Potential impact of microarray diagnosis of T cell-mediated rejection in kidney transplants: the INTERCOM study
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE48581 | GEO | 2013/09/15
SECONDARY ACCESSION(S): PRJNA210742
REPOSITORIES: GEO
Similar Datasets
Project description:The authors report that in INTERCOM, a prospective international study of 300 kidney transplant biopsies, a microarray-based molecular score for T cell-mediated rejection changed the assessment of 26% of all biopsies, illustrating the potential of precision diagnostics to impact practice. Microarray analysis of 300 kidney transplant biopsies (non-TCMR, TCMR) and 6 nephrectomies.
2013-09-15 | E-GEOD-48581 | biostudies-arrayexpress
Project description:Histologic diagnosis of T cell-mediated rejection in kidney transplant biopsies has limited reproducibility because it is based on non-specific lesions using arbitrary rules that are subject to differing interpretations. We used microarray results from 403 indication biopsies previously given histologic diagnoses to develop a molecular classifier that assigned a molecular T cell-mediated rejection score to each biopsy. Independent assessment of the biopsies by multiple pathologists confirmed considerable disagreement on the presence of TCMR features: 79-88% accuracy and 35-69% sensitivity. The agreement of the molecular T cell-mediated rejection score with the histology diagnosis was similar to agreement among individual pathologists: accuracy 89%, sensitivity 51%. However, the score also predicted the consensus among pathologists, being highest when all agreed. Many discrepancies between the scores and the histologic diagnoses were in situations where histology is unreliable e.g. scarred biopsies. The score correlated with histologic lesions and gene sets associated with T cell-mediated rejection. The transcripts most often selected by the classifier were expressed in effector T cells, dendritic cells, or macrophages or inducible by interferon-gamma. Thus the T cell-mediated rejection score offers an objective assessment of kidney transplant biopsies, predicting the consensus opinion among multiple pathologists, and offering insights into underlying disease mechanisms. Antibody-mediated rejection is a major cause of kidney transplant failure, but the current diagnostic system misses most cases due to dependency on subjective non-standardized tests. We hypothesized that molecular features could provide a test to address this problem. We classified 403 biopsies by a reference standard based on microcirculation lesions and donor-specific HLA antibody, and used microarray analysis to develop a classifier that assigned each biopsy a score reflecting the probability of antibody-mediated rejection. The scores correlated with donor-specific antibody and histologic lesions: 42/45 biopsies with antibody-mediated rejection scores >0.5 had both donor-specific antibody and microcirculation lesions. Intermediate scores (0.2-0.5) were more ambiguous, but became more specific combined with donor-specific antibody. Compared to diagnoses based on histology-plus-donor-specific antibody, the scores had sensitivity 0.67; specificity 0.90. Donor-specific antibody improved the specificity to 0.97. The score correlated not only with diagnoses of individual pathologists but with the consensus among multiple pathologists. The classifier used transcripts expressed in endothelial cells (e.g. CDH13, DARC, ROBO4) and NK cells (e.g. CX3CR1, FGFBP2), as well as IFNG-inducible transcripts e.g. CXCL11. Thus the molecular phenotype of antibody-mediated rejection provides not only an objective test that predicts microcirculation lesions and donor-specific HLA antibody, but also offers mechanistic insights.
2013-02-13 | GSE36059 | GEO
Project description:Molecular diagnosis of rejection is emerging in kidney, heart, and lung transplant biopsies and could offer insights for liver transplant biopsies. Groups differed in median time post-transplant e.g. R3injury 99 days vs. R4late 3117 days. R2TCMR biopsies expressed typical TCMR-related transcripts e.g. intense IFNG-induced effects. R3injury displayed increased expression of parenchymal injury transcripts (e.g. hypoxia-inducible factor EGLN1). R4late biopsies showed immunoglobulin transcripts and injury-related transcripts. R2TCMR correlated with histologic rejection although with many discrepancies, and R4late with fibrosis. R2TCMR, R3injury, and R4late correlated with liver function abnormalities. Supervised classifiers trained on histologic rejection showed less agreement with histology than unsupervised R2TCMR scores. No confirmed cases of clinical ABMR were present in the population, and strategies that previously revealed antibody-mediated rejection (ABMR) in kidney and heart transplants failed to reveal a liver ABMR phenotype. In conclusion, molecular analysis of liver transplant biopsies detects rejection, has the potential to resolve ambiguities, and could assist with immunosuppressive management.
2020-05-06 | GSE145780 | GEO
Project description:Histologic diagnosis of T cell-mediated rejection in kidney transplant biopsies has limited reproducibility because it is based on non-specific lesions using arbitrary rules that are subject to differing interpretations. We used microarray results from 403 indication biopsies previously given histologic diagnoses to develop a molecular classifier that assigned a molecular T cell-mediated rejection score to each biopsy. Independent assessment of the biopsies by multiple pathologists confirmed considerable disagreement on the presence of TCMR features: 79-88% accuracy and 35-69% sensitivity. The agreement of the molecular T cell-mediated rejection score with the histology diagnosis was similar to agreement among individual pathologists: accuracy 89%, sensitivity 51%. However, the score also predicted the consensus among pathologists, being highest when all agreed. Many discrepancies between the scores and the histologic diagnoses were in situations where histology is unreliable e.g. scarred biopsies. The score correlated with histologic lesions and gene sets associated with T cell-mediated rejection. The transcripts most often selected by the classifier were expressed in effector T cells, dendritic cells, or macrophages or inducible by interferon-gamma. Thus the T cell-mediated rejection score offers an objective assessment of kidney transplant biopsies, predicting the consensus opinion among multiple pathologists, and offering insights into underlying disease mechanisms. Antibody-mediated rejection is a major cause of kidney transplant failure, but the current diagnostic system misses most cases due to dependency on subjective non-standardized tests. We hypothesized that molecular features could provide a test to address this problem. We classified 403 biopsies by a reference standard based on microcirculation lesions and donor-specific HLA antibody, and used microarray analysis to develop a classifier that assigned each biopsy a score reflecting the probability of antibody-mediated rejection. The scores correlated with donor-specific antibody and histologic lesions: 42/45 biopsies with antibody-mediated rejection scores >0.5 had both donor-specific antibody and microcirculation lesions. Intermediate scores (0.2-0.5) were more ambiguous, but became more specific combined with donor-specific antibody. Compared to diagnoses based on histology-plus-donor-specific antibody, the scores had sensitivity 0.67; specificity 0.90. Donor-specific antibody improved the specificity to 0.97. The score correlated not only with diagnoses of individual pathologists but with the consensus among multiple pathologists. The classifier used transcripts expressed in endothelial cells (e.g. CDH13, DARC, ROBO4) and NK cells (e.g. CX3CR1, FGFBP2), as well as IFNG-inducible transcripts e.g. CXCL11. Thus the molecular phenotype of antibody-mediated rejection provides not only an objective test that predicts microcirculation lesions and donor-specific HLA antibody, but also offers mechanistic insights. All consenting renal transplant patients undergoing biopsies for cause as standard of care. 403 samples and 8 controls (nephrectomies). This dataset is part of the TransQST collection.
2013-02-13 | E-GEOD-36059 | biostudies-arrayexpress
Project description:Acute lung rejection is a risk factor for chronic rejection, jeopardizing the long-term survival of lung transplant recipients. At present, acute rejection is diagnosed by transbronchial lung biopsies, which are invasive, expensive, and subject to significant sampling error. In this study, we sought to identify groups of genes whose collective expression in BAL cells best classifies acute rejection versus no-rejection. BAL samples were analyzed from 32 unique subjects whose concurrent histology showed acute rejection (n=14) or no rejection (n=18). Global BAL cell gene expression was measured using Affymetrix U133A microarrays. The nearest shrunken centroid method with 10-fold cross validation was used to define the classification model. 250 runs of the algorithm were performed to determine the range of misclassification error and the most influential genes in determining classifiers. The estimated overall misclassification rate was below 20%. Seven transcripts were present in every classifier and 52 transcripts were present in at least 70% of classifiers; these transcripts were notable for involvement with T-cell function, cytotoxic CD8 activity, and granulocyte degranulation. The proportions of both lymphocytes and neutrophils in BAL samples increased with increasing probability of acute rejection; this trend was more pronounced with neutrophils. We conclude that there is a prominent acute rejection-associated signature in BAL cells characterized by increased T-cell, CD8+ cytotoxic cell, and neutrophil gene expression; this is consistent with established mechanistic concepts of the acute rejection response. Keywords: Disease State Analysis
2008-01-01 | GSE6095 | GEO
Project description:Previous studies of rejection-associated transcript expression in heart transplant biopsies identified not only rejection but a group of early biopsies with injury but no rejection. The present analysis used an expanded population of biopsies to explore parenchymal injury in all biopsies, with or without rejection, and its relationship to function, and outcome. Archetypal analysis defined five injury clusters: no-injury (N=376); mild (N=526); moderate (N=110); severe (N=87); and late (N=221). The late group, 62% of which had no rejection, had molecular characteristics associated with atrophy-fibrosis, depressed LVEF, and increased graft loss independent of rejection status. In random forest analysis, low LVEF was more strongly associated with injury scores than with rejection scores. Three-year graft failure was best predicted using a combination of injury and rejection scores. In heart transplant biopsies, injury-related molecular scores correlate with dysfunction and risk of failure and identify an important new group of late heart transplants, many with no rejection, that have impaired function and a high risk of graft loss. (ClinicalTrials.gov #NCT02670408).
2021-12-28 | GSE150059 | GEO
Project description:Background: Biopsy-based diagnosis is essential for maintaining renal allograft longevity by ensuring prompt treatment for graft complications. Although histologic assessment remains the gold standard, it carries significant limitations such as subjective interpretation, suboptimal reproducibility, and imprecise quantitation of disease burden. It is hoped that molecular diagnostics could enhance the efficiency, accuracy, and reproducibility of traditional histologic methods. Methods: Quantitative label-free mass spectrometry analysis was performed on a set of formalin-fixed, paraffin-embedded (FFPE) biopsies from renal transplant patients, comprising five biopsies with the diagnosis of T-cell-mediated rejection (TCMR), five biopsies for polyomavirus BK nephropathy (BKPyVN), and normal kidney control tissue (STA). Using the differential protein expression result as a classifier, three different machine learning algorithms were tested to build a molecular diagnostic model for TCMR. Results: The label-free proteomics method yielded 800-1350 proteins that could be quantified with high confidence per sample by single-shot measurements. Among these candidate proteins, 329 and 467 proteins were defined as differentially expressed proteins (DEPs) for TCMR in comparison with STA and BKPyVN, respectively. Comparing the FFPE quantitative proteomics data set obtained in this study using label-free method with a data set we previously reported using isobaric labeling technology, a classifier pool comprised of features from DEPs commonly quantified in both data sets, was generated for TCMR prediction. Leave-one-out cross-validation result demonstrated that the random forest (RF)-based model achieved the best predictive power. In a follow-up blind test using an independent sample set, the RF-based model yields 80% accuracy for TCMR and 100% for STA. When applying the established RF-based model to two public transcriptome datasets, 78.1%-82.9% sensitivity and 58.7%-64.4% specificity was achieved respectively. Conclusions: This proof-of-principle study demonstrates the clinical feasibility of proteomics profiling for FFPE biopsies using an accurate, efficient, and cost-effective platform integrated of quantitative label-free mass spectrometry analysis with a machine learning-derived diagnostic model. It costs less than 10 dollars per test.
2023-02-01 | PXD038601 | Pride
Project description:Our goals were to determine whether (i) gene expression patterns in biopsies grouped by acute rejection grade (AR) would be consistent; (ii) a characteristic gene expression profile would be associated with ISHLT Grade 0, 1A & 1B (equivalent to 1R on recently revised criteria) and ISHLT grade 3A & 3B (equivalent to 2R & 3R on recently revised criteria); (iii) gene expression patterns emerging from the analysis would provide insights into mechanisms of AR. The samples used for gene expression profiling were endomyocardial biopsies (EMB) with different acute rejection gradings. The EMB (n=2726) were obtained from the right site of the interventricular septum of heart transplant recipients (n=2423) and graded according to the guidelines of the International Society for Heart and Lung Transplantation (ISHLT, grade 0, n=9; grade1A, n=5; 1B, n=5; 3A, n=4; 3B, n=43). Selection criteria for inclusion of patients in this analysis required the availability of appropriately stored EMB samples for RNA extraction; absence of any infection that required treatment with an antimicrobial drug at anytime during the posttransplant course of the patient; absence of prior AR rejection of any grade; absence of hemodynamic compromise at the time of EMB; use of standard immunosuppressive regimen; and the absence of HLA antibodies prior to transplant.
2008-10-18 | GSE9377 | GEO
Project description:We hypothesized that T cell-mediated immune mechanisms play a role in two conditions; 1: donor-specific antibody (DSA) negative transplant glomerulopathy (TGP) and 2: interstitial fibrosis and tubular atrophy (IFTA) with inflammation (i>0). We investigated gene expression profiles of those biopsies compared to biopsies with antibody-mediated rejection(ABMR) and to biopsies with non-specific IFTA and no inflammation. DSA negative TGP and IFTA with inflammation biopsies have a unique molecular signature distinct to that seen in biopsies with ABMR and IFTA without inflammation with significant expression of cytotoxic and regulatory T cells.
2017-01-17 | GSE93658 | GEO
Project description:Histological features of acute rejection can be detected in surveillance biopsies despite stable graft function and can negatively impact graft outcomes. However, routine surveillance biopsies for detection of subclinical rejection are not generally performed due to potential risks and costs associated with repeated biopsies. Noninvasive biomarkers are required to facilitate early detection of acute rejection and borderline changes. We examined the impact of histological abnormalities at 3-month in surveillance biopsies on graft outcomes in kidney transplant recipients from the prospective Genomics of Chronic Allograft Rejection (GoCAR) study. We then performed RNA sequencing on whole blood collected at the time of biopsy in 88 patients (22 vs. 66) to identify transcripts associated with histological abnormalities. Subjects with subclinical ACR or borderline ACR at 3 month (ACR-3) had higher risk of subsequent clinical acute rejection at 12 and 24 month (P < 0.05), more rapid functional decline (P < 0.05) and a decreased graft survival in adjusted cox analysis (P < 0.01) than patients with no abnormalities on 3-month biopsy. We then identified a 17-gene signature in peripheral blood that accurately diagnosed ACR-3.
2019-09-11 | GSE120396 | GEO