Open AccessIdentification of a novel gene pairs signature in the prognosis of gastric cancer
Author(s) -
Peng PaiLan,
Zhou XiangYu,
Yi GuoDong,
Chen PengFei,
Wang Fan,
Dong WeiGuo
Publication year - 2018
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.1303
Subject(s) - proportional hazards model , concordance , medicine , hazard ratio , confidence interval , gene signature , oncology , stage (stratigraphy) , cancer , signature (topology) , gene , biology , gene expression , genetics , mathematics , paleontology , geometry
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 GSE 662254 ( n = 300, training set) and GSE 15459 ( n = 192, test set) were included into analysis. Prognostic genes were screened to construct prognosis‐related gene pairs ( PRGP s). Then, a penalized Cox proportional hazards regression model identified seven PRGP s, 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 PRGP s 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‐lnc RNA 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 .