A new strategy for the treatment of hepatitis B patients based on data mining

Abstract

Hepatitis B virus (HBV) infection is a major risk factor for hepatocellular carcinoma. Currently, there are still many limitations in the therapeutic approaches for HBV infection. During the antiviral process, inhibiting viral transmission, blocking the viral replication cycle, and slowing its progression to hepatocellular carcinoma are the keys to treatment. With this goal in mind, this paper proposes a new therapeutic strategy in addition to antiviral therapy for patients who are infected with HBV but have not yet become cancerous by mining transcriptomics data from relevant samples. Our contribution is mainly to find specific receptors and ligands in the cell cycle of HBV-infected patients that can be used as targets for drug administration, which is useful for understanding and intervening in the progression of hepatitis B to hepatocellular carcinoma, and also brings a fresh perspective to antiviral therapy.