bioRxivPhysiologyPreprint
Transcriptional analysis identifies novel biomarkers associated with successful ex-vivo perfusion of human donor lungs
J. R. Ferdinand, M. I. Morrison, A. Andreasson, C. Charlton, A. Chhatwal, W. E. Scott, L. A. Borthwick, M. R. Clatworthy, A. J. Fisher
Abstract
Transplantation is an effective treatment for end-stage lung disease but donor organ shortage is a major problem. Ex-vivo lung perfusion (EVLP) of marginal organs enables functional assessment under normothermic conditions to facilitate clinical decision-making around utilisation, but the molecular processes occurring during EVLP, and how they differ between more or less viable lungs, remains to be determined. Here we used RNA sequencing to delineate changes in gene expression occurring in n=10 donor lungs undergoing EVLP, comparing lungs that were deemed transplantable (n=6) to those deemed unusable (n=4). We found that lungs deemed suitable for transplantation following EVLP had reduced induction of a number of innate immune pathways during EVLP, but a greater increase in genes involved in oxidative phosphorylation, a critical ATP-degenerating pathway. Furthermore, SCGB1A1, a gene encoding an anti-inflammatory secretoglobin CC10, and other club cell genes were significantly increased in transplantable lungs following perfusion, whilst CHIT-1 was decreased. Using a larger validation cohort (n=18), we confirmed that the ratio of CHIT1 and SCGB1A1 protein levels in lung perfusate have potential utility to distinguish transplantable and non-transplantable lungs (AUC 0.81). Together, our data identify novel biomarkers that may assist with pre-transplant lung assessment, as well as pathways that may amenable to therapeutic intervention during EVLP.\n\nSingle sentence summaryTranscriptional changes in lungs undergoing ex vivo normothermic perfusion identify chitinase1 and club cell genes as potential biomarkers to guide utilisation
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
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