Chronic hepatitis B Virus (HBV) infection induces multi-step changes in the liver, involving liver fibrosis, liver cirrhosis (LC) and hepatocellular carcinoma (HCC) which is a deadly malignant tumor that lacks more effective diagnosis and treatment methods. Developing highly sensitive biomarkers could aid in early detection and intervention, improving survival rates. While numerous studies have analyzed HCC and healthy individuals, few have systematically studied HCC biomarkers from the perspective of progression changes. Here, we first constructed a comprehensive HCC-specific candidate biomarker bank, comprising up to 2968 proteins and 103 metabolites, based on the differentially expressed proteins identified by the current study, as well as HCC-related proteins and metabolites summarized from previous studies. We next determined the serum proteomics and metabolomics of 316 healthy controls and patients with HBV, HCV, LC and HCC, and constructed a cancerous trajectory of liver diseases using our DeepPRM targeted method. Based on and the machine learning-based computational pipeline, we found an 8-biomolecular based biomarker combination (accuracy rate: 91.43%) which can be used for the early diagnosis of HCC. Meanwhile, a 12-biomolecular based biomarker combination (accuracy rate: 80.00%) was identified for revealing the alterations in HBV–LC progression. This extensive circulating biomarker development study provides wealthy proteomic and metabolic data resources for better understanding of cancer biology processes in liver diseases.