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

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.