Mitochondrial Homeostasis and Mast Cells in Experimental Hepatic Ischemia-Reperfusion Injury of Rats

Koç, Sema; Doğan, Halef Okan; Karataş, Özhan; Erdogan, Mehmet Mustafa; Polat, Vural

doi:10.5152/tjg.2022.21911

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…Throughout the HIRI process, MCs accumulate and emit various bioactive substances, thereby modifying the local tissue microenvironment and influencing the inflammatory reaction. Additional research is needed to comprehensively understand their effect on the pathophysiology of HIRI ( 52 , 53 ). Furthermore, our results suggest a close correlation between NLRP3 and various immune cells and functions, aligning with prior research ( 54 , 55 ).…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning

Xiao,

Huang,

Yuan

et al. 2024

Front. Immunol.

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Background and aimsCuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusion injury (HIRI).MethodsThe datasets related to HIRI were sourced from the Gene Expression Omnibus database. The comparative analysis of differential gene expression involving CRGs was performed between HIRI and normal liver samples. Correlation analysis, function enrichment analyses, and protein-protein interactions were employed to understand the interactions and roles of these genes. Machine learning techniques were used to identify hub genes. Additionally, differences in immune cell infiltration between HIRI patients and controls were analyzed. Quantitative real-time PCR and western blotting were used to verify the expression of the hub genes.ResultsSeventy-five HIRI and 80 control samples from three databases were included in the bioinformatics analysis. Three hub CRGs (NLRP3, ATP7B and NFE2L2) were identified using three machine learning models. Diagnostic accuracy was assessed using a receiver operating characteristic (ROC) curve for the hub genes, which yielded an area under the ROC curve (AUC) of 0.832. Remarkably, in the validation datasets GSE15480 and GSE228782, the three hub genes had AUC reached 0.904. Additional analyses, including nomograms, decision curves, and calibration curves, supported their predictive power for diagnosis. Enrichment analyses indicated the involvement of these genes in multiple pathways associated with HIRI progression. Comparative assessments using CIBERSORT and gene set enrichment analysis suggested elevated expression of these hub genes in activated dendritic cells, neutrophils, activated CD4 memory T cells, and activated mast cells in HIRI samples versus controls. A ceRNA network underscored a complex regulatory interplay among genes. The genes mRNA and protein levels were also verified in HIRI-affected mouse liver tissues.ConclusionOur findings have provided a comprehensive understanding of the association between cuproptosis and HIRI, establishing a promising diagnostic pattern and identifying latent therapeutic targets for HIRI treatment. Additionally, our study offers novel insights to delve deeper into the underlying mechanisms of HIRI.

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