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Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies

Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ...

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Autores principales: Varol, Hilal, Ernst, Angela, Cristoferi, Iacopo, Arns, Wolfgang, Baan, Carla C., van Baardwijk, Myrthe, van den Bosch, Thierry, Eckhoff, Jennifer, Harth, Ana, Hesselink, Dennis A., van Kemenade, Folkert J., de Koning, Willem, Kurschat, Christine, Minnee, Robert C., Mustafa, Dana A., Reinders, Marlies E.J., Shahzad-Arshad, Shazia P., Snijders, Malou L.H., Stippel, Dirk, Stubbs, Andrew P., von der Thüsen, Jan, Wirths, Katharina, Becker, Jan U., Clahsen-van Groningen, Marian C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10065817/
https://www.ncbi.nlm.nih.gov/pubmed/36413151
http://dx.doi.org/10.1097/TP.0000000000004372
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author Varol, Hilal
Ernst, Angela
Cristoferi, Iacopo
Arns, Wolfgang
Baan, Carla C.
van Baardwijk, Myrthe
van den Bosch, Thierry
Eckhoff, Jennifer
Harth, Ana
Hesselink, Dennis A.
van Kemenade, Folkert J.
de Koning, Willem
Kurschat, Christine
Minnee, Robert C.
Mustafa, Dana A.
Reinders, Marlies E.J.
Shahzad-Arshad, Shazia P.
Snijders, Malou L.H.
Stippel, Dirk
Stubbs, Andrew P.
von der Thüsen, Jan
Wirths, Katharina
Becker, Jan U.
Clahsen-van Groningen, Marian C.
author_facet Varol, Hilal
Ernst, Angela
Cristoferi, Iacopo
Arns, Wolfgang
Baan, Carla C.
van Baardwijk, Myrthe
van den Bosch, Thierry
Eckhoff, Jennifer
Harth, Ana
Hesselink, Dennis A.
van Kemenade, Folkert J.
de Koning, Willem
Kurschat, Christine
Minnee, Robert C.
Mustafa, Dana A.
Reinders, Marlies E.J.
Shahzad-Arshad, Shazia P.
Snijders, Malou L.H.
Stippel, Dirk
Stubbs, Andrew P.
von der Thüsen, Jan
Wirths, Katharina
Becker, Jan U.
Clahsen-van Groningen, Marian C.
author_sort Varol, Hilal
collection PubMed
description Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ Transplant (B-HOT) panel and a customized antibody-mediated rejection (AMR)–specific NanoString nCounter Elements (Elements) panel. Additionally, we explored the potential for the classification of KTx rejection building and testing a classifier within our dataset. METHODS. Ninety-six formalin-fixed paraffin-embedded KTx biopsies were retrieved from the archives of the ErasmusMC Rotterdam and the University Hospital Cologne. Biopsies with AMR, borderline or T cell–mediated rejections (BLorTCMR), and no rejection were compared using the B-HOT and Elements panels. RESULTS. High correlation between gene expression levels was found when comparing the 2 chemistries pairwise (r = 0.76–0.88). Differential gene expression (false discovery rate; P < 0.05) was identified in biopsies diagnosed with AMR (B-HOT: 294; Elements: 76) and BLorTCMR (B-HOT: 353; Elements: 57) compared with no rejection. Using the most predictive genes from the B-HOT analysis and the Element analysis, 2 least absolute shrinkage and selection operators–based regression models to classify biopsies as AMR versus no AMR (BLorTCMR or no rejection) were developed achieving an receiver-operating–characteristic curve of 0.994 and 0.894, sensitivity of 0.821 and 0.480, and specificity of 1.00 and 0.979, respectively, during cross-validation. CONCLUSIONS. Transcriptomic analysis is feasible on KTx biopsies previously used for diagnostic purposes. The B-HOT panel has the potential to differentiate AMR from BLorTCMR or no rejection and could prove valuable in aiding kidney transplant rejection classification.
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spelling pubmed-100658172023-04-01 Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies Varol, Hilal Ernst, Angela Cristoferi, Iacopo Arns, Wolfgang Baan, Carla C. van Baardwijk, Myrthe van den Bosch, Thierry Eckhoff, Jennifer Harth, Ana Hesselink, Dennis A. van Kemenade, Folkert J. de Koning, Willem Kurschat, Christine Minnee, Robert C. Mustafa, Dana A. Reinders, Marlies E.J. Shahzad-Arshad, Shazia P. Snijders, Malou L.H. Stippel, Dirk Stubbs, Andrew P. von der Thüsen, Jan Wirths, Katharina Becker, Jan U. Clahsen-van Groningen, Marian C. Transplantation Original Basic Science Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ Transplant (B-HOT) panel and a customized antibody-mediated rejection (AMR)–specific NanoString nCounter Elements (Elements) panel. Additionally, we explored the potential for the classification of KTx rejection building and testing a classifier within our dataset. METHODS. Ninety-six formalin-fixed paraffin-embedded KTx biopsies were retrieved from the archives of the ErasmusMC Rotterdam and the University Hospital Cologne. Biopsies with AMR, borderline or T cell–mediated rejections (BLorTCMR), and no rejection were compared using the B-HOT and Elements panels. RESULTS. High correlation between gene expression levels was found when comparing the 2 chemistries pairwise (r = 0.76–0.88). Differential gene expression (false discovery rate; P < 0.05) was identified in biopsies diagnosed with AMR (B-HOT: 294; Elements: 76) and BLorTCMR (B-HOT: 353; Elements: 57) compared with no rejection. Using the most predictive genes from the B-HOT analysis and the Element analysis, 2 least absolute shrinkage and selection operators–based regression models to classify biopsies as AMR versus no AMR (BLorTCMR or no rejection) were developed achieving an receiver-operating–characteristic curve of 0.994 and 0.894, sensitivity of 0.821 and 0.480, and specificity of 1.00 and 0.979, respectively, during cross-validation. CONCLUSIONS. Transcriptomic analysis is feasible on KTx biopsies previously used for diagnostic purposes. The B-HOT panel has the potential to differentiate AMR from BLorTCMR or no rejection and could prove valuable in aiding kidney transplant rejection classification. Lippincott Williams & Wilkins 2022-10-27 2023-04 /pmc/articles/PMC10065817/ /pubmed/36413151 http://dx.doi.org/10.1097/TP.0000000000004372 Text en Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Basic Science
Varol, Hilal
Ernst, Angela
Cristoferi, Iacopo
Arns, Wolfgang
Baan, Carla C.
van Baardwijk, Myrthe
van den Bosch, Thierry
Eckhoff, Jennifer
Harth, Ana
Hesselink, Dennis A.
van Kemenade, Folkert J.
de Koning, Willem
Kurschat, Christine
Minnee, Robert C.
Mustafa, Dana A.
Reinders, Marlies E.J.
Shahzad-Arshad, Shazia P.
Snijders, Malou L.H.
Stippel, Dirk
Stubbs, Andrew P.
von der Thüsen, Jan
Wirths, Katharina
Becker, Jan U.
Clahsen-van Groningen, Marian C.
Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies
title Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies
title_full Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies
title_fullStr Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies
title_full_unstemmed Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies
title_short Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies
title_sort feasibility and potential of transcriptomic analysis using the nanostring ncounter technology to aid the classification of rejection in kidney transplant biopsies
topic Original Basic Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10065817/
https://www.ncbi.nlm.nih.gov/pubmed/36413151
http://dx.doi.org/10.1097/TP.0000000000004372
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