Identification of a novel gene pairs signature in the prognosis of gastric cancer

Abstract

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.

We used a novel method to identify a prognostic signature in gastric cancer, which removed the batch effects. The signature also showed a better predictive accuracy than other prognostic signatures.

from #ORL-AlexandrosSfakianakis via ola Kala on Inoreader http://ift.tt/2zFrMrB