Improving Life expectancy of LUNG transplant recipients through innovative ex vivo perfusion gene therapy

forthcoming

Patient survival after lung transplantation (LTx) for end-stage pulmonary disease is poor (5-year survival rate of 59%) due to ischemia reperfusion injury (IRI) and graft rejection. No therapies are available to prevent IRI, and current immunosuppression causes toxicity and morbidity. Novel strategies are required that can mask the graft from the recipient’s immune system The LifeLUNG initiative unites the critical building blocks available in Europe to advance towards a novel paradigm for LTx. Ex vivo lung perfusion (EVLP) is a clinically used platform to maintain active lung physiology outside the body, making pre-LTx organ engineering a reality. The project aims to advancing EVLP technology to enhance our understanding of transplant rejection through accessible models. By utilizing biobanks of lung biopsies from both clinical LTx cases and established animal models of IRI and rejection, LifeLUNG will apply advanced machine learning and AI-driven deep sequencing to identify key immune factors and gene targets. The latter will be targeted in LifeLUNG with gene therapeutic agents (GTAs) that can be delivered during EVLP to selectively modulate immune responses. Several delivery tools including adeno-associated viral vectors, virus-like particles and lipid nanoparticles, will be tailored to ensure precise and graft-specific gene modulation, enhancing the therapeutic potential for reducing IRI and preventing rejection. Also the efficient production strategies of these GTAs will be an integral part of LifeLUNG. In parallel, LifeLUNG will explore the economic and ethical paradigms of genetic modification of lung transplantation and reflect its implementation into the broader research and clinical framework. The interdisciplinary nature of LifeLUNG will support the training of 15 doctoral candidates across clinical, academic, and industrial sectors, fostering collaboration and the development of transferable skills to advance the research objectives.