Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Author:

Farkona Sofia12,Pastrello Chiara34,Konvalinka Ana12567

Affiliation:

1. Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada.

2. Soham and Shaila Ajmera Family Transplant Centre, University Health Network, Toronto, ON, Canada.

3. Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute University Health Network, Toronto, ON, Canada.

4. Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.

5. Department of Medicine, Division of Nephrology, University Health Network, Toronto, ON, Canada.

6. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.

7. Institute of Medical Science, University of Toronto, Toronto, ON, Canada.

Abstract

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Transplantation

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