Prediction of taxane and platinum sensitivity in ovarian cancer based on gene expression profiles

• Gene expression-driven scores predict platinum/taxane response
• Association of proposed scores with HGSOC gene expression subtypes
• Complimentary roles of platinum and taxane for personalized therapy

ObjectivePrognoses of ovarian cancer (OC) have improved with the paclitaxel-carboplatin regimen. However, it remains unclear which cases exhibit a genuine benefit from taxane or from platinum. We aimed to predict taxane and platinum sensitivity in OC via gene expression.MethodsWe identified differentially expressed genes in responsive and resistant cases from advanced OC biopsy expression dataset GSE15622, containing responses to paclitaxel or carboplatin monotherapy. These genes generated a scoring system for prediction of drug response by applying single-sample gene set enrichment analysis. Discriminative metrics termed the T-score and C-score were derived.ResultsHigh C-score levels were significant in responders compared to non-responders in a separate cisplatin treatment dataset (GSE18864, p = 0.043). High C-score groups also had significantly better progression-free survival in three OC datasets (The Cancer Genome Atlas, TCGA: p = 0.02; GSE9891: p = 0.03; GSE30161: p = 0.001).In two additional datasets of advanced OC, high T-scores could associate taxane and platinum regimens with better survival than non-taxane and platinum regimens (GSE9891: p < 0.0001; GSE3149: p = 0.045), whereas in cases with low T-scores, different chemotherapeutic regimens did not result in a significant difference. Assessing TCGA and GSE9891, T-scores were elevated in the C1/Mesenchymal subtype, whereas C-scores were elevated in the C5/Proliferative subtype and were lower in the C1/Mesenchymal subtype (p < 0.0001, respectively). C- and T-scores negatively correlated with each other, suggesting complementary roles of taxane and platinum.ConclusionsOur proposal and finding of a scoring system that could predict platinum or taxane response could be useful to develop individualized treatments to ovarian cancer.