Development and Validation of a Metabolic Gene-Based Prognostic Signature for Hepatocellular Carcinoma

Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

Background

Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence.

Methods

The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database.

Results

Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group.

Conclusions

Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08827-z.

Prognostic and predictive role of a metabolic rate-limiting enzyme signature in hepatocellular carcinoma

OBJECTIVES

Abnormal expression of metabolic rate-limiting enzymes drives the occurrence and progression of hepatocellular carcinoma (HCC). This study aimed to elucidate the comprehensive model of metabolic rate-limiting enzymes associated with the prognosis of HCC.

MATERIALS AND METHODS

HCC animal model and TCGA project were used to screen out differentially expressed metabolic rate-limiting enzyme. Cox regression, least absolute shrinkage and selection operation (LASSO) and experimentally verification were performed to identify metabolic rate-limiting enzyme signature. The area under the receiver operating characteristic curve (AUC) and prognostic nomogram were used to assess the efficacy of the signature in the three HCC cohorts (TCGA training cohort, internal cohort and an independent validation cohort).

RESULTS

A classifier based on three rate-limiting enzymes (RRM1, UCK2 and G6PD) was conducted and serves as independent prognostic factor. This effect was further confirmed in an independent cohort, which indicated that the AUC at year 5 was 0.715 (95% CI: 0.653-0.777) for clinical risk score, whereas it was significantly increased to 0.852 (95% CI: 0.798-0.906) when combination of the clinical with signature risk score. Moreover, a comprehensive nomogram including the signature and clinicopathological aspects resulted in significantly predict the individual outcomes.

CONCLUSIONS

Our results highlighted the prognostic value of rate-limiting enzymes in HCC, which may be useful for accurate risk assessment in guiding clinical management and treatment decisions.