Identification of cuproptosis-related biomarkers and analysis of immune infiltration in allograft lung ischemia-reperfusion injury

Jianying Qin; Xiaoyue Xiao; Silin Li; Ning Wen; Ke Qin; Haibin Li; Jihua Wu; Bing Lu; Minghu Li; Xuyong Sun

doi:10.3389/fmolb.2023.1269478

Identification of cuproptosis-related biomarkers and analysis of immune infiltration in allograft lung ischemia-reperfusion injury

Front Mol Biosci. 2023 Nov 21:10:1269478. doi: 10.3389/fmolb.2023.1269478. eCollection 2023.

Authors

Jianying Qin^#^{1

2

3}, Xiaoyue Xiao^#⁴, Silin Li^{1

2

3}, Ning Wen^{1

2

3}, Ke Qin^{1

2

3}, Haibin Li^{1

2

3}, Jihua Wu^{1

2

3}, Bing Lu^{1

2

3}, Minghu Li^{1

2

3}, Xuyong Sun^{1

2

3}

Affiliations

¹ Transplant Medical Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
² Guangxi Clinical Research Center for Organ Transplantation, Nanning, China.
³ Guangxi Key Laboratory of Organ Donation and Transplantation, Nanning, China.
⁴ Department of Pathology, The Fifth Affiliated Hospital of Guangxi Medical University, The First People's Hospital of Nanning, Nanning, China.

^# Contributed equally.

Abstract

Background: Allograft lung ischemia-reperfusion injury (ALIRI) is a major cause of early primary graft dysfunction and poor long-term survival after lung transplantation (LTx); however, its pathogenesis has not been fully elucidated. Cell death is a mechanism underlying ALIRI. Cuproptosis is a recently discovered form of programmed cell death. To date, no studies have been conducted on the mechanisms by which cuproptosis-related genes (CRGs) regulate ALIRI. Therefore, we explored the potential biomarkers related to cuproptosis to provide new insights into the treatment of ALIRI. Materials and methods: Datasets containing pre- and post-LTx lung biopsy samples and CRGs were obtained from the GEO database and previous studies. We identified differentially expressed CRGs (DE-CRGs) and performed functional analyses. Biomarker genes were selected using three machine learning algorithms. The ROC curve and logistic regression model (LRM) of these biomarkers were constructed. CIBERSORT was used to calculate the number of infiltrating immune cells pre- and post-LTx, and the correlation between these biomarkers and immune cells was analyzed. A competing endogenous RNA network was constructed using these biomarkers. Finally, the biomarkers were verified in a validation set and a rat LTx model using qRT-PCR and Western blotting. Results: Fifteen DE-CRGs were identified. GO analysis revealed that DE-CRGs were significantly enriched in the mitochondrial acetyl-CoA biosynthetic process from pyruvate, protein lipoylation, the tricarboxylic acid (TCA) cycle, and copper-transporting ATPase activity. KEGG enrichment analysis showed that the DE-CRGs were mainly enriched in metabolic pathways, carbon metabolism, and the TCA cycle. NFE2L2, NLRP3, LIPT1, and MTF1 were identified as potential biomarker genes. The AUC of the ROC curve for each biomarker was greater than 0.8, and the LRM provided an excellent classifier with an AUC of 0.96. These biomarkers were validated in another dataset and a rat LTx model, which exhibited good performance. In the CIBERSORT analysis, differentially expressed immune cells were identified, and the biomarkers were associated with the immune cells. Conclusion: NFE2L2, NLRP3, LIPT1, and MTF1 may serve as predictors of cuproptosis and play an important role in the pathogenesis of cuproptosis in ALIRI.

Keywords: allograft lung; biomarkers; cuproptosis; immune infiltration; ischemia-reperfusion injury.

Grants and funding

The authors declare that financial support was received for the research, and publication of this article. This study was funded by the High-Level Medical Expert Training Program of Guangxi “139” Plan Funding (G202002016), the Guangxi University Young and Middle-Aged Teachers’ Scientific Research Basic Ability Improvement Project (2022ky0077), and the Natural Science Foundation of Guangxi (2022JJB140413 and 2022JJA140239).