Gene expression profiles contribute to robustly predicting prognosis in hepatocellular carcinoma  

作　　者：Long Liu Yuhui Wang Yuyuan Zhang Siyuan Weng Hui Xu Zaoqu Liu Xinwei Han 

机构地区：[1]Department of Hepatobiliary and Pancreatic Surgery,The First Affiliated Hospital of Zhengzhou University,Zhengzhou,Henan 450052,China [2]Prenatal Diagnosis Center,The Third Affiliated Hospital of Zhengzhou University,Zhengzhou,Henan 450052,China [3]Department of Interventional Radiology,The First Affiliated Hospital of Zhengzhou University,Zhengzhou,Henan 450052,China [4]Interventional Institute of Zhengzhou University,Zhengzhou,Henan 450052,China [5]Interventional Treatment and Clinical Research Center of Henan Province,Zhengzhou,Henan 450052,China

出　　处：《Genes & Diseases》2024年第2期593-596,共4页基因与疾病（英文）

基　　金：supported by the Henan Province Medical Research Project,Henan,China(No.LHGJ20190388).

摘　　要：Hepatocellular carcinoma(HCC)is characterized by both inter-and intra-tumor heterogeneity and has distinct clinical outcomes.1 A promising clinical tool to perform patient stratification,prognosis evaluation,and treatment recommendations is indispensable.Here,we enrolled a total of 1595 tumor patients from 13 independent cohorts,including seven cohorts with survival data,four cohorts with immunotherapy information,and two cohorts with transcatheter arterial chemoembolization(TACE)and Sorafenib information,respectively(Table S1).Using 96 algorithms combinations derived from 10 popular machinelearning approaches,a novel framework was constructed and described in Figure S1.Firstly,a total of 26 stable consensus prognostic genes were screened in seven cohorts harboring complete survival information via univariate Cox regression analysis(Fig.S2A).

关 键 词：PROGNOSIS CLINICAL ARTERIAL 

分 类 号：R735.7[医药卫生—肿瘤]