Literature DB >> 23802725

Multicenter evaluation of a standardized protocol for noninvasive gene expression profiling.

K S Keslar1, M Lin, A A Zmijewska, T K Sigdel, T Q Tran, L Ma, M Bhasin, P Rao, R Ding, D N Iklé, R B Mannon, M M Sarwal, T B Strom, E F Reed, P S Heeger, M Suthanthiran, R L Fairchild.   

Abstract

Gene expression profiling of transplant recipient blood and urine can potentially be used to monitor graft function, but the multitude of protocols in use make sharing data and comparing results from different laboratories difficult. The goal of this study was to evaluate the performance of current methods of RNA isolation, reverse transcription and quantitative polymerase chain reaction (qPCR) and to test whether multiple centers using a standardized protocol can obtain the same results. Samples, reagents and detailed instructions were distributed to six participating sites that performed RNA isolation, reverse transcription and qPCR for 18S, PRF, GZB, IL8, CXCL9 and CXCL10 as instructed. All data were analyzed at a single site. All sites demonstrated proficiency in RNA isolation and qPCR analysis. Gene expression measurements for all targets and samples had correlations >0.938. The coefficient of variation of fold-changes between pairs of samples was less than 40%. All sites were able to accurately quantify a control sample of known concentration within a factor of 1.5. Collectively, we have formulated and validated detailed methods for measuring gene expression in blood and urine that can yield consistent results in multiple laboratories. © Copyright 2013 The American Society of Transplantation and the American Society of Transplant Surgeons.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23802725      PMCID: PMC3781926          DOI: 10.1111/ajt.12284

Source DB:  PubMed          Journal:  Am J Transplant        ISSN: 1600-6135            Impact factor:   8.086


  31 in total

1.  Noninvasive diagnosis of renal-allograft rejection by measurement of messenger RNA for perforin and granzyme B in urine.

Authors:  B Li; C Hartono; R Ding; V K Sharma; R Ramaswamy; B Qian; D Serur; J Mouradian; J E Schwartz; M Suthanthiran
Journal:  N Engl J Med       Date:  2001-03-29       Impact factor: 91.245

2.  Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Authors:  K J Livak; T D Schmittgen
Journal:  Methods       Date:  2001-12       Impact factor: 3.608

3.  Granzyme B, FAS-ligand and perforin expression during acute cellular rejection episodes after kidney transplantation: comparison between blood and renal aspirates.

Authors:  Marcos V Pádua Netto; B A L Fonseca; M Dantas; L T S Saber; M C R Castro; A S Ferraz
Journal:  Transplant Proc       Date:  2002-03       Impact factor: 1.066

4.  Serial peripheral blood perforin and granzyme B gene expression measurements for prediction of acute rejection in kidney graft recipients.

Authors:  Tania Simon; Gerhard Opelz; Manfred Wiesel; Ralf C Ott; Caner Süsal
Journal:  Am J Transplant       Date:  2003-09       Impact factor: 8.086

5.  Noninvasive detection of renal allograft inflammation by measurements of mRNA for IP-10 and CXCR3 in urine.

Authors:  Ravi Raju Tatapudi; Thangamani Muthukumar; Darshana Dadhania; Ruchuang Ding; Baogui Li; Vijay K Sharma; Elizabeth Lozada-Pastorio; Nagashree Seetharamu; Choli Hartono; David Serur; Surya V Seshan; Sandip Kapur; Wayne W Hancock; Manikkam Suthanthiran
Journal:  Kidney Int       Date:  2004-06       Impact factor: 10.612

6.  Molecular signatures of urinary cells distinguish acute rejection of renal allografts from urinary tract infection.

Authors:  Darshana Dadhania; Thangamani Muthukumar; Ruchuang Ding; Baogui Li; Choli Hartono; David Serur; Surya V Seshan; Vijay K Sharma; Sandip Kapur; Manikkam Suthanthiran
Journal:  Transplantation       Date:  2003-05-27       Impact factor: 4.939

7.  Quantitative detection of T-cell activation markers by real-time PCR in renal transplant rejection and correlation with histopathologic evaluation.

Authors:  Omaima Sabek; M Tevfik Dorak; Malak Kotb; A Osama Gaber; Lillian Gaber
Journal:  Transplantation       Date:  2002-09-15       Impact factor: 4.939

8.  Cytotoxic lymphocyte gene expression in peripheral blood leukocytes correlates with rejecting renal allografts.

Authors:  L M Vasconcellos; A D Schachter; X X Zheng; L H Vasconcellos; M Shapiro; W E Harmon; T B Strom; D Schachter
Journal:  Transplantation       Date:  1998-09-15       Impact factor: 4.939

9.  An international multicenter performance analysis of cytomegalovirus load tests.

Authors:  Hans H Hirsch; Irmeli Lautenschlager; Benjamin A Pinsky; Laura Cardeñoso; Shagufta Aslam; Bryan Cobb; Regis A Vilchez; Alexandra Valsamakis
Journal:  Clin Infect Dis       Date:  2012-10-24       Impact factor: 9.079

10.  Two-fold differences are the detection limit for determining transgene copy numbers in plants by real-time PCR.

Authors:  Ben Bubner; Klaus Gase; Ian T Baldwin
Journal:  BMC Biotechnol       Date:  2004-07-13       Impact factor: 2.563

View more
  16 in total

Review 1.  Moving Biomarkers toward Clinical Implementation in Kidney Transplantation.

Authors:  Madhav C Menon; Barbara Murphy; Peter S Heeger
Journal:  J Am Soc Nephrol       Date:  2017-01-06       Impact factor: 10.121

Review 2.  Transplant genetics and genomics.

Authors:  Joshua Y C Yang; Minnie M Sarwal
Journal:  Nat Rev Genet       Date:  2017-03-13       Impact factor: 53.242

Review 3.  Biomarkers for kidney transplant rejection.

Authors:  Denise J Lo; Bruce Kaplan; Allan D Kirk
Journal:  Nat Rev Nephrol       Date:  2014-01-21       Impact factor: 28.314

4.  The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.

Authors:  Tara K Sigdel; Nathan Salomonis; Carrie D Nicora; Soyoung Ryu; Jintang He; Van Dinh; Daniel J Orton; Ronald J Moore; Szu-Chuan Hsieh; Hong Dai; Minh Thien-Vu; Wenzhong Xiao; Richard D Smith; Wei-Jun Qian; David G Camp; Minnie M Sarwal
Journal:  Mol Cell Proteomics       Date:  2013-12-12       Impact factor: 5.911

5.  Multi-gene technical assessment of qPCR and NanoString n-Counter analysis platforms in cynomolgus monkey cardiac allograft recipients.

Authors:  Emily A S Bergbower; Richard N Pierson; Agnes M Azimzadeh
Journal:  Cell Immunol       Date:  2019-11-08       Impact factor: 4.868

Review 6.  Allograft rejection and tubulointerstitial fibrosis in human kidney allografts: interrogation by urinary cell mRNA profiling.

Authors:  Thangamani Muthukumar; John R Lee; Darshana M Dadhania; Ruchuang Ding; Vijay K Sharma; Joseph E Schwartz; Manikkam Suthanthiran
Journal:  Transplant Rev (Orlando)       Date:  2014-05-27       Impact factor: 3.943

Review 7.  Genomic and proteomic fingerprints of acute rejection in peripheral blood and urine.

Authors:  Song Ong; Roslyn B Mannon
Journal:  Transplant Rev (Orlando)       Date:  2014-12-10       Impact factor: 3.943

Review 8.  Urinary cell mRNA profiles predictive of human kidney allograft status.

Authors:  John R Lee; Thangamani Muthukumar; Darshana Dadhania; Ruchuang Ding; Vijay K Sharma; Joseph E Schwartz; Manikkam Suthanthiran
Journal:  Immunol Rev       Date:  2014-03       Impact factor: 12.988

9.  Multicenter Analysis of Immune Biomarkers and Heart Transplant Outcomes: Results of the Clinical Trials in Organ Transplantation-05 Study.

Authors:  R C Starling; J Stehlik; D A Baran; B Armstrong; J R Stone; D Ikle; Y Morrison; N D Bridges; P Putheti; T B Strom; M Bhasin; I Guleria; A Chandraker; M Sayegh; K P Daly; D M Briscoe; P S Heeger
Journal:  Am J Transplant       Date:  2015-08-10       Impact factor: 8.086

Review 10.  The Use of Genomics and Pathway Analysis in Our Understanding and Prediction of Clinical Renal Transplant Injury.

Authors:  Madhav C Menon; Karen L Keung; Barbara Murphy; Philip J OʼConnell
Journal:  Transplantation       Date:  2016-07       Impact factor: 4.939

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.