Literature DB >> 18667728

Intragraft levels of Foxp3 mRNA predict progression in renal transplants with borderline change.

Hicham Mansour1, Sébastien Homs, Dominique Desvaux, Cécile Badoual, Karine Dahan, Marie Matignon, Vincent Audard, Philippe Lang, Philippe Grimbert.   

Abstract

The optimal therapeutic management of borderline lymphocytic infiltrates in renal allografts, described by Banff criteria, is unknown, largely because of the inability to predict clinical outcome in these cases. For determination of molecular factors that may predict outcome in cases of borderline change histology, mRNA levels of Foxp3, Granzyme B, IFN-gamma, IL-23, and RORgammat were measured in renal tissue from 46 untreated patients. Twenty-five patients were considered "nonprogressive," defined by a serum creatinine that remained <110% of baseline during the 40 d after biopsy. Twenty-one patients were considered "progressive," defined by an increase in serum creatinine >110% from baseline and by repeat histologic examination within 40 d showing progression toward acute rejection. Only Foxp3 mRNA levels were significantly higher in nonprogressors than in progressors (P = 0.001). Analysis of receiver operating characteristic curves demonstrated that the outcome for patients with biopsies showing borderline change could be predicted with 90% sensitivity and 79.1% specificity using the optimal Foxp3 mRNA cutoff value. Our findings suggest that the measurement of Foxp3 mRNA offers a means of improving prediction of outcome of borderline change.

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Year:  2008        PMID: 18667728      PMCID: PMC2588097          DOI: 10.1681/ASN.2008030254

Source DB:  PubMed          Journal:  J Am Soc Nephrol        ISSN: 1046-6673            Impact factor:   10.121


  19 in total

1.  The relationship of untreated borderline infiltrates by the Banff criteria to acute rejection in renal allograft biopsies.

Authors:  S M Meehan; C T Siegel; A J Aronson; S M Bartosh; J R Thistlethwaite; E S Woodle; M Haas
Journal:  J Am Soc Nephrol       Date:  1999-08       Impact factor: 10.121

2.  Clinical significance of renal allograft biopsies with "borderline changes," as defined in the Banff Schema.

Authors:  R Saad; H A Gritsch; R Shapiro; M Jordan; C Vivas; V Scantlebury; A J Demetris; P S Randhawa
Journal:  Transplantation       Date:  1997-10-15       Impact factor: 4.939

3.  Early protocol renal allograft biopsies and graft outcome.

Authors:  D Serón; F Moreso; J Bover; E Condom; S Gil-Vernet; C Cañas; X Fulladosa; J Torras; M Carrera; J M Grinyó; J Alsina
Journal:  Kidney Int       Date:  1997-01       Impact factor: 10.612

4.  Correlation of clinical outcomes after tacrolimus conversion for resistant kidney rejection or cyclosporine toxicity with pathologic staging by the Banff criteria.

Authors:  P E Morrissey; R Gohh; D Shaffer; A Crosson; P N Madras; A I Sahyoun; A P Monaco
Journal:  Transplantation       Date:  1997-03-27       Impact factor: 4.939

5.  Sequential protocol biopsies in renal transplant patients. Clinico-pathological correlations using the Banff schema.

Authors:  D N Rush; J R Jeffery; J Gough
Journal:  Transplantation       Date:  1995-02-27       Impact factor: 4.939

6.  Significance of the Banff borderline biopsy.

Authors:  E J Schweitzer; C B Drachenberg; L Anderson; J C Papadimetriou; P C Kuo; L B Johnson; D K Klassen; E Hoehn-Saric; M R Weir; S T Bartlett
Journal:  Am J Kidney Dis       Date:  1996-10       Impact factor: 8.860

7.  Correlation between Banff classification, acute renal rejection scores and reversal of rejection.

Authors:  L W Gaber; L W Moore; R R Alloway; S D Flax; M H Shokouh-Amiri; T Schroder; A O Gaber
Journal:  Kidney Int       Date:  1996-02       Impact factor: 10.612

8.  HLA-mismatched renal transplantation without maintenance immunosuppression.

Authors:  Tatsuo Kawai; A Benedict Cosimi; Thomas R Spitzer; Nina Tolkoff-Rubin; Manikkam Suthanthiran; Susan L Saidman; Juanita Shaffer; Frederic I Preffer; Ruchuang Ding; Vijay Sharma; Jay A Fishman; Bimalangshu Dey; Dicken S C Ko; Martin Hertl; Nelson B Goes; Waichi Wong; Winfred W Williams; Robert B Colvin; Megan Sykes; David H Sachs
Journal:  N Engl J Med       Date:  2008-01-24       Impact factor: 91.245

9.  Molecular diagnosis of renal-allograft rejection: correlation with histopathologic evaluation and antirejection-therapy resistance.

Authors:  Dominique Desvaux; Michaël Schwarzinger; Myriam Pastural; Christophe Baron; Mahdi Abtahi; François Berrehar; Annick Lim; Philippe Lang; Sabine le Gouvello
Journal:  Transplantation       Date:  2004-09-15       Impact factor: 4.939

10.  Phenotypic and functional features of human Th17 cells.

Authors:  Francesco Annunziato; Lorenzo Cosmi; Veronica Santarlasci; Laura Maggi; Francesco Liotta; Benedetta Mazzinghi; Eliana Parente; Lucia Filì; Simona Ferri; Francesca Frosali; Francesco Giudici; Paola Romagnani; Paola Parronchi; Francesco Tonelli; Enrico Maggi; Sergio Romagnani
Journal:  J Exp Med       Date:  2007-07-16       Impact factor: 14.307

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  11 in total

Review 1.  FOXP3-Positive Regulatory T Cells and Kidney Allograft Tolerance.

Authors:  Alessandro Alessandrini; Laurence A Turka
Journal:  Am J Kidney Dis       Date:  2016-12-31       Impact factor: 8.860

2.  RNA expression profiling of nonhuman primate renal allograft rejection identifies tolerance.

Authors:  R N Smith; M Matsunami; B A Adam; I A Rosales; T Oura; A B Cosimi; T Kawai; M Mengel; R B Colvin
Journal:  Am J Transplant       Date:  2018-02-17       Impact factor: 8.086

Review 3.  Clinical role of the renal transplant biopsy.

Authors:  Winfred W Williams; Diana Taheri; Nina Tolkoff-Rubin; Robert B Colvin
Journal:  Nat Rev Nephrol       Date:  2012-01-10       Impact factor: 28.314

Review 4.  Tempering allorecognition to induce transplant tolerance with chemically modified apoptotic donor cells.

Authors:  D P McCarthy; J Bryant; J P Galvin; S D Miller; X Luo
Journal:  Am J Transplant       Date:  2015-03-23       Impact factor: 8.086

5.  Optimizing PLG nanoparticle-peptide delivery platforms for transplantation tolerance using an allogeneic skin transplant model.

Authors:  Sahil Shah; Saeed Daneshmandi; Kevin R Hughes; Shuangjin Yu; Angela M Bedoya; Lonnie D Shea; Xunrong Luo
Journal:  Biomaterials       Date:  2019-05-01       Impact factor: 12.479

6.  Are we ready for the use of foxp3(+) regulatory T cells for immunodiagnosis and immunotherapy in kidney transplantation?

Authors:  Francisco Salcido-Ochoa; Nurhashikin Yusof; Susan Swee-Shan Hue; Doreen Haase; Terence Kee; Olaf Rotzschke
Journal:  J Transplant       Date:  2012-05-29

7.  Immunosuppressive effects of streptozotocin-induced diabetes result in absolute lymphopenia and a relative increase of T regulatory cells.

Authors:  Yannick D Muller; Déla Golshayan; Driss Ehirchiou; Jean Christophe Wyss; Laurianne Giovannoni; Raphael Meier; Véronique Serre-Beinier; Gisella Puga Yung; Philippe Morel; Leo H Bühler; Jörg D Seebach
Journal:  Diabetes       Date:  2011-07-13       Impact factor: 9.461

8.  Association of Foxp3 Polymorphism With Allograft Outcome in Kidney Transplantation.

Authors:  Hyewon Park; Nuri Lee; Ji Won In; Eun Youn Roh; Kyoung Un Park; Sue Shin; Jaeseok Yang; Eun Young Song
Journal:  Ann Lab Med       Date:  2017-09       Impact factor: 3.464

Review 9.  Regulatory T cells in the immunodiagnosis and outcome of kidney allograft rejection.

Authors:  O Franzese; A Mascali; A Capria; V Castagnola; L Paganizza; N Di Daniele
Journal:  Clin Dev Immunol       Date:  2013-06-15

10.  Transient increase of activated regulatory T cells early after kidney transplantation.

Authors:  Young-Seon Mederacke; Florian W Vondran; Sonja Kollrich; Elvira Schulde; Roland Schmitt; Michael P Manns; Jürgen Klempnauer; Reinhard Schwinzer; Fatih Noyan; Elmar Jaeckel
Journal:  Sci Rep       Date:  2019-01-31       Impact factor: 4.379

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