98%
921
2 minutes
20
This study systematically investigated the molecular mechanisms underlying tetrahydrocannabinol (THC)-induced hepatotoxicity in humans through an integrated approach combining network toxicology, molecular docking, and experimental validation. Our analysis identified 22 core targets associated with THC-mediated hepatotoxicity. Protein-protein interaction (PPI) network analysis revealed significant functional associations among these 22 potential target proteins. KEGG pathway and GO term analyses demonstrated that THC potentially exerts hepatotoxic effects through multiple biological processes, including endocrine resistance, bile secretion, negative regulation of apoptosis, and cellular oxidant detoxification. Disease enrichment analysis further identified several pathological conditions closely associated with THC-induced hepatic damage. Molecular docking simulations demonstrated strong binding affinities between THC and functional domains of 17 target proteins that participated in the aforementioned enriched pathways. An in vitro model of THC-induced hepatocyte injury was successfully established and subsequently validated through RT-qPCR experiment. THC exposure significantly altered the expression patterns of 10 critical target genes: ERBB2, GPX1, MAPK14, NR1H4, SOD1, CXCR2, PPARG, EGFR, TYMS and KDR. The hepatotoxic effects of THC appear to arise from the synergistic interplay of multiple pathways and the coordinated dysfunction of various gene products. These findings elucidate key molecular pathways and therapeutic targets associated with THC-induced hepatotoxicity, providing a theoretical foundation for developing clinical interventions and hepatoprotective strategies against cannabis-related liver damage.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12012079 | PMC |
http://dx.doi.org/10.1038/s41598-025-97523-0 | DOI Listing |
Metabolomics
September 2025
Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France.
Introduction: Initially developed for transcriptomics data, pathway analysis (PA) methods can introduce biases when applied to metabolomics data, especially if input parameters are not chosen with care. This is particularly true for exometabolomics data, where there can be many metabolic steps between the measured exported metabolites in the profile and internal disruptions in the organism. However, evaluating PA methods experimentally is practically impossible when the sample's "true" metabolic disruption is unknown.
View Article and Find Full Text PDFSci Total Environ
September 2025
Department of Orthopedics and Traumatology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, Sichuan Province, China. Electronic address:
The objective of this research was to use a network toxicology approach to examine the possible toxicity of the cigarette toxicants nicotine and coal tar that cause osteoporosis (OP) as well as its molecular processes. We determined the primary chemical structures and 128 targets of action of tar and nicotine using the Swiss Target Prediction, NP-MRD, and PubChem databases. We discovered that genes including DNAJB1, CCDC8, LINC00888, ATP6V1G1, MPV17L2, PPCS, and TACC1 had a disease prognostic guiding value by LASSO analysis and differential analysis of GEO microarray data.
View Article and Find Full Text PDFEcotoxicol Environ Saf
September 2025
Department of Urology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China. Electronic address:
Background: Prostate cancer (PRAD) is a common malignancy in men, and exposure to soil pollutants may contribute to its development. And exposure to soil pollutant has been linked to its development, as well as to other diseases including cardiovascular disorders, neurological conditions, and additional cancers.
Methods: This study integrates network toxicology, machine learning, and advanced technologies to investigate the mechanisms through which soil pollutants affect prostate cancer.
PLoS One
September 2025
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.
Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.
Diabetologia
September 2025
Walther Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany.
Aims/hypothesis: Unimolecular peptides targeting the receptors for glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP) and glucagon (GCG) have been shown to improve glycaemic management in both mice and humans. Yet the identity of the downstream signalling events mediated by these peptides remain to be elucidated. Here, we aimed to assess the mechanisms by which a validated peptide triagonist for GLP-1/GIP/GCG receptors (IUB447) stimulates insulin secretion in murine pancreatic islets.
View Article and Find Full Text PDF