Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma  

作　　者：Jin-Cheng Guo Yang Wu Yang Chen Feng Pan Zhi-Yong Wu Jia-Sheng Zhang Jian-Yi Wu Xiu-E Xu Jian-Mei Zhao En-Min Li Yi Zhao Li-Yan Xu 

机构地区：[1]Key Laboratory of Molecular Biology in High Cancer Incidence Coastal Chaoshan Area of Guangdong Higher Education Institutes,Shantou University Medical College,Shantou,Guangdong 515041,P.R.China [2]Department of Biochemistry and Molecular Biology,Shantou University Medical College,Shantou,Guangdong 515041,P.R.China [3]Departments of Oncology Surgery,Shantou Central Hospital,Affiliated Shantou Hospital of Sun Yat-Sen University,Shantou,Guangdong 515041,P.R.China [4]Institute of Oncologic Pathology,Shantou University Medical College,Shantou,Guangdong 515041,P.R.China [5]Key Laboratory of Intelligent Information Processing,Advanced Computer Research Center,State Key Laboratory of Computer Architecture,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,P.R.China

出　　处：《Cancer Communications》2018年第1期50-62,共13页癌症通讯（英文）

基　　金：supported by the Natural Science Foundation of China-Guangdong Joint Fund(Grant Numbers U1301227,U0932001);the National Natural Science Foundation of China(Grant Numbers 81360331,81472613,81572341);the Science&Technology Planning Project of Guangdong Province(Grant Number 2014A030304060);the Department of Education,Guangdong Government under the Top-tier University Development Scheme for Research and Control of Infectious Diseases.

摘　　要：Background:Esophageal squamous cell carcinoma(ESCC)is the predominant subtype of esophageal carcinoma in China.This study was to develop a staging model to predict outcomes of patients with ESCC.Methods:Using Cox regression analysis,principal component analysis(PCA),partitioning clustering,Kaplan-Meier analysis,receiver operating characteristic(ROC)curve analysis,and classification and regression tree(CART)analysis,we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 dataset.Results:Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes(PCGs)and 635 long non-coding RNAs(lncRNAs)were associated with the survival of patients with ESCC.PCA categorized these PCGs and lncRNAs into three principal components(PCs),which were used to cluster the patients into three groups.ROC analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging(area under ROC curve[AUC]:0.69 vs.0.65,P<0.05).Accord-ingly,we constructed a molecular disaggregated model comprising one lncRNA and two PCGs,which we desig-nated as the LSB staging model using CART analysis in the GSE63624 dataset.This LSB staging model classified the GSE63622 dataset of patients into three different groups,and its effectiveness was validated by analysis of another cohort of 105 patients.Conclusions:The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

关 键 词：Long non-coding RNA Protein-coding gene Esophageal squamous cell carcinoma Overall survival Staging model TRANSCRIPTOME 

分 类 号：R73[医药卫生—肿瘤]