Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma - Zhang, Zunyi; Chen, Weixun; Luo, Chu; Zhang, Wei (Frontiers in Pharmacology, 2022)
Background: Liver cancer is a lethal cancer type and hepatocellular carcinoma (HCC) is the most common and known type in liver cancer globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs are reported to result in drug resistance. In the present study, we aimed to identify key lncRNAs associated with doxorubicin resistance and HCC prognosis. Materials and Methods: Gene expression profiles with clinical information of HCC samples were accessed from public databases. We used differential analysis to identify key differential lncRNAs between HCC and normal samples, drug-fast and control samples. Univariate Cox regression analysis was used to screen lncRNAs or genes associated with HCC prognosis. Least absolute shrinkage and selection operator (LASSO) was employed to determine key prognostic genes. Receiver operation characteristic analysis was used to validate the effectiveness of the risk model. Results: RNF157-AS1 was identified as a key lncRNA associated with both doxorubicin resistance and HCC prognosis. Metabolic pathways such as fatty acid metabolism and oxidative phosphorylation were found to be enriched in RNF157-AS1-related genes. Four protein-coding genes including CENPP, TSGA10, MRPL53, and BFSP1 were determined by LASSO to construct a risk model. The four-gene risk model was effective to classify HCC samples into two risk groups with different overall survival. Finally, we established a nomogram which showed a superior performance in predicting long-term prognosis for HCC. Conclusions: RNF157-AS1 was considered to be possibly involved in doxorubicin resistance and may serve as a potential therapeutic target. The four-gene risk model had a potential value to predict HCC prognosis.