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

接收机工作特性 医学 活检 转录组 肾移植 病理 移植 内科学 基因表达 生物 基因 生物化学
作者
Hilal Varol,Angela Ernst,Iacopo Cristoferi,Wolfgang Arns,Carla C. Baan,Myrthe van Baardwijk,Thierry van den Bosch,Jennifer A. Eckhoff,Ana Harth,Dennis A. Hesselink,Folkert J. van Kemenade,Willem de Koning,Christine Kurschat,Robert C. Minnee,Dana A.M. Mustafa,Marlies E. J. Reinders,Shazia P. Shahzad-Arshad,Malou L.H. Snijders,Dirk L. Stippel,Andrew Stubbs,Jan H. von der Thüsen,Katharina Wirths,Jan U. Becker,Marian C. Clahsen‐van Groningen
出处
期刊:Transplantation [Ovid Technologies (Wolters Kluwer)]
卷期号:107 (4): 903-912 被引量:11
标识
DOI:10.1097/tp.0000000000004372
摘要

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.

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