Identification of immunization-related new prognostic biomarkers for papillary renal cell carcinoma by integrated bioinformatics analysis

Abstract

Abstract Background Despite papillary renal cell carcinoma (pRCC) being the second most common type of kidney cancer, the underlying molecular mechanism remains unclear. Targeted therapies in the past have not been successful because of the lack of a clear understanding of the molecular mechanism. Hence, exploring the underlying mechanisms and seeking novel biomarkers for pursuing a precise prognostic biomarker and appropriate therapies are critical. Material and methods In our research, the differentially expressed genes (DEGs) were screened from the TCGA and GEO databases, and a total of 149 upregulated and 285 downregulated genes were sorted. This was followed by construction of functional enrichment and protein–protein interaction (PPI) network, and then the top 15 DEGs were selected for further analysis. The P4HB gene was chosen as our target gene by repetitively validating multiple datasets, and higher levels of P4HB expression predicted lower overall survival (OS) in patients with pRCC. Results We found that P4HB not only connects with immune cell infiltration and co-expression with PD-1, PD-L2, and CTLA-4, but also has a strong connection with the newly discovered hot gene, TOX. Conclusion We speculate that P4HB is a novel gene involved in the progression of pRCC through immunomodulation.

Keywords

• Carcinoma
• Renal cell
• Computational biology
• Prolyl hydroxylases
• Biological markers
• Immunotherapy