Investigating the prognostic value of KCNN4 gene expression in human pancreatic adenocarcinoma by bioinformatic analysis

Finding accurate biomarkers for early detection and prognosis is critical because pancreatic adenocarcinoma (PAAD) is a deadly cancer with a poor prognosis. Though its function in PAAD is still unknown, the gene KCNN4, which codes for a calcium-activated potassium channel, has been linked to a number of malignancies. In this work, the cancer studies of the CPTAC, TCGA, and GTEx projects were targeted using a thorough database mining technique. Several analytical methods were used to examine full-scale molecular, expression, and prognostic profiles of the KCNN4 gene in pancreatic adenocarcinoma tissues. It was discovered that the majority of the cancerous tissue had different levels of mRNA and protein expression for this gene. The results of comparative immunohistochemistry also revealed that normal pancreatic tissues had reduced expression of the KCNN4 protein. An analysis overview of copy-number alterations and KCNN4 mutations in PAAD samples was also conducted. Furthermore, there was a correlation found between the expression of KCNN4 and both overall and disease-free survival in pancreatic adenocarcinoma. In pancreatic adenocarcinoma tissue, co-expressed genes of KCNN4 were found to be involved in cell maintenance-related functions, according to gene coexpression, additional ontology, and pathway analysis. When it comes to cancer diagnosis and treatment, the experimental findings of this study should aid in integrating KCNN4 into clinical applications.