Identification of Mutator-Derived lncRNA Signatures of Genomic Instability for Promoting the Clinical Outcome in Hepatocellular Carcinoma

Background. Accumulating evidence proves that long noncoding RNA (lncRNA) plays a crucial role in maintaining genomic instability. However, it is significantly absent from exploring genomic instability-associated lncRNAs and discovering their clinical significance. Objective. To identify crucial mutator-derived lncRNAs and construct a predictive model for prognosis and genomic instability in hepatocellular carcinoma. Methods. First, we constructed a mutator hypothesis-derived calculative framework through uniting the lncRNA expression level and somatic mutation number to screen for genomic instability-associated lncRNA in hepatocellular carcinoma. We then selected mutator-derived lncRNA from the genome instability-associated lncRNA by univariate Cox analysis and Lasso regression analysis. Next, we created a prognosis model with the mutator-derived lncRNA signature. Furthermore, we verified the vital role of the model in the prognosis and genomic instability of hepatocellular carcinoma patients. Finally, we examined the potential relationship between the model and the mutation status of TP53. Results. In this study, we screened 88 genome instability-associated lncRNAs and built a prognosis model with four mutator-derived lncRNAs. Moreover, the model was an independent predictor of prognosis and an accurate indicator of genomic instability in hepatocellular carcinoma. Finally, the model could catch the TP53 mutation status, and the model was a more effective indicator than the mutation status of TP53 for hepatocellular carcinoma patients. Conclusion. This research adopted a reliable method to analyze the role of lncRNA in genomic instability. Besides, the prognostic model with four mutator-derived lncRNAs is an excellent new indicator of prognosis and genomic instability in hepatocellular carcinoma. In addition, this finding may help clinicians develop therapeutic systems.