Molecular T-cell mediated rejection in transbronchial and mucosal lung transplant biopsies
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PROVIDER: PRJNA631267 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Diagnosing lung transplant rejection currently depends on histologic assessment of transbronchial biopsies (TBB) with limited reproducibility and considerable risk of complications. Mucosal biopsies are safer but not histologically interpretable. Microarray-based diagnostic systems for TBBs and other transplants suggest such systems could assess mucosal biopsies as well.
2019-11-19 | GSE125004 | GEO
Project description:We previously developed molecular assessment systems for lung transplant transbronchial biopsies (TBBs) with high surfactant and bronchial mucosal biopsies (3BMBs). Unsupervised machine learning identified T cell-mediated rejection (TCMR) based on expression of validated rejection-associated transcripts (RATs). The relationship to patient outcomes is not known. We aimed to establish whether molecular TCMR in TBBs and 3BMBs has implications for future graft loss. Molecular TCMR scores assigned in all TBBs or high surfactant TBBs agreed closely, indicating that variation in alveolar content in TBBs does not prevent detection of TCMR. Molecular assessments of 3BMB-3BMB pairs showed less variation than TBB-TBB pairs. TBB TCMR scores correlated with those in 3BMB. In both formats, molecular TCMR was associated with increased risk of graft loss whereas the presence of histologic rejection or donor-specific antibodies was not. Molecular TCMR can be detected in TBBs or 3BMBs and is associated with future risk of graft loss. TCMR emerges as a n important contributor to risk of failure. ClinicalTrials.gov NCT02812290.
2020-10-07 | GSE150156 | GEO
Project description:Molecular phenotyping of rejection in mucosal biopsies from lung transplant recipients
| PRJNA514864 | ENA
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: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:Improved understanding of lung transplant disease states is essential because failure rates are high, often due to chronic lung allograft dysfunction. However, histologic assessment of lung transplant transbronchial biopsies (TBBs) is difficult and often uninterpretable even with 10 pieces. All 242 single-piece TBBs produced reliable transcript measurements. Paired TBB pieces available from 12 patients showed significant similarity but also showed some sampling variance. Alveolar content, as estimated by surfactant transcript expression, was a source of sampling variance. To offset sampling variation, for analysis we selected 152 single-piece TBBs with high surfactant transcripts. Unsupervised archetypal analysis identified four idealized phenotypes (archetypes) and scored biopsies for their similarity to each: normal, T cell-mediated rejection (TCMR; T cell transcripts), antibody-mediated rejection (ABMR)-like (endothelial transcripts), and injury (macrophage transcripts). Molecular TCMR correlated with histologic TCMR. The relationship of molecular scores to histologic ABMR could not be assessed because of the paucity of ABMR in this population. Molecular assessment of single-piece TBBs can be used to classify lung transplant biopsies and correlated with rejection histology. Two or three pieces for each TBB will probably be needed to offset sampling variance.
2019-08-16 | GSE125478 | 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.
2013-02-13 | GSE36059 | GEO
Project description:Molecular phenotyping of biopsies affords opportunities for increased precision and improved disease classification to address the limitations of conventional histologic diagnostic systems. We applied archetypal analysis, an unsupervised method similar to cluster analysis, to microarray data from 1208 prospectively collected kidney transplant biopsies from 13 centers. Seven machine learning-generated cross-validated classifier scores per biopsy were used as input for the archetypal analysis. Six archetypes representing extreme phenotypes were generated: no rejection; T cell-mediated rejection (TCMR); three phenotypes associated with antibody-mediated rejection (ABMR) - early-stage, fully-developed, and late-stage; and mixed rejection (TCMR plus early-stage ABMR). Each biopsy was assigned six scores, one for each archetype, that together represent a probabilistic assessment of that biopsy based on its rejection-related molecular properties. Viewed as clusters, the archetypes were similar to existing histologic Banff categories, but there was 32% disagreement, much of it probably reflecting the “noise” in the current histologic assessment system. Graft survival was worst for fully-developed and late-stage ABMR and was better predicted by molecular archetype scores than histologic diagnoses. The results provide a system for precision molecular assessment of biopsies and a new standard for recalibrating conventional diagnostic systems. (ClinicalTrials.gov NTC1299168) We applied archetypal analysis, an unsupervised method similar to cluster analysis, to microarray data from 1208 prospectively collected kidney transplant biopsies from 13 centers. This dataset is part of the TransQST collection.
2017-07-10 | E-GEOD-98320 | biostudies-arrayexpress
Project description:Molecular Assessment of Rejection and Injury in Lung Transplant Biopsies
| PRJNA516459 | ENA