A Ten-Long Non-coding RNA Model Improves Prognosis Prediction of Hepatocellular Carcinoma Patients

被引：0

作者：

Fang, Xiaonan ^{[1
,2
]}

Liu, Naiwen ^{[2
]}

Du, Yanling ^{[3
]}

Yuan, Feng ^{[2
]}

Li, Yongqin ^{[4
]}

机构：

[1] Shandong Normal Univ, Coll Life Sci, Shandong Prov Key Lab Anim Resistance Biol, Jinan, Shandong, Peoples R China

[2] Shandong Management Univ, Key Lab TCM Data Cloud Serv Univ Shandong, Jinan, Shandong, Peoples R China

[3] Shandong Univ Tradit Chinese Med, Coll Sci & Technol, Jinan, Shandong, Peoples R China

[4] Shandong Normal Univ, Fac Educ, Jinan, Shandong, Peoples R China

来源：

2018 NINTH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY IN MEDICINE AND EDUCATION (ITME 2018) | 2018年

关键词：

hepatocellular carcinoma; cox survival analysis; long noncoding RNAs; differential expression analysis; EXPRESSION; CANCER;

D O I：

10.1109/ITME.2018.00018

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, the lncRNA expression profiles of 424 hepatocellular carcinoma (HCC) patients, including 374 tumor and 50 adjacent non-tumor tissues, from The Cancer Genome Atlas (TCGA) were analyzed. By univariate and multivariate Cox survival analysis, we found and validated 10 significant lncRNAs associated with HCC prognosis. Based on the risk calculation model established on these 10 lncRNAs, HCC patients samples could be divided into high-risk and low-risk groups, and the survival rates of patients in these two groups are significantly different. Our research provides data to further understand the molecular mechanisms implicated in HCC and to improve diagnosis, treatment and prognosis used for HCC patients.

引用

页码：29 / 33

页数：5

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