Characteristics of endoplasmic reticulum stress in colorectal cancer for predicting prognosis and developing treatment options.

Abstract

An increasing body of evidence supports an essential role for endoplasmic reticulum stress (ERS) in colorectal cancer (CRC). In this study, we developed an ERS-related genes (ERSRGs) model to aid in the prognostic evaluation and treatment of CRC patients. The training set and validation set data were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. ERSRGs were obtained from the GeneCards database. A prognostic risk scoring model was constructed using the least absolute shrinkage and selection operator (LASSO) along with univariate Cox regression analysis. To further predict the probability of survival for patients at 1, 2, and 3 years, a nomogram was devised. The advantages of the prognostic risk score model in screening patients' sensitive to chemotherapy and immunotherapy were analyzed by drug sensitivity analysis and immune correlation analysis. Finally, hub genes associated with poor prognosis in the risk model were screened by Protein-protein interaction (PPI) network and their expression was validated using clinical specimens. A risk model for overall survival (OS) was developed using 16 ERSRGs associated with prognosis. Through analyses, we demonstrated a high degree of reliability for the prognostic risk scoring model. The constructed nomograms performed well in predicting patient survival over 1, 3, and 5 years. The calibration curve and decision curve analysis (DCA) supported a high degree of accuracy for the model. Patients in the low-risk group had a lower IC50 for the common chemotherapy drug, 5-FU, and responded better to immunotherapy. hub poor prognostic genes were validated in CRC clinical specimens. We have identified and validated a new ERS prognostic marker that can accurately predict the survival status of CRC patients for clinicians and better provide personalized treatment plans.