[Risk model construction and immune cell infiltration analysis of the CLDN4 gene in ovarian cancer cells]

Objective To screen for the key genes involved in the development of ovarian cancer (OV), analyze the immune cell infiltration and construct a risk model, so as to provide evidence for the early diagnosis, treatment and prognosis evaluation of OV patients. Methods The GSE18520 and GSE6008 datasets were analyzed for differentially expressed genes (DEGs) using the GEO2R data analysis tool, and a Venn diagram was generated. Then, DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) networks, as well as mutations, expression and prognosis analysis to identify key genes. Next, a risk model was constructed and immune cell infiltration analysis of key genes was performed. Finally, ovarian cancer tissues were collected as the experimental group, and adjacent normal tissues were collected as the control group. The expression of claudin 4 (CLDN4) mRNA and protein levels were detected using real-time quantitative PCR (RT-qPCR) and Western-blot, and the results were compared between the two groups. Results CLDN4 was identified as a key gene in the development of OV. As its expression increased, the prognosis risk of OV patients worsened, which unfavorably impacted their overall survival (OS). A significant positive correlation was found between CLDN4 and dendritic cell (DC) in the OV microenvironment, and high expression of DCs was significantly associated with better OS in OV patients. The mRNA and protein expression levels of CLDN4 were significantly increased in OV tissues, with statistically significant differences. Conclusion CLDN4 is a key gene in the development of OV, and may serve as a potential biomarker and immunotherapy target for OV.