Application of RNA-Seq Derived Diagnostic Algorithms of T-Cell Mediated Kidney Rejection (TCMR) to DNA Microarray-Based Gene Expression Datasets
1Department of Pathology, The Thomas E Starzl Transplantation Institute, University of Pittsburgh, School of Medicine, Pittsburgh, PA
2Department of Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
3Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA.
Meeting: 2018 American Transplant Congress
Abstract number: B2
Keywords: Kidney transplantation, Rejection
Session Information
Session Name: Poster Session B: Acute and Chronic Graft Injury
Session Type: Poster Session
Date: Sunday, June 3, 2018
Session Time: 6:00pm-7:00pm
Presentation Time: 6:00pm-7:00pm
Location: Hall 4EF
Recent years have seen the development of DNA microarray based tools for the diagnosis of TCMR using fresh frozen tissue. This study has accomplished the same goal with RNA-seq performed on formalin fixed tissue, using the same biopsy core for interrogating both histologic and molecular changes.
RNA-seq was performed on 10 renal transplant biopsies, 5 with TCMR and 5 with stable (STA) function. Differential gene expression was evaluated by the DESeq2 package in R. Machine learning tools were developed to distinguish between TCMR and STA . 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).
Biopsy material typically yielded ~ 25,000 mRNA sequences per sample. A total of 252 genes were found differentially expressed between TCMR and STA samples. Internal cross validation using five-fold leave-out-one-cross-validation demonstrated sensitivity and specificity of 100% with the Support Vector Machines algorithm, and 80% for linear discriminant analysis (LDA). The LDA based training algorithm correctly predicted TCMR in 58/67 biopsies in the external validation dataset, TCMR was also identified in 74/105 biopsies designated as antibody-mediated rejection (ABMR)and 259/503 that were classified as Non-Rejection.
These data illustrate the feasibility of implementing RNAseq as a molecular diagnostic tool for routinely processed formalin fixed specimens. Biopsies labeled simply as ABMR were frequently found to have co-existent TCMR highlighting the fact that mixed ABMR-TCMR is much more common than is currently recognized. The presence of a TCMR-like RNA-seq signature in a significant number of biopsies labeled as Non-rejection highlights a need to develop bioinformatics tools that would allow more precise molecular sub-classification of this category into diseases that are mimics of acute rejection, including currently undiagnosed smoldering TCMR, infection associated interstitial nephritis, drug hypersensitivity reactions, and recurrent glomerulonephritis.
CITATION INFORMATION: Wang Z., Pan L., Lyu Z., Liu P., Tseng G., Randhawa P. Application of RNA-Seq Derived Diagnostic Algorithms of T-Cell Mediated Kidney Rejection (TCMR) to DNA Microarray-Based Gene Expression Datasets Am J Transplant. 2017;17 (suppl 3).
To cite this abstract in AMA style:
Wang Z, Pan L, Lyu Z, Liu P, Tseng G, Randhawa P. Application of RNA-Seq Derived Diagnostic Algorithms of T-Cell Mediated Kidney Rejection (TCMR) to DNA Microarray-Based Gene Expression Datasets [abstract]. https://atcmeetingabstracts.com/abstract/application-of-rna-seq-derived-diagnostic-algorithms-of-t-cell-mediated-kidney-rejection-tcmr-to-dna-microarray-based-gene-expression-datasets/. Accessed June 27, 2025.« Back to 2018 American Transplant Congress