A five lncRNA signature for prognosis prediction in hepatocellular carcinoma

This study was conducted to screen prognosis-associated long-noncoding RNAs (lncRNAs) and a prognosis assessment model in hepatocellular carcinoma (HCC). lncRNA- and mRNA-sequencing data of early-stage HCC samples were downloaded from The Cancer Genome Atlas database. The samples were divided into training set and validation set. Differentially expressed lncRNAs (DELs) between poor prognosis and good prognosis samples were screened with DEseq and edgeR. Cox regression analysis was conducted to identify prognosis-associated lncRNAs in the training set. A prognosis risk assessment model was established to calculate the risk score for each patient in the training set, and the prognosis prediction function was tested and validated in the validation dataset. The connection between the risk assessment model and clinical features was analyzed. A co-expression network between lncRNAs and corresponding genes was constructed, and functional enrichment was performed for these genes. A total of 81 DELs were screened between poor and good prognosis samples in the training set, and 43 prognosis-associated lncRNAs were observed. Of these DELs, five were used to construct the risk assessment model (RP11-325L7.2, DKFZP434L187, RP11-100L22.4, DLX2-AS1 and RP11-104L21.3). Low-risk samples exhibited longer survival time compared with the high-risk samples. The five lncRNAs exhibited significant differences in expression levels between different prognosis groups. Risk score was an independent prognostic factor for HCC. In the entire set, the low-risk group demonstrated significantly better prognosis compared with the high-risk group, even across all age, sex and alcohol consumption subgroups. Nucleoside-triphosphatase regulator activity', GTPase regulator activity', enzyme binding', peroxisome proliferator-activated receptor signaling pathway' and fatty acid metabolism' were the most significantly enriched functional terms. The signature lncRNAs screened in this study may have constitute novel strategies and biomarkers that predict the prognosis of HCC, and these may also contribute to a deeper understanding of the mechanisms underlying HCC development.