Saint-Mezard, Pierre; Berthier, Céline C; Zhang, Hai; Hertig, Alexandre; Kaiser, Sergio; Schumacher, Martin; Wieczorek, Grazyna; Bigaud, Marc; Kehren, Jeanne; Rondeau, Eric; Raulf, Friedrich; Marti, Hans-Peter (2009). Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection. Transplant international, 22(3), pp. 293-302. Oxford: Wiley-Blackwell 10.1111/j.1432-2277.2008.00790.x
Full text not available from this repository.Transcriptomics could contribute significantly to the early and specific diagnosis of rejection episodes by defining 'molecular Banff' signatures. Recently, the description of pathogenesis-based transcript sets offered a new opportunity for objective and quantitative diagnosis. Generating high-quality transcript panels is thus critical to define high-performance diagnostic classifier. In this study, a comparative analysis was performed across four different microarray datasets of heterogeneous sample collections from two published clinical datasets and two own datasets including biopsies for clinical indication, and samples from nonhuman primates. We characterized a common transcriptional profile of 70 genes, defined as acute rejection transcript set (ARTS). ARTS expression is significantly up-regulated in all AR samples as compared with stable allografts or healthy kidneys, and strongly correlates with the severity of Banff AR types. Similarly, ARTS were tested as a classifier in a large collection of 143 independent biopsies recently published by the University of Alberta. Results demonstrate that the 'in silico' approach applied in this study is able to identify a robust and reliable molecular signature for AR, supporting a specific and sensitive molecular diagnostic approach for renal transplant monitoring.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Dermatology, Urology, Rheumatology, Nephrology, Osteoporosis (DURN) > Clinic of Nephrology and Hypertension |
UniBE Contributor: |
Marti, Hans-Peter |
ISSN: |
0934-0874 |
ISBN: |
19017305 |
Publisher: |
Wiley-Blackwell |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 15:05 |
Last Modified: |
05 Dec 2022 14:20 |
Publisher DOI: |
10.1111/j.1432-2277.2008.00790.x |
PubMed ID: |
19017305 |
Web of Science ID: |
000262954000005 |
URI: |
https://boris.unibe.ch/id/eprint/28091 (FactScience: 116584) |