Background: The eighth-leading cause of cancer-related mortality and the seventh-most prevalent malignancy in women globally is ovarian cancer (OV). However, 5-year survival expectancy after conventional treatment is not good. Therefore, there is an urgent need for novel signatures to guide the designation of therapeutic schemes for OV patients.
Methods: We used univariate Cox analysis to screen hormone secretion regulation axis-related microRNAs (miRNAs), least absolute shrinkage and selection operator analysis to select candidate miRNAs and multivariate Cox analysis to build the risk model. To evaluate possible route and functional differences, enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on the differentially expressed genes (DEGs) across various risk groups. We compared Tumor Immune Dysfunction and Exclusion (TIDE) scores across risk categories by analyzing immune cell infiltration, immune checkpoint gene expression, immunological function and TIDE scores. In the end, we determined the half maximal inhibitory concentration (IC50 ) of chemotherapy and targeted medicines for individual patients. Cell assays were determined to test the migration of the miRNA-target genes and western blotting was used to test the correlation of the miRNA-target genes and the pathways.
Results: We finally identified hormone secretion regulation axis-related 13 microRNAs to build a risk model. The validation of observed and anticipated values revealed a fair level of agreement. To evaluate the molecular pathways between various groups in accordance with the GO and KEGG analyses, we then discovered 173 DEGs between distinct risk groups. The risk score was shown to be inversely related to the number of immune cells, including myeloid dendritic, granulocytes, M1 and M2 macrophages, B cells, t-lymphocytes, and CD4+ and CD8+ cells, suggesting that immune cells are more frequent in the low-risk group. Immune cell infiltration investigation yielded these results. Finally, we recognized 11 chemotherapeutic drugs and 30 novels targeted drugs on the basis of IC50 between the different risk groups. GJB5 was determined to be the mir-219 target gene and was identified as promoting the cell cycle process. In addition, hormone secretion regulation axis related miRNAs were reported to affects the heterogeneity of endocrine microenvironment and anti-tumor immune pattern.
Conclusions: In conclusion, a 13-miRNA prognostic model was constructed to know the immune status, prognosis, immunotherapeutic response and anti-tumor drug sensitivity for OV, which provides theoretical guidance for the effective and individualized treatment of OV patients.
Keywords: MicroRNA; immunotherapy; prognosis for ovarian cancer; risk model.
© 2023 John Wiley & Sons Ltd.