A novel assessing system for predicting the prognosis of gastric cancer

Abstract

Aim: To develop novel diagnostic tools that can predict the prognosis of gastric cancer. Material & methods: Using RNA expression data from The Cancer Genome Atlas and Gene Expression Omnibus, we established protein-coding RNAs-noncoding RNAs-tumor microenvironment type (PNM) scores, which contain signatures of tumor protein coding genes (P), tumor noncoding genes (N) and immune/stroma cells in tumor microenvironment (M) to predict the prognosis of gastric cancer. Results & conclusion: Based on PNM scores, gastric cancer patients were divided into three subgroups and Kaplan–Meier survival curves revealed significant differences among the subgroups (p < 0.001). Our study showed that the PNM scores could be used as a robust predicting tool for the prognosis of gastric cancer.