Abstract
Introduction Transplantation of lungs from donation after circulatory death (DCD) in addition to donation after brain death (DBD) became routine worldwide to address the global organ shortage. The development of ex vivo lung perfusion (EVLP) for donor lung assessment and repair contributed to the increased use of DCD lungs. We hypothesise that a better understanding of the differences between lungs from DBD and DCD donors, and between EVLP and directly transplanted (non-EVLP) lungs, will lead to the discovery of the injury-specific targets for donor lung repair and reconditioning.
Methods Tissue biopsies from human DBD (n=177) and DCD (n=65) donor lungs, assessed with or without EVLP, were collected at the end of cold ischaemic time. All samples were processed with microarray assays. Gene expression, network and pathway analyses were performed using R, Ingenuity Pathway Analysis and STRING. Results were validated with protein assays, multiple logistic regression and 10-fold cross-validation.
Results Our analyses showed that lungs from DBD donors have upregulation of inflammatory cytokines and pathways. In contrast, DCD lungs display a transcriptome signature of pathways associated with cell death, apoptosis and necrosis. Network centrality revealed specific drug targets to rehabilitate DBD lungs. Moreover, in DBD lungs, tumour necrosis factor receptor-1/2 signalling pathways and macrophage migration inhibitory factor-associated pathways were activated in the EVLP group. A panel of genes that differentiate the EVLP from the non-EVLP group in DBD lungs was identified.
Conclusion The examination of gene expression profiling indicates that DBD and DCD lungs have distinguishable biological transcriptome signatures.
Abstract
Lungs from DBD donors have increased activation of inflammatory pathways. In contrast, cell death, apoptosis and necrosis are activated in lungs from DCD donors. EVLP and non-EVLP lungs also have distinct transcriptomic signatures. https://bit.ly/36SWsdb
Footnotes
Author contributions: C. Baciu participated in the study design, performed all bioinformatics analyses, submitted the raw data to GEO and wrote the manuscript; A. Sage performed protein analysis; R. Zamel provided raw microarray data and revised the manuscript; J. Shin and X-H. Bai performed experimental validation; O. Hough prepared the figures; M. Bhat, M. Cypel and J.C. Yeung assisted with review and editing; S. Keshavjee led the biobanking and microarray studies; M. Liu and S. Keshavjee conceived the study design and supervised the project; all authors revised the final draft of the manuscript.
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Conflict of interest: C. Baciu has nothing to disclose.
Conflict of interest: A. Sage has nothing to disclose.
Conflict of interest: R. Zamel has nothing to disclose.
Conflict of interest: J. Shin has nothing to disclose.
Conflict of interest: X-H. Bai has nothing to disclose.
Conflict of interest: O. Hough has nothing to disclose.
Conflict of interest: M. Bhat has nothing to disclose.
Conflict of interest: J.C. Yeung has nothing to disclose.
Conflict of interest: M. Cypel has nothing to disclose.
Conflict of interest: S. Keshavjee reports grants from Canadian Institutes of Health Research (operating grants MOP-31227, MOP-119514 and PJT-148847) and Genome Canada (Genomic Application Partnership Program grant 6427), during the conduct of the study.
Conflict of interest: M. Liu reports grants from Canadian Institutes of Health Research (operating grants MOP-31227, MOP-119514 and PJT-148847) and Genome Canada (Genomic Application Partnership Program grant 6427), during the conduct of the study.
Support statement: This work was supported by the Canadian Institutes of Health Research (operating grants MOP-31227, MOP-119514 and PJT-148847) and Genome Canada (Genomic Application Partnership Program grant 6427). Funding information for this article has been deposited with the Crossref Funder Registry.
- Received February 14, 2020.
- Accepted October 5, 2020.
- Copyright ©ERS 2021