Identification of Potential key Genes and Pathways in Prostate Cancer Using Bioinformatic Analysis

Prostate cancer (PCa) is the world's second most frequent malignancy that threatens men's health. There arestill significant challenges in the treatment of prostate cancer. Its mortality accounts for around ۱۰% of alltumor-related deaths, and it is increasing year by year. The precise molecular pathways are still unknown,prompting urgent study and experience. Therefore, we used bioinformatics analysis to identify potentialbiomarkers and efficient pathways for PCa early detection. The GSE۱۰۳۵۱۲ dataset, which has beendownloaded from the Gene Expression Omnibus database (GEO), was normalized using the Transcriptomeanalysis console (TAC). The genes with adjusted p-value (FDR)< ۰.۰۵ and -۲<|[log FC]|<۲ were identifiedas differentially expressed genes (DEGs) between ۷ normal prostate tissue and ۵۰ PCa samples. Proteinproteininteraction (PPI) and visualization were constructed using string, Cytoscape, and Gephi, respectively.We examined these through KEGG pathway enrichment analysis to determine which biological processes,molecular activities may be linked to the overlapping DEGs. According to the findings,۸۲۲ DEGs (۵۸۵ upregulatedand ۲۳۷ down-regulated) were discovered. V-myc avian myelocytomatosis viral oncogenehomolog (MYC), SRC proto-oncogene, non-receptor tyrosine kinase (SRC), and cadherin ۱, type ۱ (CDH۱)are three overexpressed genes enriched in the KEGG pathway of peroxisome proliferator-activated receptors(PPARs) and bladder cancer, while caveolin ۱ (CAV۱), jun proto-oncogene (JUN), and elastin (ELN) arethree low expressed genes enriched in the KEGG pathway of protein digestion and absorption and focaladhesion pathways. DEGs in prostate cancer were significantly enriched in the following GO terms (mostsignificant) under the biological process's group: ‘extracellular matrix organization’(GO:۰۰۳۰۱۹۸), ‘aorticvalve morphogenesis’(GO:۰۰۰۳۱۸۰), ‘fatty-acyl-CoA biosynthetic process’(GO:۰۰۴۶۹۴۹), and ‘polyaminemetabolic process’(GO:۰۰۰۶۵۹۵). Taken together, we discovered new potential key genes in PCa that mightfunction as robust biomarkers and provide important information for future molecularly targeted therapeutics.