ArticleNaunyn-Schmiedeberg's archives of pharmacology2025
Identification of key immune genes of drug-induced liver injury induced by tolvaptan based on bioinformatics.
Article in Naunyn-Schmiedeberg's archives of pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug-induced liver injury (DILI) poses critical challenges in preclinical drug development and is a primary reason for candidate drug attrition. The incidence of DILI has risen in recent years. While immune-related genes (IRGs) are crucial in immune infiltration, their expression and regulatory mechanisms in tolvaptan-induced DILI remain largely uncharacterized. RNA sequencing data related to DILI and associated clinical data were sourced from the Gene Expression Omnibus (GEO), and IRGs were obtained from the ImmPort database. Differentially expressed genes (DEGs) from DILI and IRGs were intersected to identify differentially expressed immune-related genes (DEIRGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to elucidate the biological functions of DEIRGs. In addition, a protein-protein interaction (PPI) network of DEIRGs was constructed. Immunocytes and immune regulation analyses were conducted using the CIBERSORT tool. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic accuracy of individual DEIRGs. Networks of transcription factor and microRNA co-regulation were constructed using the NetworkAnalyst database. The expression of DEIRGs in DILI samples was quantified with RT-qPCR. From GSE99878, 204 DEGs were identified, with 23 matching IRGs exhibiting significant expression differences in 17 DEIRGs. The ROC curve analysis suggested satisfactory diagnostic values for six DEIRGs. The potential gene regulatory network comprised 214 microRNAs, 257 transcription factors, and 23 DEIRGs. Finally, RT-qPCR confirmed the expression levels of nine DEIRGs, aligning with public database results. The study revealed numerous immune-related biomarkers, verifying expression in five pivotal genes (ICAM1, CXCL10, IGF1, CX3CL1, and EGFR) and highlighting four genes with notable diagnostic potential (TNFAIP3, BDNF, NR1D2, and PPARA). Additionally, it explored the roles of key biomarkers in inflammatory responses, relevant signaling pathways, and interaction networks, offering new insights into DILI diagnosis, mechanistic understanding, and treatment strategies.
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