Performance of Molecular Diagnostic Algorithms of T-Cell Mediated Kidney Rejection (TCMR) in Non-Transplant Biopsies with Interstitial Nephritis
1Transplant Pathology, Thomas E Starzl Transplant Institute, University of Pittsburgh, School of Medicine, Pittsburgh, PA
2Epidemiology, Graduate School of Public Health, and University of Pittsburgh, Pittsburgh, PA.
Meeting: 2018 American Transplant Congress
Abstract number: D190
Keywords: Kidney transplantation, Rejection
Session Information
Session Name: Poster Session D: Kidney: Acute Cellular Rejection
Session Type: Poster Session
Date: Tuesday, June 5, 2018
Session Time: 6:00pm-7:00pm
Presentation Time: 6:00pm-7:00pm
Location: Hall 4EF
DNA microarray based tools for the diagnosis of TCMR have been developed and are now being offered commercially. There is need to further evaluate the performance of these tests in the non-transplant kidney, since native disease can recur in the graft and be confused with TCMR.
Accordingly, RNA-seq was performed on 10 renal transplant biopsies, 5 with TCMR and 5 with native interstitial nephritis (ISN). Cross platform external validation was performed on two different sample sets containing a total of 703 biopsies analyzed by DNA microarray technology (GSE48581 INTERCOM 300 Study, and GSE36059 BFC403 study). TCC, EdgeR, Poisson, and DESeq2 packages for R software were used to define differentiated expressed genes (DEGs) between TCMR and ISN. Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM) based machine learning algorithms were also developed to distinguish TCMR from ISN.
ISN & TCMR samples had substantially similar mRNA profiles. The Poisson, TCC, EdgeR, and DESeq2 packages identified 0, 1, 2 & 29 of 47614 transcripts to be differentially regulated between ISN & TCMR (p <0.05, FDR<0.05). IL-17A Signaling, Acute Phase Response Signaling, IL-10 Signaling, JAK/Stat Signaling and HGF Signaling were identified as the top 5 canonical pathways among DEGs. Using data available on the Gene Expression Omnibus, 16 (19.51%) of 82 TCMR transcripts and 20 (36.14%) of 83 antibody mediated rejection (ABMR) transcripts were significantly up-regulated in ISN. LDA & SVM algorithms classified 2 of 5 ISN samples in the TCMR category.
In conclusion, there is significant overlap between gene expression profiles of biopsies with TCMR and ISN. Gene expression based tests for TCMR should be interpreted in conjunction with clinical parameters to avoid over-diagnosis in settings where recurrence of the native disease is also a consideration in the differential diagnosis.
CITATION INFORMATION: Wang Z., Liu P., Tseng G., Zeng G., Randhawa P. Performance of Molecular Diagnostic Algorithms of T-Cell Mediated Kidney Rejection (TCMR) in Non-Transplant Biopsies with Interstitial Nephritis Am J Transplant. 2017;17 (suppl 3).
To cite this abstract in AMA style:
Wang Z, Liu P, Tseng G, Zeng G, Randhawa P. Performance of Molecular Diagnostic Algorithms of T-Cell Mediated Kidney Rejection (TCMR) in Non-Transplant Biopsies with Interstitial Nephritis [abstract]. https://atcmeetingabstracts.com/abstract/performance-of-molecular-diagnostic-algorithms-of-t-cell-mediated-kidney-rejection-tcmr-in-non-transplant-biopsies-with-interstitial-nephritis/. Accessed May 16, 2025.« Back to 2018 American Transplant Congress