Table3_A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies.XLSX

Abstract

Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers.Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model.Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.</p