BACKGROUND & AIMS Hepatitis E virus (HEV) causes approximately 19.47 million symptomatic cases annually and is an emerging cause of chronic hepatitis in immunocompromised individuals. No definite evidence demonstrates that laboratory mice are susceptible to all known HEV genotypes. The factors that define the host species range of HEV remain unclear. Given the numerous genetic variants and toolkits available for mice, which permit deep mechanistic studies, we aimed to develop an inbred mouse model of HEV infection. METHODS AG129 and C57BL/6J mice were infected with HEV. Key infection parameters included HEV RNA detection by RT-PCR and RNAscope, liver function tests, histopathological examination. Single-cell RNA sequencing was employed alongside transcriptomic analysis to delineate infection dynamics and investigate virus-host interactions. RESULTS We show that an emerging human-pathogenic rat-derived HEV-C1 strain can breach the species barrier and robustly infect AG129 mice. Using single-cell sequencing and RNAscope, we demonstrate viral tropism for liver macrophages and hepatocytes, providing a previously unknown single-cell atlas of intrahepatic HEV-C1 infection. We subsequently adapted this HEV-C1 isolate by serial passaging in AG129 mice. After 13 passages, the resulting mouse-adapted strain acquired the ability to infect immunocompetent C57BL/6J mice. Both the immunocompromised and immunocompetent mouse models supported efficient HEV replication and enabled antiviral and vaccine testing. CD4 depletion experiments suggest that impairment of CD4+ T cell responses may contribute to the establishment of persistent infection. CONCLUSIONS: We developed two mouse models using AG129 and C57BL/6J mice, both of which support efficient HEV-C1 replication. This work establishes the first immunocompetent mouse model for HEV infection. These mouse models offer a robust platform for studying HEV immunopathogenesis, evaluating antivirals and vaccines, and investigating mechanisms of cross-species transmission. GenBank accession numbers PX496820, PX572923RNA-Seq data: https://ngdc.cncb.ac.cn/gsa/ Impact and implications HEV research is hampered by the lack of suitable small-animal models, and our study fills this gap by establishing two mouse models, particularly the immunocompetent C57BL/6J mouse model, which should support the use of versatile genetic and immunological tools for deep mechanistic studies in the future. This study also provides a single-cell atlas of HEV infection dynamics, revealing intrahepatic viral tropism. We identified CD4+ T cell depletion as a pivotal driver of chronic infection. These mouse models offer a robust platform for studying HEV immunopathogenesis, evaluating antivirals and vaccines, and investigating mechanisms of cross-species transmission.
Hepatocellular carcinoma (HCC) surveillance with semiannual ultrasound and AFP is guideline-recommended for patients with cirrhosis and selected patients with chronic hepatitis B. However, this strategy has suboptimal sensitivity for early-stage HCC and poor real-world adherence; moreover, randomized trial evidence demonstrating reduced HCC-related or all-cause mortality in patients with cirrhosis is lacking. This Expert Opinion evaluates two emerging categories of HCC surveillance tests - abbreviated magnetic resonance imaging (aMRI) protocols and blood-based biomarker panels - and proposes that, if validated, their future clinical implementation should be guided not only by HCC risk, but by expected surveillance benefit. Protocols for aMRI seek to preserve the high diagnostic accuracy of full liver-protocol MRI while reducing scan time, cost, and patient burden. Dynamic contrast-enhanced aMRI (DCE-aMRI) can establish a definitive HCC diagnosis without recall imaging and may match the accuracy of full liver-protocol MRI. Non-contrast aMRI (NC-aMRI) avoids intravenous contrast and has demonstrated superior sensitivity and specificity compared with ultrasound in recent trials. Blood-based biomarker panels, including protein-based tests (GALAD, HES 2.0) and circulating tumor DNA-based assays (Oncoguard, HelioLiver) may improve adherence, but face methodological challenges and require rigorous, prospective longitudinal evaluation to determine whether they result not only in earlier actionable detection but also better clinical outcomes. We argue that selecting which patients should receive enhanced surveillance requires moving beyond risk stratification toward benefit stratification, i.e., towards basing surveillance recommendations not only on the patient's risk of developing HCC, but also on the probability that by enabling earlier-stage detection and receipt of effective treatment, surveillance improves clinical outcomes. Patients at the highest HCC risk do not necessarily stand to gain the most from earlier detection, underscoring the need for pragmatic frameworks and prediction tools that estimate individualized surveillance benefit.
