Identification and validation of a pyroptosis-related prognostic model for colorectal cancer

In this study, we explored the pyroptosis-related biomarkers and signatures of colorectal cancer (CRC). Gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA)-COADREAD and were analyzed for differentially expressed genes (DEGs). DEGs in CRC‒pyroptosis-related genes (CRC‒PRGs) were obtained by intersecting DEGs associated with CRC and PRGs. The CRC‒PRGs were verified; functional enrichment analysis was performed with Gene Ontology (GO) followed by cluster analysis. Cox analyses and LASSO regression were used in TCGA dataset to construct a prognostic model for patients with CRC. A prognostic risk assessment model was constructed and efficacy was evaluated. Decision curve analysis was utilized to assess the role of the Lasso-Cox regression prognostic model for clinical utility at 1, 3, and 5 years. Twelve CRC‒PRGs were identified as prognostic pyroptosis-related DEGs. CXCL8, IL13RA2, MELK, and POP1 were selected as prognostic genes to construct features with a good prognostic performance in GEO and TCGA. Functional enrichment indicated that the 4-gene signature might be involved in CRC tumorigenesis and development through various pathways by playing a prognostic role in CRC. Furthermore, the results of the immune landscape analysis showed that the expression of CXCL8 and IL13RA2 in TCGA-COADREAD dataset was positively correlated with significant differential enrichment of most immune cells. A novel prognostic model consisting of four key genes, CXCL8, IL13RA2, MELK, and POP1, can accurately predict the survival of patients with CRC. This finding may provide a new perspective for the treatment of pyroptosis-related CRC.