downregulation of adaptive immunity in chemo-resistant patients, and one mRNA network enriched for protein ubiquitination. The analysis also identified 21 differentially expressed miRNAs that regulate the epithelial to mesenchymal transition (EMT) and the MET/ERK2 oncogenic pathway, and three miRNA networks enriched for lipoprotein transport and angiogenesis. An expression correlation analysis detected miRNAs that may regulate the transcriptional network associated with resistance. Finally, 74 eQTLs associated with significant mRNAs were reported. This study characterised novel transcriptional networks that potentially regulate chemotherapy response in HGSOC patients and helped elucidate the underlying mechanisms of platinum-based chemo-resistance. The impact of these findings lies in precision medicine, where a better understanding of the genes modulating treatment response can lead to more accurate genetic screening of HGSOC patients and determine novel therapeutic targets for ovarian cancer.