A 16‐mRNA signature optimizes recurrence‐free survival prediction of Stages II and III gastric cancer

Abstract High‐throughput messenger RNA (mRNA) analysis has become a powerful tool for exploring tumor recurrence or metastasis mechanisms. Here, we constructed a signature to predict the recurrence risk of Stages II and III gastric cancer (GC) patients. A least absolute shrinkage and selection operator method Cox regression model was utilized to construct the signature. Using this method, a 16‐mRNA signature was identified to be associated with the relapse‐free survival of Stages II and III GCs in training dataset GSE62254 ( n = 194). Then this signature was validated in an independent Gene Expression Omnibus cohort GSE26253 ( n = 297) and a dataset of The Cancer Genome Atlas (TCGA; n = 235). This classifier could successfully screen out the high‐risk Stages II and III GCs in the training cohort (hazard ratio [HR] = 40.91; 95% confidence interval [CI] = 5.58–299.7; p < .0001). Analysis in two independent validation cohorts yielded consistent results (GSE26253: HR = 1.69, 95% CI = 1.17–2.43,; p = .0045; TCGA: HR = 2.01, 95% CI = 1.13–3.56, p = .0146). Cox regression analyses revealed that the risk score derived from this signature was an independent risk factor in Stages II and III GCs. Besides, a nomogram was constructed to serve clinical practice. Through gene set variation analysis, we found several gene sets associated with chemotherapeutic drug resistance and tumor metastasis significantly enriched in high‐risk patients. In summary, this 16‐mRNA signature can be used as a powerful tool for prognostic evaluation and help clinicians identify high‐risk patients.