A New Prognostic Strategy Based on four DNA Repair-Associated lncRNAs for Hepatocellular Carcinoma.

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.