EpCAM as a Novel Biomarker for Survivals in Prostate Cancer Patients.

Abstract

Background: Due to the insufficient understanding of the biological mechanisms, the improvement of therapeutic effects of prostate cancer (PCa) is limited. There is an urgent need to find the molecular mechanisms and underlying PCa to improve its early diagnosis, treatment, and prognosis. Methods: The mRNA expression profiles, survival and methylation data of PRAD were downloaded from The Cancer Genome Atlas (TCGA) database. The identification of differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed by R software. Subsequently, we identified the key gene and validated its prognostic role from the Human Protein Atlas (HPA) database, UALCAN and the LinkedOmics database. We performd correlation analysis and constructed the ceRNA network based on the data obtained from miRbase and starBase. Finally, we performed methylation analysis and evaluated the immune cell infiltration by Tumor Immune Estimation Resource (TIMER). Results: A total of 567 DEGs were identified in PCa. ARHGEF38, SLPI, EpCAM, C1QTNF1, and HBB were regarded as target genes related to favorable overall survival (OS). Among them, EpCAM was considered as the most significant gene through the HPA database and receiver operating characteristic (ROC) analysis. A prognostic ceRNA network was constructed with EBLN3P, miR-204-5p, and EpCAM. EpCAM was found to be related to DNA methylation and tumor-infiltrating immune cells. Conclusion: Our findings provide novel insights into the tumorigenesis mechanism of PCa and contribute to the development of EpCAM as a potential prognostic biomarker in PCa.