Characterization of an endoplasmic reticulum stress-related signature to predict prognosis in Colorectal Adenocarcinoma

Abstract Background Colorectal cancer (CRC) is a malignant tumor of the digestive tract with high incidence and mortality rates. Colorectal adenocarcinoma (COAD) is accounting for the majority of CRC. Endoplasmic reticulum stress-related genes play a role in cancer. This study aimed to develop a novel prognostic risk model for COAD based on endoplasmic reticulum stress-related genes, providing theoretical support for prognosis and clinical treatment ofCOAD. Methods Two cohorts, The cancer genome atlas (TCGA)- COAD cohort and GSE39582 dataset were enrolled in the study. The differentially expressed genes (DEGs) were determined using the ‘limma’ R package. The ‘clusterProfiler’ R package was utilized to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Univariate and multivariate Cox analyses were performed to identify the prognostic genes. The risk score model was constructed and verified by internal and external cohorts. We analyzed the changes of enriched pathways in the high- and low-risk groups by gene set variation analysis(GSVA). The immune infiltration landscape was calculated by single sample gene set enrichment analysis (ssGSEA) and the immunotherapy response was assessed by the Tumour Immune Dysfunction and Exclusion (TIDE) algorithm. The expression of prognostic genes in clinically normal and COAD samples was verified by Real Time Quantitative polymerase chain reaction (RT-qPCR). Results A total of 147 differentially expressed endoplasmic reticulum stress-related genes (DE-ERSGs) in COAD were identified. We screened eight prognostic genes to construct endoplasmic reticulum stress-related gene signature through Cox regression analysis in the training set of TCGA-COAD cohort. Then we validated the risk score model by a testing set of TCGA-COAD cohort and GSE39582 cohort. The univariate and multivariate Cox regression analysis demonstrated the risk score was a robust independent prognostic factor in overall survival prediction. The GSVA also suggested that the gene signature was related to the immune-related pathways. The result of ssGSEA implied that there were significant differences in the immune microenvironment between the high- and low-risk groups. The TIDE analysis revealed that the risk score could predict the clinical response of immunotherapy. The result of RT-qPCR demonstrated that the expression trends of prognostic genes in clinical samples were consistent with the result from public database. Conclusion Our study identified prognostic endoplasmic reticulum stress-related genes and established a novel risk signature, which could predict prognosis in COAD patients and provide theoretical support for clinical treatment of COAD.