Construction of a Metabolism-Related Long Non-Coding RNAs-Based Risk Score Model of Hepatocellular Carcinoma for Prognosis and Personalized Treatment Prediction.

ABSTRACT: Background: Long non-coding RNAs (lncRNAs) play a key regulatory role in tumor metabolism. Although hepatocellular carcinoma (HCC) is a metabolic disease, there have been few systematic reports on the association between lncRNA expression and metabolism in HCC. Results: In this study, we screened 557 metabolism-related lncRNAs in HCC. A risk score model based on 13 metabolism-related lncRNA pairs was constructed to predict the outcome and drug response in HCC. The risk score model presented a better prediction of the outcomes than that with common clinicopathological characteristics, such as tumor stage, grade, and status and aneuploidy score in both training and testing cohorts. In addition, patients in the high-risk group exhibited higher responses to gemcitabine and epothi

SUBMITTER: Zhang P 

PROVIDER: S-EPMC9171512 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature