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Hepatitis B virus (HBV) hijacks autophagy for its replication. Nucleos(t)ide analogs (NUCs) treatment suppressed HBV replication and reduced hepatocellular carcinoma (HCC) incidence. However, the use of NUCs in chronic hepatitis B (CHB) patients with normal or minimally elevated serum alanine aminotransferase (ALT) levels is still debated. Animal models are crucial for studying the unanswered issue and evaluating new therapies. MicroRNA‐122 (miR‐122), which regulates fatty acid and cholesterol metabolism, is downregulated during hepatitis and HCC progression. The reciprocal inhibition of miR‐122 with HBV highlights its role in HCC development as a tumor suppressor. By crossbreeding HBV‐transgenic mice with miR‐122 knockout mice, we generated a hybrid mouse model with a high incidence of HCC up to 89% and normal ALT levels before HCC. The model exhibited early‐onset hepatic steatosis, progressive liver fibrosis, and impaired late‐phase autophagy. Metabolomics and microarray analysis identified metabolic signatures, including dysregulation of lipid metabolism, inflammation, genomic instability, the Warburg effect, reduced TCA cycle flux, energy deficiency, and impaired free radical scavenging. Antiviral treatment reduced HCC incidence in hybrid mice by approximately 30–35% compared to untreated mice. This effect was linked to the activation of ER stress‐responsive transcription factor ATF4, clearance of autophagosome cargo p62, and suppression of the CHOP‐mediated apoptosis pathway. In summary, this study suggests that despite minimal ALT elevation, HBV replication can lead to liver injury. Endoplasmic reticulum stress, reduced miR‐122 levels, mitochondrial and metabolic dysfunctions, blocking protective autophagy resulting in p62 accumulation, apoptosis, fibrosis, and HCC. Antiviral may improve the above‐mentioned pathogenesis through HBV suppression. [ABSTRACT FROM AUTHOR]

Simple Summary: Gut dysbiosis with an impaired intestinal barrier is differentially associated with liver diseases and, therefore, alters the systemic immunological milieu through the gut–liver axis. As a result, it plays a prominent role in liver inflammation, fibrosis, and carcinogenesis. Here, a list of network features common to patients with liver cirrhosis or hepatocellular carcinoma (HCC), regardless of etiology, was identified. In addition, disease-specific signatures were identified. This study provides novel insights that suggest alterations in gut microbial/viral composition may either confer pre-HCC disorders or contribute to the metabolic reprogramming and/or inflammatory microenvironment for HCC development. Gut bacterial/viral dysbiosis, changes in circulating metabolites, and plasma cytokines/chemokines have been previously associated with various liver diseases. Here, we analyzed the associations between fecal microbial composition, circulating metabolites, and plasma cytokines/chemokines in patients with liver cirrhosis (LC) and hepatocellular carcinoma (HCC). We recruited 10 HCC patients, 18 LC patients, and 17 healthy individuals. Their stool samples were used for gene sequencing of bacterial 16S rRNA and viral genomes, while plasma samples were utilized for the determination of endotoxin, zonulin, metabolite, and cytokine/chemokine levels. Dysbiosis was observed among gut bacteria and viruses, with significant changes in abundance at the genus and species levels, respectively. However, no differences were found between cohorts in the alpha and beta diversity. Plasma lipopolysaccharides and zonulin, but not trimethylamine N-oxide, were progressively increased in LC and HCC subjects. Profiling plasma metabolites and selected cytokines/chemokines revealed differential changes in the LC and HCC cohorts. Following joint correlation and correlation network analyses, regardless of etiology, common network signatures shared by LC and HCC patients were characterized by the gut virus Stenotrophomonas virus DLP5 and the uncultured Caudovirales phage, plasma metabolites pyruvic acid and acetic acid, and plasma cytokines/chemokines eotaxin and PDGF-AB/BB, respectively. Additionally, LC- and HCC-specific correlation networks were also identified. This study provides novel insights into altered gut microbial/viral composition that may contribute to pre-HCC disorders, metabolic reprogramming, or inflammatory microenvironments for hepatocarcinogenesis. [ABSTRACT FROM AUTHOR]

Sorafenib is a first-line treatment for patients with advanced hepatocellular carcinoma (HCC). These patients may simultaneously receive anti-hepatitis B treatment if they are viremic. The N-Acetylgalactosaminyltransferase 14 (GALNT14) gene can serve as a biomarker to guide HCC treatments. However, the enzyme substrates of its gene product, GalNAc-T14 (a glycosyltransferase), remained uncharacterized. Here, we conducted a glycoproteome-wide search for GalNAc-T14 substrates using lectin affinity chromatography followed by tandem mass spectrometry. Seventeen novel GalNAc-T14 substrates were identified. A connective map analysis showed that an antiviral drug, tenofovir, was the leading medicinal compound to down-regulate the expression of these substrates. In vitro assays showed that HCC cells were resistant to sorafenib if pretreated by tenofovir but not entecavir. Clinical analysis showed that the concomitant use of tenofovir and sorafenib was a previously unrecognized predictive factor for unfavorable overall survival (hazard ratio = 2.060, 95% confidence interval = [1.256, 3.381], p = 0.004) in a cohort of 181 hepatitis-B-related, sorafenib-treated HCC patients (concomitant tenofovir versus entecavir treatment; p = 0.003). In conclusion, by conducting a glycoproteome-wide search for GalNAc-T14 substrates, we unexpectedly found that tenofovir was a major negative regulator of GalNAc-T14 substrates and an unfavorable anti-hepatitis B drug in HCC patients receiving sorafenib. [ABSTRACT FROM AUTHOR]

Background and Aim Methods Results Conclusions Hepatitis B virus (HBV) reactivation could develop after withdrawal following a finite course of nucleoside analog (NA) therapy, leading to virological and clinical relapses. The genetic heterogeneity in the HBV surface and polymerase genes during finite NA therapy has not been carefully studied.Seven chronic HBV‐infected patients experiencing relapses following entecavir (ETV; n = 5; Patients 1 to 5) or tenofovir disoproxil fumarate (TDF; n = 2; Patients 6 and 7) withdrawal were included. Sera obtained before treatment and at relapses were retrieved and submitted for DNA extraction and amplicon‐specific deep sequencing.ETV‐treated patients had a longer time‐to‐relapse than that of TDF‐treated patients (P = 0.0357). No drug‐resistance related polymerase mutation was detected during relapses, except for a low percentage (1.4%) of rtM204I mutation in Patient 1. Two surface truncation mutations (sW216*; 40.9% and sW182*; 4.7%) detected before treatment in two TDF‐treated patients (Patients 6 and 7, respectively) were overtaken by the wild types during subsequent drug‐withdrawal‐related relapses. The simultaneous presence of sG44E (T‐cell epitope) and sE164G (B‐cell epitope) mutations was associated with failure of HBV e antigen (HBeAg) seroclearance in ETV‐treated patients.In conclusion, HBV genome continues to evolve during the courses of finite antiviral therapies. Pre‐existing surface truncation mutations can be overtaken by the wild types after relapses. The sG44E/sE164G mutations are associated with failure of HBeAg seroclearance. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic has had a major impact on human life. This review highlights the versatile roles of both classical and modern structure-based approaches for COVID-19. X-ray crystallography, nuclear magnetic resonance spectroscopy, and cryogenic electron microscopy are the three cornerstones of classical structural biology. These technologies have helped provide fundamental and detailed knowledge regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the related human host proteins as well as enabled the identification of its target sites, facilitating the cessation of its transmission. Further progress into protein structure modeling was made using modern structure-based approaches derived from homology modeling and integrated with artificial intelligence (AI), facilitating advanced computational simulation tools to actively guide the design of new vaccines and the development of anti-SARS-CoV-2 drugs. This review presents the practical contributions and future directions of structure-based approaches for COVID-19., Competing Interests: Conflicts of interest: The authors declare that they have no conflicts of interest related to the subject matter or materials discussed in this article., (Copyright © 2023, the Chinese Medical Association.)

Background: Lung adenocarcinoma-an aggressive and life-threatening malignancy-is a type of non-small-cell lung cancer. Despite medical advancements, the prognosis of lung adenocarcinoma remains unfavorable, likely because of its heterogeneous nature. Furthermore, few subtype-specific treatments are available for lung adenocarcinoma. This study was conducted to explore the molecular subtypes of lung adenocarcinoma., Methods: We performed a joint analysis of transcriptome and proteome data from East Asian patients with lung adenocarcinoma (nonsmokers, 86.5%)., Results: Four novel subtypes were identified based on distinct molecular characteristics: subtypes I, II, III, and IV. In patients with subtype I lung adenocarcinoma, eukaryotic translation initiation factor 4 gamma 1 activates cell proliferation; inhibiting this factor suppresses tumor growth, and reducing its level induces autophagy. Subtype II is characterized by Kristen rat sarcoma viral oncogene homolog-activating oncogenesis; the onset age of this subtype is the lowest among all subtypes. Subtype III manifests as an advanced disease at diagnosis; it is characterized by a core serum response-related oncogenic signature, which indicates poor overall survival in Western patients with lung cancer. Subtype IV is more common in men than in women; it has astroglial characteristics. A Connectivity Map analysis revealed that the oncogenic expression patterns corresponding to subtypes I, II, III, and IV can be reversed by the inhibitors of Inhibitor of κB (IκB) kinase (eg, withaferin A), mammalian target of rapamycin (eg, everolimus), Src proto-oncogene (Src) (eg, saracatinib), and Transforming Growth Factor (TGF)-β/Smad (eg, LY-364947), respectively., Conclusion: This study introduced an innovative multiomics data analysis pipeline. Using this approach, we successfully identified four molecular subtypes of lung adenocarcinoma and their candidate therapeutic agents. The newly identified subtypes can be combined with the current biomarkers to generate a comprehensive roadmap for treatment decision-making., Competing Interests: Conflicts of interest: Dr. Shih-Hwa Chiou and Dr. Han-Shui Hsu, editorial board members at the Journal of the Chinese Medical Association , have no roles in the peer review process or decision to publish this article. The other authors declare that they have no conflicts of interest related to the subject matter or materials discussed in this article., (Copyright © 2023, the Chinese Medical Association.)