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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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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. |
format | Online Article Text |
id | pubmed-10065817 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
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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