Comprehensive Molecular Analyses of a Six-Gene Signature for Predicting Late Recurrence of Hepatocellular Carcinoma

Abstract

A larger number of patients with stages I–III hepatocellular carcinoma (HCC) experience late recurrence (LR) after surgery. We sought to develop a novel tool to stratify patients with different LR risk for tailoring decision-making for postoperative recurrence surveillance and therapy modalities. We retrospectively enrolled two independent public cohorts and 103 HCC tissues. Using LASSO logical analysis, a six-gene model was developed in the The Cancer Genome Atlas liver hepatocellular carcinoma (TCGA-LIHC) and independently validated in GSE76427. Further experimental validation using qRT-PCR assays was performed to ensure the robustness and clinical feasible of this signature. We developed a novel LR-related signature consisting of six genes. This signature was validated to be significantly associated with dismal recurrence-free survival in three cohorts TCGA-LIHC, GSE76427, and qPCR assays [HR: 2.007 (1.200–3.357), p = 0.008; HR: 2.171 (1.068, 4.412), p-value = 0.032; HR: 3.383 (2.100, 5.450), p-value <0.001]. More importantly, this signature displayed robust discrimination in predicting the LR risk, with AUCs being 0.73 (TCGA-LIHC), 0.93 (GSE76427), and 0.85 (in-house cohort). Furthermore, we deciphered the specific landscape of molecular alterations among patients in nonrecurrence (NR) and LR group to analyze the mechanism contributing to LR. For high-risk group, we also identified several potential drugs with specific sensitivity to high- and low-risk groups, which is vital to improve prognosis of LR-HCC after surgery. We discovered and experimentally validated a novel gene signature with powerful performance for identifying patients at high LR risk in stages I–III HCC.