Background: Hepatocellular carcinoma (HCC) is a malignant tumour with a poor
prognosis. The effect of DNA repair on prognosis cannot be ignored, and long non-coding RNA
(lncRNA) can regulate the DNA repair process.
Objective: To obtain DNA repair-associated lncRNA (DR-lncRNA) prognostic signature for
improving the ability to predict HCC prognosis.
Methods: Our study used the Cancer Genome Atlas database. Gene set variation analysis was
performed to differentiate high and low levels of DNA repair to identify DR-lncRNAs. By
performing univariate Cox regression, LASSO regression, and multivariate Cox regression
analyses, we finally obtained a DR-lncRNA prognostic signature and constructed a nomogram
prognostic model. Time-dependent receiver operating characteristic (ROC) curves, calibration
plots, decision curve analysis (DCA), and clinical impact curves were used to assess predictive
ability and clinical utility. Differentially expressed genes (DEGs) functional enrichment analysis
was performed to further explore the underlying mechanisms that influence HCC prognosis.
Results: We obtained the following DR-lncRNA prognostic signature:AP002478.1, AC116351.1,
LINC02580, and LINC00861. The ROC curves and calibration plots showed good discrimination
and calibration properties. Combining the DR-lncRNA prognostic signature and tumour stages, we
established a nomogram prognostic model. DCA and clinical impact curves showed the clinical
utility of this model. DEGs of high-risk and low-risk groups predicted by the prognostic DRlncRNA
were significantly associated with cell cycle, various metabolic pathways and biological
processes, such as the oxidation-reduction process and cell division.
Conclusion: We identified a DR-lncRNA prognostic signature and constructed a nomogram
prognostic model, which could be a beneficial prognostic strategy for HCC.