TY - JOUR
T1 - Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies
AU - Varol, Hilal
AU - Ernst, Angela
AU - Cristoferi, Iacopo
AU - Arns, Wolfgang
AU - Baan, Carla C.
AU - van Baardwijk, Myrthe
AU - van den Bosch, Thierry
AU - Eckhoff, Jennifer
AU - Harth, Ana
AU - Hesselink, Dennis A.
AU - van Kemenade, Folkert J.
AU - de Koning, Willem
AU - Kurschat, Christine
AU - Minnee, Robert C.
AU - Mustafa, Dana A.
AU - Reinders, Marlies E. J.
AU - Shahzad-Arshad, Shazia P.
AU - Snijders, Malou L. H.
AU - Stippel, Dirk
AU - Stubbs, Andrew P.
AU - von der Thüsen, Jan
AU - Wirths, Katharina
AU - Becker, Jan U.
AU - Clahsen-van Groningen, Marian C.
N1 - Funding Information: This project has in part been financially supported by an Astellas project funding (M.C.C.v.-G.). This study is also supported by an intramural grant Köln Fortune (J.U.B.). Publisher Copyright: © 2023 Lippincott Williams and Wilkins. All rights reserved.
PY - 2023/4/1
Y1 - 2023/4/1
N2 - Background. 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.
AB - Background. 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.
UR - http://www.scopus.com/inward/record.url?scp=85151575243&partnerID=8YFLogxK
U2 - https://doi.org/10.1097/TP.0000000000004372
DO - https://doi.org/10.1097/TP.0000000000004372
M3 - Article
C2 - 36413151
SN - 0041-1337
VL - 107
SP - 903
EP - 912
JO - Transplantation
JF - Transplantation
IS - 4
ER -