Bioinformatics analyses of immune-related genes and immune infiltration associated with lung ischemia-reperfusion injury

Jing Qian; Zhanyu Xu; Mingjing Yin; Zhidan Qin; Liao Pinhu

doi:10.1016/j.trim.2023.101926

Bioinformatics analyses of immune-related genes and immune infiltration associated with lung ischemia-reperfusion injury

Transpl Immunol. 2023 Dec:81:101926. doi: 10.1016/j.trim.2023.101926. Epub 2023 Aug 29.

Authors

Jing Qian¹, Zhanyu Xu², Mingjing Yin³, Zhidan Qin⁴, Liao Pinhu⁵

Affiliations

¹ Department of Cardiothoracic Intensive Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
² Department of Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
³ Department of Emergency, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
⁴ Department of Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
⁵ Department of Emergency, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China. Electronic address: liaopinhu@163.com.

PMID: 37652362
DOI: 10.1016/j.trim.2023.101926

Abstract

Background: Ischemia-reperfusion injury (IRI) is a significant complication that can occur following lung transplantation and is known to contribute to poor prognosis. Our research aimed to investigate the potential molecular targets and mechanisms involved in lung IRI (LIRI), in order to improve our understanding of this condition.

Method: We downloaded gene expression datasets (GSE127003 and GSE18995) linked to LIRI from the GEO database. Using WGCNA, we identified LIRI-related modules. Functional enrichment analyses were performed on the modules showing significant correlation with LIRI. Core immune-related genes (IRGs) were identified and validated using the GSE18995 dataset. A rat LIRI model was established to validate the expression changes of core IRGs. The LIRI groups were subjected to 60 min of warm ischemia followed by 120 min of reperfusion. Additionally, the xCell algorithm was used to characterize the immune landscape and analyze the relationships between hub IRGs and infiltrating immune cells.

Results: A total of 483 genes from the turquoise module were identified through WGCNA, with a predominant enrichment in immune- and inflammation-related pathways. Three IRGs (PTGS2, CCL2, and RELB) were found to be up-regulated after reperfusion in both GSE127003 and GSE18995 datasets, and this was further confirmed using the rat LIRI model. The xCell analysis revealed that immune score, CD8+ naive T cells, eosinophils, neutrophils, NK cells, and Tregs were upregulated after reperfusion. PTGS2, CCL2, and RELB showed positive correlations with CD8+ naive T cells, monocytes, neutrophils, and Tregs.

Conclusion: PTGS2, CCL2, and RELB were found to be potential biomarkers for LIRI. Immune and microenvironment scores were higher after reperfusion compared to before reperfusion. PTGS2, CCL2, and RELB appear to play a crucial role in the development of LIRI and may contribute to it by increasing the number of immune cells. Our findings offer new perspectives on potential treatment targets and the pathogenesis of LIRI.

Keywords: Bioinformatics analysis; Immune cell infiltration; Lung ischemia-reperfusion; WGCNA.

MeSH terms

Animals
Cyclooxygenase 2 / metabolism
Lung / pathology
Lung Transplantation* / adverse effects
Rats
Rats, Sprague-Dawley
Reperfusion Injury* / genetics
Reperfusion Injury* / metabolism

Substances

Cyclooxygenase 2

Grants and funding

82060022/National Natural Science Foundation of China