An early relapse-associated gene signature optimizes prognostic prediction for gastric cancer patients

Abstract Background: Gastric cancer (GC) is one of the most common cancers in the world. Patients with GC who experienced early relapse have poor prognosis. We aim to develop an early relapse-associated gene signature to optimize prognosis prediction in patients with replapsing GC. Methods: The GC cohorts including GSE62254 set (N=300) and GSE15459 set (N=192) were extracted from Gene Expression Omnibus (GEO) database. Propensity score matching (1:1) based on pathological stage was executed between patients with early relapse and long-term survival from GSE62254 set. Global transcriptome analysis was performed between the two groups to identify early relapse-associated gene. Based on the differentially expressed genes, we developed a classifier incorporating 5 genes that using LASSO Cox regression model. The signature’s prognostic value was internally validated in 210 GC patients and validated in GSE15459 set externally. The patients from GSE62254 set could be divided into high-risk or low-risk group.Results: In the train set, patients in high-risk group had poor prognosis as compared to those in low-risk group [hazard ratio (HR): 3.002, 95% confidence interval (CI): 2.132-4.226, P<0.001)]. Good reproducibility for the prognostic value of early relapse-associated gene signature was verified in the internal validation set (HR: 2.772, 95% CI: 1.836–4.184, P<0.001) and another external validation set (HR: 1.733, 95% CI: 1.149–2.614, P=0.009). Also, we developed a nomogram which integrated the five mRNA classifier, pathological stage and lymph node ratio (LNR) to evaluate prognosis based on GSE62254 set. Time-dependent receiver-operating characteristic at 1 year demonstrated that integrated signature had better prognostic accuracy [area under curve (AUC=0.849)] than the American Joint Commission on Cancer TNM staging system (AUC=0.773) and LNR (AUC=0.811) in GSE62254 set. Conclusions: This study suggest that an early relapse-associated gene signature that can robustly divide gastric cancer patients into two groups with distinctive prognosis. This classifier may contribute to select gastric cancer patients with poor prognosis who require more frequent follow-up and more aggressive therapeutic intervention.