Immune Classification of Serous Ovarian Carcinoma and Prediction of Sensitivity to Immunotherapy

Objective Serous ovarian cancer (SOC) is the most prevalent pathological type of OC. Currently, no effective approaches can be used to improve prognosis of SOC in clinical practice. Immunotherapy has demonstrated its considerable potential in improving cancer prognosis to a certain extent. The tumor microenvironment (TME) has an important impact on the effect of immunotherapy. A comprehensive understanding of the TME can provide a foundation for working out targeted immunotherapeutic strategies against cancer. However, the relationship between the immune microenvironment of SOC and immunotherapy remains to be fully elucidated.Methods First, we collected 591 gene expression samples of SOC from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Then, we used CIBERSORT and ESTIMATE to quantify the infiltration of SOC immune cells and ConsensusCluster to implement immunophenotyping. This way, differential genes between different subtypes were screened out. Finally, the Principal Component Analysis technique (PCA) was used to obtain an immune score.Results Three types of immune checkpoint inhibitor (ICI) subtypes and two ICI gene clusters were defined, and the ICI score was obtained. The results show that there was close relation between the immune score and the prognosis of SOC. Tumors with low ICI scores showed increased tumor mutation burden (TMB) and enhanced immune activation signaling pathways. This indicates that low ICI score groups may exhibit better responses to immunotherapy and have favorable prognosis.Conclusion This study suggests that the ICI score may serve as a predictive indicator of prognosis and sensitivity to immunotherapy in SOC.