Significance of immunogenic cell death-related prognostic gene signature in cervical cancer prognosis and anti-tumor immunity

Abstract

BACKGROUND Immunogenic cell death (ICD) can reshape the tumor immune microenvironment, and ICD, as a type of regulated cell death, activates the adaptive immunity of the body to achieve better therapeutic results through direct tumor cell killing. ICD has never been associated with cervical cancer (CC), hence the purpose of this research was to find and evaluate ICD-related genetic characteristics as cervical cancer prognostic ators. METHODS Data of CC patients from The Tumor Genome Atlas (TCGA) was used as the basis to obtain immunogenic cell death-related prognostic genes (IPGs) in patients with CC, using the least absolute shrinkage and selection operator and Cox regression screening, and the IPGs scoring system was constructed to classify patients into high- and low-risk groups, with the Gene Expression Omnibus (GEO) dataset as the validation group. Finally, the difference analysis of single-sample gene set enrichment analysis, tumor microenvironment (TME), immune cells, tumor mutational burden, and chemotherapeutic drug sensitivity between the high-risk and low-risk groups was investigated. The PDIA3 gene was identified as the major gene in immunogenic death-related genes (IRG) with the greatest hazard ratio (HR), and in vitro experiments were performed to confirm its expression in colorectal cancer (CC) and its influence on the prognosis of the patient. RESULTS A prognostic model with four IPGs (PDIA3, CASP8, IL1 and LY96) was developed, and it was found that the group of CC patients with a higher risk score of IPG expression had a lower survival rate. Multiple regression analysis also showed that this risk score was a reliable predictor of overall survival (HR = 1.058, P 0.01). In comparison to the low-risk group, the high-risk group had lower TME scores and immune cell infiltration, and gene set variation analysis showed that immune-related pathways were more enriched in the high-risk group. Chemotherapeutic drug sensitivity analysis revealed that IC50 value of common chemotherapeutic agents for CC was lower in the high-risk compared with that in the low-risk group. In addition, high expression of the PDIA3 gene, a key gene in IPGs, was linked to worse patient prognosis. CONCLUSION A risk model constructed from four IPGs can independently predict the prognosis of CC patients and recommend more appropriate immunotherapy strategies for patients.