Clinical application value of long non-coding RNAs signatures of genomic instability in predicting prognosis of hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma (HCC) presents challenges due to its high recurrence and metastasis rates and poor prognosis. While current clinical diagnostic and prognostic indicators exist, their accuracy remains imperfect due to their biological complexity. Therefore, there is a quest to identify improved biomarkers for HCC diagnosis and prognosis. By combining long non-coding RNA (lncRNA) expression and somatic mutations, Duan et al identified five representative lncRNAs from 88 lncRNAs related to genomic instability (GI), forming a GI-derived lncRNA signature (LncSig). This signature outperforms previously reported LncSig and TP53 mutations in predicting HCC prognosis. In this editorial, we comprehensively evaluate the clinical application value of such prognostic evaluation model based on sequencing technology in terms of cost, time, and practicability. Additionally, we provide an overview of various prognostic models for HCC, aiding in a comprehensive understanding of research progress in prognostic evaluation methods.