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Proteomics Clin Appl. 2019 Jan 25:e1800091. doi: 10.1002/prca.201800091. [Epub ahead of print]

Proteomics in Kidney Allograft Transplantation-Application of Molecular Pathway Analysis for Kidney Allograft Disease Phenotypic Biomarker Selection.

Author information

1
Nephrology - Transplantation Department, UMR_S. INSERM UMR_S 1109, ImmunoRhumatologie Moléculaire, Fédération Hospitalo-Universitaire OMICARE, Fédération de Médecine Translationnelle de Strasbourg, Institut d'Immunologie et d'Hématologie, 67085, Strasbourg, France.
2
Laboratoire de Spectrométrie de Masse BioOrganique, University of Strasbourg, Centre National de la Recherche Scientifique, Institut Pluridisciplinaire Hubert Curien, UMR 7178, 67037, Strasbourg, France.
3
Mosaiques Diagnostics GmbH, 30659, Hannover, Germany.
4
Department of Pathology, University Hospital of Strasbourg, 67091, Strasbourg, France.
5
Department of Nephrology and Organ Transplantation, University Hospital of Toulouse, 31059, Toulouse, France.
6
Institut National de la Santé et de la Recherche Médicale (INSERM), Institut of Cardiovascular and Metabolic Disease, U1048, 31432, Toulouse, France.
7
Université Toulouse III Paul-Sabatier, 31330, Toulouse, France.
8
Department of Pathology, Cancer University Institute of Toulouse, 31100, Toulouse, France.
9
Division of Biomedical Sciences, Centre for Health Science, University of the Highlands and Islands, Inverness, IV2 3JH, UK.
10
Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, United Kingdom.
11
Department of Nephrology, Hannover Medical School, 30625, Hannover, Germany.

Abstract

There is a need for accurate, robust, non-invasive methods to provide early diagnosis of graft lesions after kidney transplantation. A multitude of proteomic biomarkers for the major kidney allograft disease phenotypes defined by the BANFF classification criteria have been described in literature. None of these biomarkers have been established in the clinic. A key reason for this is the lack of clinical validation which is difficult, as even the gold standard of diagnosis, kidney biopsy, is often ambiguous. The semantic clustering by ReviGO on top of transcriptomic pathway analysis is evaluated to connect histological and transcriptomic kidney allograft disease characteristics with proteomic biomarker qualification. By using public data generated in microarray studies of kidney allograft tissue, biological processes and key molecules specifically associated with the different kidney allograft disease phenotypes are identified. Semantic clustering holds the promise to guide adaptation of proteomic marker panels to molecular pathology. This can support the development of noninvasive tests (e.g. in urine, by capillary electrophoresis mass spectrometry) that simultaneously detect diverse kidney allograft phenotypes with high accuracy and sensitivity.

KEYWORDS:

allograft biopsy; biomolecular pathways; kidney transplantation; protein marker selection; proteomics

PMID:
30680934
DOI:
10.1002/prca.201800091

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