Multi-omics biomarker detection in Diethylnitrosamine (DENA) induced hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is frequently diagnosed at an advanced stage due to tumor heterogeneity and chronic liver damage, which reduce the performance of single biomarkers and complicate the clinical interpretation of laboratory results. The genotoxic diethylnitrosamine (DENA)-induced hepatocarcinogenesis model provides a stage-resolved and experimentally controlled framework associated with genotoxic stress, inflammation, and fibrosis, along with metabolic adaptation in target tissues and circulating biofluids. This review summarizes multi-omics data from DENA models and translational cohorts, encompassing genomics/epigenomics, transcriptomics, proteomics, metabolomics, and glycomics, as well as liquid biopsy analytes, including cell-free DNA, extracellular vesicle cargo, and circulating tumor cell markers. We integrated the dynamics of injury progression to fibrosis and tumor development at the pathway scale, highlighting multi-analyte biomarker sets that improve the differentiation between advanced fibrosis/cirrhosis and early hepatocellular carcinoma (HCC). Additionally, we examined enabling technologies in analytical techniques, including targeted mass spectrometry (MS), PCR-based methods, and clinically scalable glycoprofiling. Notably, we propose a stage-aware biomarker selection paradigm that emphasizes mechanistic consistency, analytical viability, and clinical actionability to facilitate earlier identification and longitudinal tracking. Finally, we discuss the practical implications of multicenter validation and a harmonized study design to enhance reproducibility and expedite clinical translation.