Identification of a novel Immune-Related prognostic model for patients with colorectal cancer based on 3 subtypes

The mechanism of immunity in the development of colorectal cancer (CRC) has been studied in-depth, but knowledge of its role in the treatment of CRC is limited. This study aimed to classify CRC based on immunology and construct an immune-related prognostic model. Nine expression profile datasets of CRC, comprising 1640 samples, were downloaded from the NCBI GEO database. Immune infiltration of CRC was estimated using 5 algorithms. Based on the relative infiltration level of immune cells, immune score, and stromal score, immunosubtype analysis of tumors was conducted. Differentially expressed genes (DEGs) between the two subtypes were screened, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Hematoxylin eosin (HE) staining, immunohistochemical (IHC) staining and qPCR were used to verify the correlation between DEGs and differentiation degree of cancer and the expression of Ki67. Subsequently, a risk signature was constructed based on the least absolute shrinkage and selection operator (LASSO) model. Based on the infiltration level, immune score, and stromal score of each immune cell, CRC was divided into three immune cell subtypes. Most immune checkpoint genes showed highly significant differences among the three cell subtypes, and most of the co-stimulatory and co-inhibitory molecules were lower in cluster 1 and the highest in cluster 3. Next, 50 common DEGs were determined from the intersections of the different subtypes. Among these common DEGs, 25 were identified to be relevant to the prognosis of CRC patients. The mRNA expressions of C5orf46, CYP1B1, MIR100HG, SFRP2 and CXCL13 was related to clinical prognostic indicators. Finally, these 5 DEGs were included in a prognostic risk signature model, which effectively identified high-risk groups among CRC patients in both the training and validation sets. In this study, CRCs were divided into three subtypes based on immunology, and the different subtypes led to different prognosis. Additionally, a prognostic model was constructed based on five immune-related DEGs to distinguish the three subtypes.