Potential biomarkers in the fibrosis progression of nonalcoholic steatohepatitis (NASH)

SOX9: a key transcriptional regulator in organ fibrosis

The SOX9 gene locus is not only extensive but also intricate, and it could promote fibrosis in different organs or tissues, including cardiac fibrosis, liver fibrosis, kidney fibrosis, pulmonary fibrosis, as well as other organ fibrosis. Many disorders are associated with the process of fibrosis; moreover, fibrosis is a common symptom of chronic inflammatory diseases, characterized by the accumulation of excessive components in the extracellular matrix through different signaling pathways. The advanced stage of the fibrotic process leads to organ dysfunction and, ultimately, death. In this review, we first give an overview of the original structure and functions of SOX9. Second, we will discuss the role of SOX9 in fibrosis in various organs or tissues. Third, we describe and reveal the possibility of SOX9 as an antifibrotic treatment target. Finally, we will focus on the application of novel technologies for SOX9 and the subsequent investigation of fibrosis.

Dawn of an era of effective treatments for MAFLD

Fatty liver disease is a commonly occurring disease resulting in hepatic and extrahepatic complications. To date, there have been few available treatments beyond conventional lifestyle modification. While lifestyle modifications resulting in weight loss >10% have shown to be beneficial for metabolic dysfunction‐associated steatohepatitis (MASH), for the majority of patients, this is difficult to achieve. The recent approval of resmetirom (a thyroid hormone receptor beta agonist) by the Food and Drug Administration following positive results for histological outcomes in a phase 3 trial has opened the door for new treatments for metabolic (dysfunction)‐associated fatty liver disease (MAFLD) and MASH. There are currently a number of phase 3 trials targeting a variety of signaling pathways involved in the pathogenesis of metabolic steatohepatitis that are also promising. This review focuses on the currently available treatments for MAFLD and MASH, ongoing phase 3 clinical trials, and unresolved controversies in clinical trials in this area.

Diverse functions of SOX9 in liver development and homeostasis and hepatobiliary diseases

The liver is the central organ for digestion and detoxification and has unique metabolic and regenerative capacities. The hepatobiliary system originates from the foregut endoderm, in which cells undergo multiple events of cell proliferation, migration, and differentiation to form the liver parenchyma and ductal system under the hierarchical regulation of transcription factors. Studies on liver development and diseases have revealed that SRY-related high-mobility group box 9 (SOX9) plays an important role in liver embryogenesis and the progression of hepatobiliary diseases. SOX9 is not only a master regulator of cell fate determination and tissue morphogenesis, but also regulates various biological features of cancer, including cancer stemness, invasion, and drug resistance, making SOX9 a potential biomarker for tumor prognosis and progression. This review systematically summarizes the latest findings of SOX9 in hepatobiliary development, homeostasis, and disease. We also highlight the value of SOX9 as a novel biomarker and potential target for the clinical treatment of major liver diseases.

Multi-omics approaches reveal the molecular mechanisms underlying the interaction between Clonorchis sinensis and mouse liver

Introduction

Clonorchiasis remains a serious global public health problem, causing various hepatobiliary diseases. However, there is still a lack of overall understanding regarding the molecular events triggered by Clonorchis sinensis (C. sinensis) in the liver.

Methods

BALB/c mouse models infected with C. sinensis for 5, 10, 15, and 20 weeks were constructed. Liver pathology staining and observation were conducted to evaluate histopathology. The levels of biochemical enzymes, blood routine indices, and cytokines in the blood were determined. Furthermore, alterations in the transcriptome, proteome, and metabolome of mouse livers infected for 5 weeks were analyzed using multi-omics techniques.

Results

The results of this study indicated that adult C. sinensis can cause hepatosplenomegaly and liver damage, with the most severe symptoms observed at 5 weeks post-infection. However, as the infection persisted, the Th2 immune response increased and symptoms were relieved. Multi-omics analysis of liver infected for 5 weeks identified 191, 402 and 232 differentially expressed genes (DEGs), proteins (DEPs) and metabolites (DEMs), respectively. Both DEGs and DEPs were significantly enriched in liver fibrosis-related pathways such as ECM-receptor interaction and cell adhesion molecules. Key molecules associated with liver fibrosis and inflammation (Cd34, Epcam, S100a6, Fhl2, Itgax, and Retnlg) were up-regulated at both the gene and protein levels. The top three metabolic pathways, namely purine metabolism, arachidonic acid metabolism, and ABC transporters, were associated with liver cirrhosis, fibrosis, and cholestasis, respectively. Furthermore, metabolites that can promote liver inflammation and fibrosis, such as LysoPC(P-16:0/0:0), 20-COOH-leukotriene E4, and 14,15-DiHETrE, were significantly up-regulated.

Conclusion

Our study revealed that the most severe symptoms in mice infected with C. sinensis occurred at 5 weeks post-infection. Moreover, multi-omics analysis uncovered predominant molecular events related to fibrosis changes in the liver. This study not only enhances our understanding of clonorchiasis progression but also provides valuable insights into the molecular-level interaction mechanism between C. sinensis and its host liver.

Recent insights into the pathogenesis and therapeutic targets of chronic liver diseases

Viral hepatitis, alcohol-associated liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) are the three major causes of chronic liver diseases, which account for approximately 2 million deaths per year worldwide. The current direct-acting antiviral drugs and vaccinations have effectively reduced and ameliorated viral hepatitis infection, but there are still no effective drug treatments for ALD, NAFLD and liver cancer due to the poor understanding of their pathogenesis. To better understand the pathogenesis, the fifth Chinese American Liver Society/Society of Chinese Bioscientists in America Hepatology Division Annual Symposium, which was held virtually on 21-22 October 2022, focused on the topics related to ALD, NAFLD and liver cancer. Here, we briefly highlight the presentations that focus on the current progress in basic and translational research in ALD, NAFLD and liver cancer. The roles of non-coding RNA, autophagy, extrahepatic signalling, macrophages, etc in liver diseases are deliberated, and the application of single-cell RNA sequencing in the study of liver disease is also discussed.

Identification of Basement Membrane Genes and Related Molecular Subtypes in Nonalcoholic Fatty Liver Disease

Basement membranes (BMs) are widely distributed and highly specialized extracellular matrix (ECM). The goal of this study was to explore novel genes associated with nonalcoholic fatty liver disease (NAFLD) from the perspective of BMs. Sequencing results of 304 liver biopsy samples about NAFLD were systematically obtained from the Gene Expression Omnibus (GEO) database. Biological changes during NAFLD progression and hub BM-associated genes were investigated by differential gene analysis and weighted gene co-expression network analysis (WGCNA), respectively. The nonalcoholic steatohepatitis (NASH) subgroups were identified based on hub BM-associated genes expression, as well as the differences in Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways and immune microenvironment between different subgroups were compared. Extracellular matrix (ECM) seems to play an important role in the development of NAFLD. Three representative BM-associated genes (ADAMTS2, COL5A1, and LAMC3) were finally identified. Subgroup analysis results suggested that there were significant changes in KEGG signaling pathways related to metabolism, extracellular matrix, cell proliferation, differentiation, and death. There were also changes in macrophage polarization, neutrophils, and dendritic cells abundance, and so on. In conclusion, the present study identified novel potential BM-associated biomarkers and further explored the heterogeneity of NASH that might provide new insights into the diagnosis, assessment, management, and personalized treatment of NAFLD.

Exploring Key Genes with Diagnostic Value for Nonalcoholic Steatohepatitis Based on Bioinformatics Analysis

We aimed to screen specific genes in liver tissue samples of patients with nonalcoholic steatohepatitis (NASH) with clinical diagnostic value based on bioinformatics analysis. The datasets of liver tissue samples from healthy individuals and NASH patients were retrieved for consistency cluster analysis to obtain the NASH sample typing, followed by verification of the diagnostic value of sample genotyping-specific genes. All samples were subjected to logistic regression analysis, followed by the establishment of the risk model, and then, the diagnostic value was determined by receiver operating characteristic curve analysis. NASH samples could be divided into cluster 1, cluster 2, and cluster 3, which could predict the nonalcoholic fatty liver disease activity score of patients. A total of 162 sample genotyping-specific genes were extracted from patient clinical parameters, and the top 20 core genes in the protein interaction network were obtained for logistic regression analysis. Five sample genotyping-specific genes (WD repeat and HMG-box DNA-binding protein 1 [WDHD1], GINS complex subunit 2 [GINS2], replication factor C subunit 3 (RFC3), secreted phosphoprotein 1 [SPP1], and spleen tyrosine kinase [SYK]) were extracted to construct the risk models with high diagnostic value in NASH. Compared with the low-risk group, the high-risk group of the model showed increased lipoproduction and decreased lipolysis and lipid β oxidation. The risk models based on WDHD1, GINS2, RFC3, SPP1, and SYK have high diagnostic value in NASH, and this risk model is closely related to lipid metabolism pathways.

Establishment and Validation of a Novel Risk Score for Hepatocellular Carcinoma Based on Bile Acid and Bile Salt Metabolism-Related Genes

Liver cancer is a public disease burden with an increasing incidence rate globally. Bile acid and bile salt's metabolic pathways participate in liver tumorigenesis and regulate the tumor microenvironment. However, there still remains a lack of systematic analysis of the genes related to bile acid and bile salt metabolic pathways in hepatocellular carcinoma (HCC). The mRNA expression data and clinical follow-up information of patients with HCC were obtained from public databases, including The Cancer Genome Atlas, Hepatocellular Carcinoma Database, Gene Expression Omnibus, and IMvigor210. The bile acid and bile salt metabolism-related genes were extracted from Molecular Signatures Database. Univariate Cox and logistic least absolute shrinkage and selection operator regression analyses were conducted to establish the risk model. Single sample gene set enrichment analysis, Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data, and Tumor Immune Dysfunction and Exclusion were adopted to analyze immune status. The efficiency of the risk model was tested using a decision tree and a nomogram. We determined two molecular subtypes based on bile acid and bile salt metabolism-related genes, with the prognosis of the S1 subtype being markedly superior to the S2 subtype. Next, we established a risk model based on the differentially expressed genes between the two molecular subtypes. The high-risk and low-risk groups showed significant differences in the biological pathways, immune score, immunotherapy response, and drug susceptibility. Our results demonstrated the good predictive performance of the risk model in immunotherapy datasets and established that it could be an essential factor affecting the prognosis of HCC. In conclusion, we identified two molecular subtypes based on bile acid and bile salt metabolism-related genes. The risk model established in our study could effectively predict the prognosis of patients with HCC and their immunotherapeutic response, which may contribute to targeted immunotherapy in HCC.

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

Integrated analysis of potential gene crosstalk between non-alcoholic fatty liver disease and diabetic nephropathy

BACKGROUND

Growing evidence indicates that non-alcoholic fatty liver disease (NAFLD) is related to the occurrence and development of diabetic nephropathy (DN). This bioinformatics study aimed to explore optimal crosstalk genes and related pathways between NAFLD and DN.

METHODS

Gene expression profiles were downloaded from Gene Expression Omnibus. CIBERSORT algorithm was employed to analyze the similarity of infiltrating immunocytes between the two diseases. Protein-protein interaction (PPI) co-expression network and functional enrichment analysis were conducted based on the identification of common differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm were implemented to initially screen crosstalk genes. Machine learning models, including support vector machine, random forest model, and generalized linear model, were utilized to further identify the optimal crosstalk genes between DN and NAFLD. An integrated network containing crosstalk genes, transcription factors, and associated pathways was developed.

RESULTS

Four gene expression datasets, including GSE66676 and GSE48452 for NAFLD and GSE30122 and GSE1009 for DN, were involved in this study. There were 80 common DEGs between the two diseases in total. The PPI network built with the 80 common genes included 77 nodes and 83 edges. Ten optimal crosstalk genes were selected by LASSO regression and Boruta algorithm, including CD36, WIPI1, CBX7, FCN1, SLC35D2, CP, ZDHHC3, PTPN3, LPL, and SPP1. Among these genes, LPL and SPP1 were the most significant according to NAFLD-transcription factor network. Five hundred twenty-nine nodes and 1,113 edges comprised the PPI network of activated pathway-gene. In addition, 14 common pathways of these two diseases were recognized using Gene Ontology (GO) analysis; among them, regulation of the lipid metabolic process is closely related to both two diseases.

CONCLUSIONS

This study offers hints that NAFLD and DN have a common pathogenesis, and LPL and SPP1 are the most relevant crosstalk genes. Based on the common pathways and optimal crosstalk genes, our proposal carried out further research to disclose the etiology and pathology between the two diseases.