慢性HBV感染可造成肝癌等严重肝脏疾病。现有药物的疗效有限，仅能在部分患者中实现治疗应答。有效的基线预测指标，对提高治疗效率具有重要意义。研究表明，慢性乙肝(CHB)患者血清病毒水平是影响治疗应答的重要因素，目前常用核酸/免疫检测测定HBV DNA水平/病毒抗原水平，间接指示感染者体内病毒水平。但对于患者血清病毒的直接感染活力，目前尚无成熟测定方法，更缺乏对其临床意义的系统研究。在前期工作中，我们基于HepG2-NTCP细胞结合小分子促进剂建立了可支持血清样品直接感染的优化细胞模型，并首次发现CHB病人基线血清HBV感染力与PEG-IFN治疗应答高度相关。有鉴于此，本项目拟进一步通过CHB病人治疗队列、HBV细胞感染模型、FRG人肝嵌合小鼠模型，系统研究基线血清HBV感染力在疗效预测中的临床价值并阐释其病毒学机制。预期成果将为慢性乙肝提供新的疗效预测方法，并有助于HBV感染机制的深入理解。

Chronic HBV infection can cause severe liver diseases such as liver cancer. The efficacies of approved drugs are limited, only a small fraction of patients can achieve treatment response via regular anti-HBV regimen. Effective baseline predictors are important for improvement of therapeutic efficiency. Previous studies had demonstrated that the viral load is a key factor associated with post-treatment response. Currently, quantification of the levels of HBV DNA or viral antigens by nucleic acid tests or immunoassays are clinically used to indicate patients’ viral loads indirectly. So far, there is no satisfactory method for direct evaluation of the infectivity of patient’s serum samples, and the clinical significance of infectious titer of patient’s serum samples are still largely unknown. We had developed a robust in vitro HBV infection system supporting in vitro infection of patient’s sera based on the small compound agonist treated HepG2-NTCP cells. Using the system, we revealed the significant association between baseline serum infectivity and treatment response in chronic hepatitis B patients received peginterferon treatment for the first time. In this proposal, we aim to use clinical cohorts of chronic hepatitis B patients, cell model supporting HBV infection and human liver chimeric mouse model to investigate the clinical implications and underlying mechanism(s) for baseline serum infectivity. We expect the results of this study will elucidate whether the serum infectivity can serve as a new predictor for treatment response of anti-HBV therapies. This study can also shed light on the virological mechanism of HBV infection.