Ovarian cancer (OV) is a highly heterogeneous gynecological tumor that makes the prognostic prediction challenging. Resistance to platinum-based chemotherapy is associated with a poor prognosis in OV. There seems to be an overlap between molecular mechanisms responsible for platinum resistance and immunogenicity in OV. However, the predictive role of platinum resistance-related immune genes for OV prognosis needs to be further explored. In our study, the mRNA expression data of OV patients with corresponding clinical information were collected from The Cancer Genome Atlas (TCGA) cohort and International Cancer Genome Consortium (ICGC) cohort. A multigene signature was constructed for OV patients in the TCGA cohort using the least absolute shrinkage and selection operator (LASSO) Cox regression model according to the optimal value of λ and was validated in the ICGC cohort. Furthermore, we performed functional analysis to explore the immune status between low- and high-risk groups based on the median value of the risk score for the multigene signature. Our data showed that there were 41.1% of the platinum resistance-related genes which differentially expressed between immune score low- and high-OV patients in the TCGA cohort. Univariate Cox regression analysis identified 30 differentially expressed genes (DEGs) associated with overall survival (OS) (P < 0.05). 14 genes were identified to construct a novel platinum resistance-related immune model for classifying OV patients into the low- and high- risk groups. Patients in the low-risk group showed significantly higher OS than those in the high-risk group (P < 0.0001 in the both TCGA and ICGC cohort), which was associated with different immune status for the two risk groups. A novel platinum resistance-related immune model can be used for prognostic prediction in OV. Targeting tumor immunity may be a therapeutic alternative for OV with platinum resistance.
© 2023. The Author(s).