Literature DB >> 19935467

Functional genomic analysis of peripheral blood during early acute renal allograft rejection.

Oliver P Günther1, Robert F Balshaw, Andreas Scherer, Zsuzsanna Hollander, Alice Mui, Timothy J Triche, Gabriela Cohen Freue, Guiyun Li, Raymond T Ng, Janet Wilson-McManus, W Robert McMaster, Bruce M McManus, Paul A Keown.   

Abstract

BACKGROUND: Acute graft rejection is an important clinical problem in renal transplantation and an adverse predictor for long-term graft survival. Peripheral blood biomarkers that provide evidence of early graft rejection may offer an important option for posttransplant monitoring, optimize the utility of graft biopsy, and permit timely and effective therapeutic intervention to minimize the graft damage.
METHODS: In this feasibility study (n=58), we have used gene expression profiling in a case-control design to compare whole blood samples between normal subjects (n=20) and patients with (n=11) or without (n=22) biopsy-confirmed acute rejection (BCAR) or borderline changes (n=5).
RESULTS: A total of 183 probe sets representing 160 genes were differentially expressed (false discovery rate [FDR] <0.01) between subjects with or without BCAR, from which linear discriminant analysis and cross-validation identified an initial gene signature of 24 probe sets, and a more refined set of 11 probe sets found to classify subject samples correctly. Cross-validation suggested an out-of-sample sensitivity of 73% and specificity of 91% for identification of samples with or without BCAR. An increase in classifier gene expression correlated closely with acute rejection during the first 3 months posttransplant. Biological evaluation indicated that the differentially expressed genes encompassed processes related to immune response, signal transduction, and cytoskeletal reorganization.
CONCLUSION: Preliminary evidence indicates that gene expression in the peripheral blood may yield a relevant measure for the occurrence of BCAR and offer a potential tool for immunologic monitoring. These results now require confirmation in a larger cohort.

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Year:  2009        PMID: 19935467     DOI: 10.1097/TP.0b013e3181b7ccc6

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  16 in total

Review 1.  Molecular diagnostics in transplantation.

Authors:  Maarten Naesens; Minnie M Sarwal
Journal:  Nat Rev Nephrol       Date:  2010-08-24       Impact factor: 28.314

2.  Development of a cross-platform biomarker signature to detect renal transplant tolerance in humans.

Authors:  Pervinder Sagoo; Esperanza Perucha; Birgit Sawitzki; Stefan Tomiuk; David A Stephens; Patrick Miqueu; Stephanie Chapman; Ligia Craciun; Ruhena Sergeant; Sophie Brouard; Flavia Rovis; Elvira Jimenez; Amany Ballow; Magali Giral; Irene Rebollo-Mesa; Alain Le Moine; Cecile Braudeau; Rachel Hilton; Bernhard Gerstmayer; Katarzyna Bourcier; Adnan Sharif; Magdalena Krajewska; Graham M Lord; Ian Roberts; Michel Goldman; Kathryn J Wood; Kenneth Newell; Vicki Seyfert-Margolis; Anthony N Warrens; Uwe Janssen; Hans-Dieter Volk; Jean-Paul Soulillou; Maria P Hernandez-Fuentes; Robert I Lechler
Journal:  J Clin Invest       Date:  2010-05-24       Impact factor: 14.808

3.  Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study.

Authors:  Oliver P Günther; Heesun Shin; Raymond T Ng; W Robert McMaster; Bruce M McManus; Paul A Keown; Scott J Tebbutt; Kim-Anh Lê Cao
Journal:  OMICS       Date:  2014-11

Review 4.  Therapeutic cancer vaccines and translating vaccinomics science to the global health clinic: emerging applications toward proof of concept.

Authors:  Megan M O'Meara; Mary L Disis
Journal:  OMICS       Date:  2011-07-06

5.  Characterization of acute renal allograft rejection by proteomic analysis of renal tissue in rat.

Authors:  Gang Chen; Jing-Bin Huang; Jie Mi; Yun-Feng He; Xiao-Hou Wu; Chun-Li Luo; Si-Min Liang; Jia-Bing Li; Ya-Xiong Tang; Jie Li
Journal:  Mol Biol Rep       Date:  2011-05-22       Impact factor: 2.316

6.  CXCL10 and CXCL13 Expression were highly up-regulated in peripheral blood mononuclear cells in acute rejection and poor response to anti-rejection therapy.

Authors:  Youying Mao; Minmin Wang; Qin Zhou; Juan Jin; Yucheng Wang; Wenhan Peng; Jianyong Wu; Zhangfei Shou; Jianghua Chen
Journal:  J Clin Immunol       Date:  2010-12-30       Impact factor: 8.317

7.  Identification of Candidate Biomarkers for Transplant Rejection from Transcriptome Data: A Systematic Review.

Authors:  Sheyla Velasques Paladini; Graziela Hünning Pinto; Rodrigo Haas Bueno; Raquel Calloni; Mariana Recamonde-Mendoza
Journal:  Mol Diagn Ther       Date:  2019-08       Impact factor: 4.074

8.  Proteomic signatures in plasma during early acute renal allograft rejection.

Authors:  Gabriela V Cohen Freue; Mayu Sasaki; Anna Meredith; Oliver P Günther; Axel Bergman; Mandeep Takhar; Alice Mui; Robert F Balshaw; Raymond T Ng; Nina Opushneva; Zsuzsanna Hollander; Guiyun Li; Christoph H Borchers; Janet Wilson-McManus; Bruce M McManus; Paul A Keown; W Robert McMaster
Journal:  Mol Cell Proteomics       Date:  2010-05-25       Impact factor: 5.911

9.  Deconvoluting post-transplant immunity: cell subset-specific mapping reveals pathways for activation and expansion of memory T, monocytes and B cells.

Authors:  Yevgeniy A Grigoryev; Sunil M Kurian; Zafi Avnur; Dominic Borie; Jun Deng; Daniel Campbell; Joanna Sung; Tania Nikolcheva; Anthony Quinn; Howard Schulman; Stanford L Peng; Randolph Schaffer; Jonathan Fisher; Tony Mondala; Steven Head; Stuart M Flechner; Aaron B Kantor; Christopher Marsh; Daniel R Salomon
Journal:  PLoS One       Date:  2010-10-14       Impact factor: 3.240

10.  A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers.

Authors:  Oliver P Günther; Virginia Chen; Gabriela Cohen Freue; Robert F Balshaw; Scott J Tebbutt; Zsuzsanna Hollander; Mandeep Takhar; W Robert McMaster; Bruce M McManus; Paul A Keown; Raymond T Ng
Journal:  BMC Bioinformatics       Date:  2012-12-08       Impact factor: 3.169

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