A novel cuproptosis-related signature for predicting prognosis and immune response in gastric cancer

Abstract

Abstract Cuproptosis is a novel non-apoptotic programmed cell death distinguished from classical cell death. However, the direct prognostic value of cuproptosis-related genes (CRGs), and corresponding detailed mechanisms in gastric cancer (GC) remain unknown. Here, we collected RNA-sequencing data, copy number variation, single nucleotide variation and clinical information of GC from TCGA database. Then, two distinct cuproptosis-related clusters were established based on the expression patterns of 13 CRGs using consensus unsupervised clustering analysis. Based on the differentially expressed genes with prognostic value between the two CRGs clusters, a predictive signature was developed which divided all patients into high- and low-risk two groups. It was found that patients in the low-risk group showed better survival prognosis than those in the high-risk group. Moreover, the accuracy of this model in prognostic prediction was further confirmed in two independent GEO cohorts. Univariate and multivariate Cox regression analyses demonstrated that the CRG score was an independent prognostic predictor for GC patients. In addition, there were also an obvious differences of immune cells infiltration and tumor mutation burden (TMB) between the two groups. Meanwhile, this signature could help to predict chemotherapeutic drug sensitivity and immunotherapy efficacy in GC patients. Collectively, we demonstrated a comprehensive overview of CRG profiles in GC and established a novel risk model for the prediction of therapy effect and prognosis in GC patients.