A Stable Gene Set for Prediction of Prognosis and Efficacy of Chemotherapy in Gastric Cancer

Abstract

Background Gastric cancer is one of the leading causes of cancer-related death worldwide. How to eliminate gastric cancer is an urgent public health problem. Prediction of prognosis is critical to the development of clinical treatment regimens. The aim of this study was to establish a stable prognostic gene set to guide the clinical diagnosis and treatment of gastric cancer. Methods A public microarray dataset of TCGA providing clinical information was obtained. The selection operator regression method was used to reduce the dimensionality of stable prognostic genes identified via the bootstrap method and survival analysis. Conclusion We established two prognostic models, respectively designated as stable gene risk score of OS(SGRS-OS) and stable gene risk score of PFI(SGRS-PFI) consisting of 18 and 21 genes. With specific risk score formulae, the SGRS set possesses a strong ability to predict overall survival and progression-free interval through both univariate and multivariate analyses. Compared with the TNM stage, the SGRS set showed much higher predictive accuracy. Further analysis revealed that patients with higher SGRS exhibited worse chemotherapy outcomes. Our SGRS set may be an effective tool to predict survival and guide treatment in patients with gastric cancer.