Nuclear ErbB2 expression in hepatocytes in liver disease

Systems pharmacology of phytochemical anacardic acid in the chemoprevention of hepatocellular carcinoma

OBJECTIVES

Hepatocellular carcinoma (HCC) is a common type of liver cancer that progresses quickly and has limited treatment options. Nutraceutical anacardic acid (AA), a bioactive compound derived from cashew nut shell, has emerged as a potential candidate for HCC treatment owing to its reported anti-inflammatory, anticancer and diverse pharmacological properties. In the present study, we investigate the potential of AA as an HCC inhibitor using molecular docking, gene ontology, and network pharmacology.

METHODS

The pharmacokinetic and physicochemical properties of AA were assessed using Swiss ADME. SuperPred, Similarity Ensemble Approach, ChEMBL and Swiss Target Prediction online tools were used for determining molecular targets of AA. In addition, GeneCards, NCBI, DisGeNET and UniProt ID were used to search the targets of HCC and the top 25 hub genes were determined using Cytohubba plugin. A protein protein interaction (PPI) network was constructed through the STRING database. Gene Ontology (GO) biological process and Kyoto Encyclopaedia of Genes and Genes (KEGG) pathway enrichment analysis were performed through FunRich and ShinyGO 0.77. Moreover, molecular docking studies were performed on NF-κB and GSK-3β. The expression levels of the hub genes were also validated by western blotting.

RESULTS

Comprehensive data analysis identified 375 targets for AA and 11,333 for HCC, with 264 targets in common. Network analysis determined 25 key HCC targets, including caspase-3, and NF-κB. Gene ontology and topology analysis highlighted essential pathways implicated in HCC progression such as the renin-angiotensin system, VEGF signalling, and apoptosis. Molecular docking analysis revealed strong binding affinity of HCC proteins with NF-κB and GSK-3β. Upregulation of p-NRF2 and p-GSK-3β, and downregulation of p-NF-κB and caspase-1 expression were validated using western blotting.

CONCLUSIONS

Taken together, our study highlights the potential of AA as a promising chemopreventive agent for HCC because of its significant modulatory effects on important regulatory proteins linked to cell division, inflammation, apoptosis, and antioxidant response.

Six-gene prognostic signature for non-alcoholic fatty liver disease susceptibility using machine learning

BACKGROUND

nonalcoholic fatty liver disease (NAFLD) is a common liver disease affecting the global population and its impact on human health will continue to increase. Genetic susceptibility is an important factor influencing its onset and progression, and there is a lack of reliable methods to predict the susceptibility of normal populations to NAFLD using appropriate genes.

METHODS

RNA sequencing data relating to nonalcoholic fatty liver disease was analyzed using the "limma" package within the R software. Differentially expressed genes were obtained through preliminary intersection screening. Core genes were analyzed and obtained by establishing and comparing 4 machine learning models, then a prediction model for NAFLD was constructed. The effectiveness of the model was then evaluated, and its applicability and reliability verified. Finally, we conducted further gene correlation analysis, analysis of biological function and analysis of immune infiltration.

RESULTS

By comparing 4 machine learning algorithms, we identified SVM as the optimal model, with the first 6 genes (CD247, S100A9, CSF3R, DIP2C, OXCT 2 and PRAMEF16) as predictive genes. The nomogram was found to have good reliability and effectiveness. Six genes' receiver operating characteristic curves (ROC) suggest an essential role in NAFLD pathogenesis, and they exhibit a high predictive value. Further analysis of immunology demonstrated that these 6 genes were closely connected to various immune cells and pathways.

CONCLUSION

This study has successfully constructed an advanced and reliable prediction model based on 6 diagnostic gene markers to predict the susceptibility of normal populations to NAFLD, while also providing insights for potential targeted therapies.

p63 controls metabolic activation of hepatic stellate cells and fibrosis via an HER2-ACC1 pathway

The p63 protein has pleiotropic functions and, in the liver, participates in the progression of nonalcoholic fatty liver disease (NAFLD). However, its functions in hepatic stellate cells (HSCs) have not yet been explored. TAp63 is induced in HSCs from animal models and patients with liver fibrosis and its levels positively correlate with NAFLD activity score and fibrosis stage. In mice, genetic depletion of TAp63 in HSCs reduces the diet-induced liver fibrosis. In vitro silencing of p63 blunts TGF-β1-induced HSCs activation by reducing mitochondrial respiration and glycolysis, as well as decreasing acetyl CoA carboxylase 1 (ACC1). Ectopic expression of TAp63 induces the activation of HSCs and increases the expression and activity of ACC1 by promoting the transcriptional activity of HER2. Genetic inhibition of both HER2 and ACC1 blunt TAp63-induced activation of HSCs. Thus, TAp63 induces HSC activation by stimulating the HER2-ACC1 axis and participates in the development of liver fibrosis.

Characterizing the origin of blood plasma proteins from organ tissues in rainbow trout (Oncorhynchus mykiss) using a comparative non-targeted proteomics approach

Protein expression patterns adapt to various cues to meet the needs of an organism. The dynamicity of an organism's proteome can therefore reveal information about an organism's health. Proteome databases contain limited information regarding organisms outside of medicinal biology. The UniProt human and mouse proteomes are extensively reviewed and ∼50 % of both proteomes include tissue specificity, while >99 % of the rainbow trout proteome lacks tissue specificity. This study aimed to expand knowledge on the rainbow trout proteome with a focus on understanding the origin of blood plasma proteins. Blood, brain, heart, liver, kidney, and gills were collected from adult rainbow trout, plasma and tissue proteins were analyzed using liquid chromatography tandem mass spectrometry. Over 10,000 proteins were identified across all groups. Our data indicated that the majority of the plasma proteome is shared amongst multiple tissue types, though 4-7 % of the plasma proteome is uniquely originated from each tissue (gill > heart > liver > kidney > brain).

New Insight Into Mechanisms of Hepatic Encephalopathy: An Integrative Analysis Approach to Identify Molecular Markers and Therapeutic Targets

Hepatic encephalopathy (HE) is a set of complex neurological complications that arise from advanced liver disease. The precise molecular and cellular mechanism of HE is not fully understood. Differentially expressed genes (DEGs) from microarray technologies are powerful approaches to obtain new insight into the pathophysiology of HE. We analyzed microarray data sets of cirrhotic patients with HE from Gene Expression Omnibus to identify DEGs in postmortem cerebral tissues. Consequently, we uploaded significant DEGs into the STRING to specify protein-protein interactions. Cytoscape was used to reconstruct the genetic network and identify hub genes. Target genes were uploaded to different databases to perform comprehensive enrichment analysis and repurpose new therapeutic options for HE. A total of 457 DEGs were identified in 2 data sets totally from 12 cirrhotic patients with HE compared with 12 healthy subjects. We found that 274 genes were upregulated and 183 genes were downregulated. Network analyses on significant DEGs indicated 12 hub genes associated with HE. Enrichment analysis identified fatty acid beta-oxidation, cerebral organic acidurias, and regulation of actin cytoskeleton as main involved pathways associated with upregulated genes; serotonin receptor 2 and ELK-SRF/GATA4 signaling, GPCRs, class A rhodopsin-like, and p38 MAPK signaling pathway were related to downregulated genes. Finally, we predicted 39 probable effective drugs/agents for HE. This study not only confirms main important involved mechanisms of HE but also reveals some yet unknown activated molecular and cellular pathways in human HE. In addition, new targets were identified that could be of value in the future study of HE.

Analysis of the multi-physiological and functional mechanism of wheat alkylresorcinols based on reverse molecular docking and network pharmacology

Alkylresorcinols (ARs) are phenolic lipids present in the bran part of whole grain wheat and rye, which possess antioxidant, anti-inflammatory, anti-cancer and anti-tumor properties. The physiological activities of ARs have been proven to be diverse; however, the specific molecular mechanisms are still unclear. In this study, reverse virtual screening and network pharmacology were used to explore the potential molecular mechanisms of the physiological function of ARs and their endogenous metabolites. The Metascape database was used for GO enrichment and KEGG pathway analysis. Furthermore, molecular docking was used to investigate the interactions between active compounds and potential targets. The results showed that the bioavailability of most ARs and their endogenous metabolites was 0.55 and 0.56, while the bioavailability of certain endogenous metabolites was only 0.11. Multiplex analysis was used to screen 73 important targets and 4 core targets (namely, HSP90AA1, EP300, HSP90AB1 and ERBB2) out of the 163 initial targets. The important targets involved in the key KEGG pathway were pathways in cancer (hsa05200), lipid and atherosclerosis (hsa05417), Th17 cell differentiation (hsa04659), chemical carcinogenesis-receptor activation (hsa05207), and prostate cancer (hsa05215). The compounds involved in the core targets were AR-C21, AR-C19, AR-C17, 3,5-DHPHTA-S, 3,5-DHPHTA-G, 3,5-DHPPTA, 3,5-DHPPTA-S, 3,5-DHPPTA-G, 3,5-DHPPTA-Gly and 3,5-DHPPA-G. The interaction force between them was mainly related to hydrogen bonds and van der Waals. Overall, the physiological activities of ARs are not only related to their multiple targets, but may also be related to the synergistic effect of their endogenous metabolites.