Pathological Pattern of Intrahepatic HBV in HCC is Phenocopied by PDX-Derived Mice: a Novel Model for Antiviral Treatment

HBCVTr: an end-to-end transformer with a deep neural network hybrid model for anti-HBV and HCV activity predictor from SMILES

Hepatitis B and C viruses (HBV and HCV) are significant causes of chronic liver diseases, with approximately 350 million infections globally. To accelerate the finding of effective treatment options, we introduce HBCVTr, a novel ligand-based drug design (LBDD) method for predicting the inhibitory activity of small molecules against HBV and HCV. HBCVTr employs a hybrid model consisting of double encoders of transformers and a deep neural network to learn the relationship between small molecules' simplified molecular-input line-entry system (SMILES) and their antiviral activity against HBV or HCV. The prediction accuracy of HBCVTr has surpassed baseline machine learning models and existing methods, with R-squared values of 0.641 and 0.721 for the HBV and HCV test sets, respectively. The trained models were successfully applied to virtual screening against 10 million compounds within 240 h, leading to the discovery of the top novel inhibitor candidates, including IJN04 for HBV and IJN12 and IJN19 for HCV. Molecular docking and dynamics simulations identified IJN04, IJN12, and IJN19 target proteins as the HBV core antigen, HCV NS5B RNA-dependent RNA polymerase, and HCV NS3/4A serine protease, respectively. Overall, HBCVTr offers a new and rapid drug discovery and development screening method targeting HBV and HCV.

Novel non-HAP class A HBV capsid assembly modulators have distinct in vitro and in vivo profiles

IMPORTANCE

Chronic hepatitis B is the most important cause of liver cancer worldwide and affects more than 290 million people. Current treatments are mostly suppressive and rarely lead to a cure. Therefore, there is a need for novel and curative drugs that target the host or the causative agent, hepatitis B virus itself. Capsid assembly modulators are an interesting class of antiviral molecules that may one day become part of curative treatment regimens for chronic hepatitis B. Here we explore the characteristics of a particularly interesting subclass of capsid assembly modulators. These so-called non-HAP CAM-As have intriguing properties in cell culture but also clear virus-infected cells from the mouse liver in a gradual and sustained way. We believe they represent a considerable improvement over previously reported molecules and may one day be part of curative treatment combinations for chronic hepatitis B.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Protocol for chronic hepatitis B virus infection mouse model development by patient-derived orthotopic xenografts

Background

According to the World Health Organization, more than 250 million people worldwide are chronically infected with the hepatitis B virus, and almost 800.000 patients die annually of mediated liver disorders. Therefore, adequate biological test systems are needed that could fully simulate the course of chronic hepatitis B virus infection, including in patients with hepatocellular carcinoma.

Methods

In this study, we will assess the effectiveness of existing protocols for isolation and cultivation of primary cells derived from patients with hepatocellular carcinoma in terms of the yield of viable cells and their ability to replicate the hepatitis B virus using isolation and cultivation methods for adhesive primary cells, flow cytometry and quantitative polymerase chain reaction. Another part of our study will be devoted to evaluating the effectiveness of hepatocellular carcinoma grafting methods to obtain patient-derived heterotopic and orthotopic xenograft mouse avatars using animal X-ray irradiation and surgery procedures and in vivo fluorescent signals visualization and measurements. Our study will be completed by histological methods.

Discussion

This will be the first extensive comparative study of the main modern methods and protocols for isolation and cultivation primary hepatocellular carcinoma cells and tumor engraftment to the mice. All protocols will be optimized and characterized using the: (1) efficiency of the method for isolation cells from removed hepatocellular carcinoma in terms of their quantity and viability; (2) efficiency of the primary cell cultivation protocol in terms of the rate of monolayer formation and hepatitis B virus replication; (3) efficiency of the grafting method in terms of the growth rate and the possibility of hepatitis B virus persistence and replication in mice. The most effective methods will be recommended for use in translational biomedical research.

Murine Models of Chronic Viral Infections and Associated Cancers

Viruses are now recognized as bona fide etiologic factors of human cancer. Carcinogenic viruses include Epstein– Barr virus (EBV), high-risk human papillomaviruses (HPVs), hepatitis B virus (HBV), hepatitis C virus (HCV), human T-cell leukemia virus type 1 (HTLV-1), human immunodeficiency virus type 1 (HIV-1, indirectly), and several candidate human cancer viruses. It is estimated that 15% of all human tumors worldwide are caused by viruses. Tumor viruses establish long-term persistent infections in humans, and cancer is an accidental side effect of viral replication strategies. Viruses are usually not complete carcinogens, supporting the concept that cancer results from the accumulation of multiple cooperating events, in which human cancer viruses display different, often opposing roles. The laboratory mouse Mus musculus is one of the best in vivo experimental systems for modeling human pathology, including viral infections and cancer. However, mice are unsusceptible to infection with the known carcinogenic viruses. Many murine models were developed to overcome this limitation and to address various aspects of virus-associated carcinogenesis, from tumors resulting from xenografts of human tissues and cells, including cancerous and virus infected, to genetically engineered mice susceptible to viral infections and associated cancer. The review considers the main existing models, analyzes their advantages and drawbacks, describes their applications, outlines the prospects of their further development.

The Impact of HBV Quasispecies Features on Immune Status in HBsAg+/HBsAb+ Patients With HBV Genotype C Using Next-Generation Sequencing

Background

This study aimed to explore the molecular mechanism of the coexistence of hepatitis B surface antigen (HBsAg) and hepatitis B surface antibody (HBsAb) serological pattern via intensive characterization of HBV s gene in both chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC) patients.

Method

A total of 73 HBsAg+/HBsAb+ patients (CHB = 36, HCC = 37) and 96 HBsAg+/HBsAb− patients (CHB = 47, HCC = 49) were enrolled from 13 medical centers in China. The sequence features were elaborated based on the combination of next-generation sequencing (NGS) and multidimensional bioinformatics analysis.

Results

The 16 high-frequency missense mutations, changes of stop codon mutation, clustering, and random forest models based on quasispecies features demonstrated the significant discrepancy power between HBsAg+/HBsAb+ and HBsAg+/HBsAb− in CHB and HCC, respectively. The immunogenicity for cytotoxic T lymphocyte (CTL) epitope Se and antigenicity for the major hydrophilic region (MHR) were both reduced in HBsAg+/HBsAb+ patients (CTL Se: p < 0.0001; MHR: p = 0.0216). Different mutation patterns were observed between HBsAg+/HBsAb+ patients with CHB and with HCC. Especially, mutations in antigenic epitopes, such as I126S in CHB and I126T in HCC, could impact the conformational structure and alter the antigenicity/immunogenicity of HBsAg.

Conclusion

Based on NGS and bioinformatics analysis, this study indicates for the first time that point mutations and quasispecies diversities of HBV s gene could alter the MHR antigenicity and CTL Se immunogenicity and could contribute to the concurrent HBsAg+/HBsAb+ with different features in HCC and CHB. Our findings might renew the understanding of this special serological profile and benefit the clinical management in HBV-related diseases.

RNA N6-Methyladenosine-Related Gene Contribute to Clinical Prognostic Impact on Patients With Liver Cancer

Liver cancer (LC) is the fourth leading cause of cancer-related deaths worldwide. There is an urgent need to identify novel and reliable prognostic biomarkers for LC in order to improve patient outcomes. N6-methyladenosine (m6A) is the most common internal modification in eukaryotic mRNA and has been associated with various cancers, although its roles in the prognosis of LC remains to be elucidated. We analyzed the expression profiles of 15 m6A-related genes in the International Cancer Genome Consortium (ICGC) LIRI-JP dataset, and applied consensus clustering to stratify LC patients into two subgroups (Cluster 1 and Cluster 2). Cluster1 was significantly correlated to lower tumor stage and longer overall survival (OS). Gene set enrichment analysis showed that tumorigenic markers, including DNA repair, E2F targets, G2M checkpoint, and MYC targets V1, were enriched in Cluster2. We then constructed a prognostic risk model using three m6A-related genes that were identified as independent factors affecting OS. The nomogram based on the risk model score indicated good performance in predicting the 1-, 2- and 3-year survival of the LC patients. In conclusion, m6A-related genes are potential prognostic markers and therapeutic targets for LC.

Comprehensive comparison of patient-derived xenograft models in Hepatocellular Carcinoma and metastatic Liver Cancer

Patient-derived xenograft (PDX) models are effective preclinical cancer models that reproduce the tumor microenvironment of the human body. The methods have been widely used for drug screening, biomarker development, co-clinical trials, and personalized medicine. However, the low success rate and the long tumorigenesis period have largely limited their usage. In the present studies, we compared the PDX establishment between hepatocellular cancer (HCC) and metastatic liver cancer (MLC), and identified the key factors affecting the transplantation rate of PDXs. Surgically resected tumor specimens obtained from patients were subcutaneously inoculated into immunodeficient mice to construct PDX models. The overall transplantation rate was 38.5% (20/52), with the HCC group (28.1%, 9/32) being lower than MLC group (56.2%, 9/16). In addition, HCC group took significantly longer latency period than MLC group to construct PDX models. Hematoxylin and eosin staining results showed that the histopathology of all generations in PDX models was similar to the original tumor in all three types of cancer. The transplantation rate of PDX models in HCC patients was significantly associated with blood type (P=0.001), TNM stage (P=0.023), lymph node metastasis (P=0.042) and peripheral blood CA19-9 level (P=0.049), while the transplantation rate of PDX models in MLC patients was significantly associated with tumor size (P=0.034). This study demonstrates that PDX models can effectively reproduce the histological patterns of human tumors. The transplantation rate depends on the type of original tumor. Furthermore, it shows that the invasiveness of the original liver cancer affects the possibility of its growth in immunodeficient mice.