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Pre-transplant Renal Ex vivo Imaging and Multi-omics for Advanced Graft Evaluation

Periodic Reporting for period 3 - PRE-IMAGE (Pre-transplant Renal Ex vivo Imaging and Multi-omics for Advanced Graft Evaluation)

Periodo di rendicontazione: 2023-11-01 al 2025-04-30

There is a considerable shortage of kidneys recovered from deceased donors, which are essential to save lives of end stage kidney patients. Hence, more kidneys of marginal quality need to be considered for transplantation. A large percentage of these kidneys ultimately fail, with detrimental consequences for the transplant recipient and the overall healthcare costs. In this context, reliable pre-transplant assessment of organ quality combined with improved organ preservation techniques, have become a top priority to improve the success of transplantation and most important the quality of life of end stage kidney patients.
Ex vivo normothermic machine perfusion is an increasingly used method to better preserve donor kidneys prior to transplantation and presumably improve transplantation success. However, little is known about molecular pathways that are active while the organ is perfused ex vivo at normothermic conditions (35-37 C). Also, there is hardly any data on which molecular processes/biomarkers are relevant to assess organ quality during (normothermic) kidney perfusion and could predict transplant outcome.
In contrast to single biomarker discovery studies, a multi-omics approach has the potential of finding relevant pathways and molecular associations. In real clinical transplantation practice, however, there is only very limited time available between organ retrieval and transplantation and invasive sampling should be reduced to a minimum. Therefore, it will be of paramount importance for actual clinical implementation that multi-omics biomarkers can also be measured with a non-invasive and very rapid method. Magnetic resonance imaging (MRI) provides a promising non-invasive tool to obtain a wealth of additional tissue-specific information about kidney quality and viability. So far, innovative MRI techniques have not been applied to image and characterize ex vivo perfused donor kidneys.
Overall, the PRE-IMAGE project aims to unravel the molecular mechanisms activated during normothermic ex vivo kidney perfusion and identify/validate pre-transplant functional markers as reliable predictors of post-transplant outcome.
The results of PRE-IMAGE will also pave the way to the use of normothermic perfusion in the MRI setting as a non-invasive and rapid diagnostic and prognostic clinical tool prior to transplantation, increasing the success of transplantation with significant consequences for the healthcare costs and the quality of life of end stage renal patients.

The PRE-IMAGE project aims to determine the molecular mechanisms of ex vivo kidney perfusion prior to renal transplantation in order to develop breakthrough pre-transplant perfusion-based diagnostic markers that can indicate kidney transplant outcomes and to establish the added value of pre-transplant normothermic ex vivo kidney perfusion.
From the beginning of the project, I completed all experiments of Objective 1, as well as transcriptomics, proteomics and major parts of metabolomics and radiomics data analyses of those experiments. These analyses show how immensely different ex vivo kidney physiology is compared to the in vivo biological processes that we know. From the start of ex vivo perfusion, and increasingly during perfusion, many normal metabolic and physiologic processes slow down, and inflammatory and protective pathways take over. In addition, in our MRI data, we have found that regional blood flow distribution and oxygen delivery in a kidney during ex vivo perfusion has a different pattern than the normal in vivo distribution, thus contributing to the establishment of a reference frame for what normal and abnormal ex vivo renal physiology looks like.

Logistics and protocols for Objective 2 have been finalized. The experiments described under Objective 2 are currently approximately at two-thirds, with 18 out of 25 discarded human kidneys perfused in an MRI scanner. So far, inclusions for this Objective are progressing smoothly and I expect to finish these inclusions before the end of this year, after which data analyses can commence.

As a result of almost 2 years COVID restrictions I have, unfortunately, not yet been able to start the clinical study as outlined in Objective 3 of the action. This clinical study will be almost 2 years delayed, for which I plan to request an extension of my project. Also, I have initiated an amendment request for the clinical study in Objective 3, in order to be able to also conduct a multi-center randomized clinical trial alongside the clinical kidney perfusions that will be performed. The ethics application for this study has been finalized and will be sent to our medical ethics committee this summer.
PRE-IMAGE utilizes a multi-omics approach combined with a precise imaging technique such as MRI to address its objectives. This multi-modal approach has never been used so far to unravel relevant molecular/biological pathways occurring during (normothermic) ex vivo perfusion and to allow the identification of novel diagnostic and prognostic pre-transplant biomarkers.
The advantage of the broad multi-omics approach is that it incorporates different biological layers of information at once, therefore providing a more reliable assessment of kidney biology compared to individual omics approaches. Moreover, to be able to perform reliable pre-transplant quality assessment in a short time frame and in a non-invasive way, MRI techniques/radiomics have been used and optimized for the first time in the normothermic perfusion setting. Indeed, to be able to use MRI during kidney perfusion, we have invented a novel tethered machine perfusion machinery with no MRI-sensitive components and we have used it to perform a series of successful perfusion experiments.
In the time left until the end of the project, I aim to perform a prospective clinical study to validate conventional and novel multi-omics markers which indicate the chance of kidney transplant success. With machine learning techniques, multi-omics measurements and standard clinical variables will be associated with actual transplant results, to create advanced prediction models for post-transplant outcome.
Moreover, I will explore the correlation between multi-omics and radiomic markers in order to set the basis for future clinical studies aimed at replacing invasive and tissue/perfusate analyses with non-invasive ex vivo MRI prior to transplantation.
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