biostudies-literaturePeng PLNational Natural Science Foundation of China344-350https://www.ebi.ac.uk/biostudies/studies/S-EPMC5806102biostudies-literatureUnknown7(2)Current prognostic signatures need to be improved in identifying high-risk patients of gastric cancer (GC). Thus, we aimed to develop a reliable prognostic signature that could assess the prognosis risk in GC patients. Two microarray datasets of GSE662254 (n = 300, training set) and GSE15459 (n = 192, test set) were included into analysis. Prognostic genes were screened to construct prognosis-related gene pairs (PRGPs). Then, a penalized Cox proportional hazards regression model identified seven PRGPs, which constructed a prognostic signature and divided patients into high- and low-risk groups according to the signature score. High-risk patients showed a poorer prognosis than low-risk patients in both the training set (hazard ratios [HR]: 6.086, 95% confidence interval [CI]: 4.341-8.533) and test set (1.773 [1.107-2.840]). The PRGPs signature also achieved a higher predictive accuracy (concordance index [C-index]: 0.872, 95% CI: 0.846-0.897) than two existing molecular signatures (0.706 [0.667-0.744] for a 11-gene signature and 0.684 [0.642-0.726] for a 24-lncRNA signature) and TNM stage (0.764 [0.715-0.814]). In conclusion, our study identified a novel gene pairs signature in the prognosis of GC.Cancer medicineIdentification of a novel gene pairs signature in the prognosis of gastric cancer.PMC580610281372551Chen PFDong WGPeng PLZhou XYWang FYi GDfalseIdentification of a novel gene pairs signature in the prognosis of gastric cancer.Current prognostic signatures need to be improved in identifying high-risk patients of gastric cancer (GC). Thus, we aimed to develop a reliable prognostic signature that could assess the prognosis risk in GC patients. Two microarray datasets of GSE662254 (n = 300, training set) and GSE15459 (n = 192, test set) were included into analysis. Prognostic genes were screened to construct prognosis-related gene pairs (PRGPs). Then, a penalized Cox proportional hazards regression model identified seven PRGPs, which constructed a prognostic signature and divided patients into high- and low-risk groups according to the signature score. High-risk patients showed a poorer prognosis than low-risk patients in both the training set (hazard ratios [HR]: 6.086, 95% confidence interval [CI]: 4.341-8.533) and test set (1.773 [1.107-2.840]). The PRGPs signature also achieved a higher predictive accuracy (concordance index [C-index]: 0.872, 95% CI: 0.846-0.897) than two existing molecular signatures (0.706 [0.667-0.744] for a 11-gene signature and 0.684 [0.642-0.726] for a 24-lncRNA signature) and TNM stage (0.764 [0.715-0.814]). In conclusion, our study identified a novel gene pairs signature in the prognosis of GC.2018-01-01T00:00:00Z2018 Feb2024-11-19T18:57:12.341Z2019-03-26T23:02:54ZS-EPMC58061022928289110.1002/cam4.1303