An Integrative Multi-Omic Biomarker Panel Distinguishes Hepatocellular Carcinoma From Chronic Liver Disease in HBV-Predominant Populations.

Abstract

Aim: DNA methylation is a promising diagnostic biomarker for various cancers including hepatocellular carcinoma (HCC). We aimed to identify aberrant DNA methylation and protein alterations via integrated approaches and develop a highly predictive biomarker panel for blood-based discrimination of HCC from non-HCC chronic liver disease (CLD) in an HBV-predominant population.

Methods: Genome-wide methylation profiling was conducted to screen hypermethylated CpG sites and genes distinguishing 55 HCC and matched non-HCC tissues. Candidate marker genes were then evaluated with five protein markers in 299 blood samples, and a diagnostic model was developed and validated in an independent cohort of 149 participants.

Results: Methylation pattern analysis identified 44 candidate hypermethylation biomarkers using four strategies. Through cross-validation, a panel of six methylation markers from four different groups yielded an AUC of 0.938, surpassing other methylation marker panels. A logistic regression model incorporating four DNA methylation markers and two protein markers achieved sensitivities of 91.8% and 88.4% at specificities of 95.4% and 93.8% in the training and validation sets, respectively. The 6-marker panel showed higher sensitivity of 82.9% for BCLC 0-A HCC, outperforming alpha-fetoprotein (AFP), and des-gamma-carboxyprothrombin (DCP).

Conclusions: The developed 6-marker model demonstrated strong diagnostic performance for distinguishing HCC from non-HCC CLD in the studied HBV-predominant cohorts. It outperformed AFP and DCP in this case-control setting and may have potential for blood-based HCC detection. Prospective validation in surveillance cohorts is required before clinical implementation.