Prognostic characteristics and immunological role of angiogenic factors in epithelial ovarian cancer

Background: The combination of antiangiogenic and immune checkpoint inhibitor therapies has emerged as a breakthrough treatment for ovarian cancer (OC). However, the immune effects of angiogenesis-related factors in OC remain to be investigated. Methods Using OC single-cell RNA sequencing (scRNA-seq) data (GSE189843) obtained from Gene Expression Omnibus and bulk data from The Cancer Genome Atlas, we identified differentially expressed genes in OC epithelial cells. Furthermore, functional enrichment analysis and gene set enrichment analysis were performed using “clusterProfiler,” followed by univariate Cox regression to identify genes with prognostic significance. The efficiency of the prognostic risk scoring model was evaluated using receiver operating characteristic (ROC) analysis. Angiogenesis-related factors were identified using public databases, and immune analysis of these factors was performed using TIMER and TIDE data. Results The functional enrichment analysis revealed that the differentially expressed cancer genes identified in OC epithelial cells were associated with immune functions, including B-cell activation and immunoglobulin complex, and 13 genes were found to have significant prognostic implications. Subsequently, a prognostic risk model comprising four genes ( IGKC , KRT19 , JCHAIN , and SCNN1A ) was constructed. ROC analysis showed favorable performance of the model in terms of discrimination efficiency. Additionally, we identified 25 angiogenic factors specifically expressed in epithelial cells. Importantly, the expressions of angiogenic factors clusterin (CLU) and ceruloplasmin (CP) were found to significantly affect the immune response in OC and showed a strong association with the prognosis of OC patients. Conclusions Our study identified prognostic factors in OC epithelial cells and established a prognostic risk model.