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de Nattes T, Beadle J, Roufosse C. Biopsy-based transcriptomics in the diagnosis of kidney transplant rejection. Curr Opin Nephrol Hypertens 2024; 33:273-282. [PMID: 38411022 PMCID: PMC10990030 DOI: 10.1097/mnh.0000000000000974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
PURPOSE OF REVIEW The last year has seen considerable progress in translational research exploring the clinical utility of biopsy-based transcriptomics of kidney transplant biopsies to enhance the diagnosis of rejection. This review will summarize recent findings with a focus on different platforms, potential clinical applications, and barriers to clinical adoption. RECENT FINDINGS Recent literature has focussed on using biopsy-based transcriptomics to improve diagnosis of rejection, in particular antibody-mediated rejection. Different techniques of gene expression analysis (reverse transcriptase quantitative PCR, microarrays, probe-based techniques) have been used either on separate samples with ideally preserved RNA, or on left over tissue from routine biopsy processing. Despite remarkable consistency in overall patterns of gene expression, there is no consensus on acceptable indications, or whether biopsy-based transcriptomics adds significant value at reasonable cost to current diagnostic practice. SUMMARY Access to biopsy-based transcriptomics will widen as regulatory approvals for platforms and gene expression models develop. Clinicians need more evidence and guidance to inform decisions on how to use precious biopsy samples for biopsy-based transcriptomics, and how to integrate results with standard histology-based diagnosis.
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Affiliation(s)
- Tristan de Nattes
- Univ Rouen Normandie, INSERM U1234, CHU Rouen, Department of Nephrology, Rouen, France
| | - Jack Beadle
- Centre for Inflammatory Diseases, Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Candice Roufosse
- Centre for Inflammatory Diseases, Department of Immunology and Inflammation, Imperial College London, London, UK
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de Nattes T, Beadle J, Toulza F, Candon E, Ruminy P, François A, Bertrand D, Guerrot D, Drieux F, Roufosse C, Candon S. A Simple Molecular Tool for the Assessment of Kidney Transplant Biopsies. Clin J Am Soc Nephrol 2023; 18:499-509. [PMID: 36723289 PMCID: PMC10103338 DOI: 10.2215/cjn.0000000000000100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/17/2023] [Indexed: 02/02/2023]
Abstract
BACKGROUND The Banff Classification for Allograft Pathology recommendations for the diagnosis of kidney transplant rejection includes molecular assessment of the transplant biopsy. However, implementation of molecular tools in clinical practice is still limited, partly due to the required expertise and financial investment. The reverse transcriptase multiplex ligation-dependent probe amplification (RT-MLPA) assay is a simple, rapid, and inexpensive assay that permits simultaneous evaluation of a restricted gene panel using paraffin-embedded tissue blocks. The aim of this study was to develop and validate a RT-MLPA assay for diagnosis and classification of rejection. METHODS A retrospective cohort of 220 kidney transplant biopsies from two centers, which included 52 antibody-mediated rejection, 51 T-cell-mediated rejection, and 117 no-rejection controls, was assessed. A 17-gene panel was identified on the basis of relevant pathophysiological pathways. A support vector machine classifier was developed. A subset of 109 biopsies was also assessed using the Nanostring Banff Human Organ Transplant panel to compare the two assays. RESULTS The support vector machine classifier train and test accuracy scores were 0.84 and 0.83, respectively. In the test cohort, the F1 score for antibody-mediated rejection, T-cell-mediated rejection, and control were 0.88, 0.86, and 0.69, respectively. Using receiver-operating characteristic curves, the area under the curve for class predictions was 0.96, 0.89, and 0.91, respectively, with a weighted average at 0.94. Classifiers' performances were highest for antibody-mediated rejection diagnosis with 94% correct predictions, compared with 88% correct predictions for control biopsies and 60% for T-cell-mediated rejection biopsies. Gene expression levels assessed by RT-MLPA and Nanostring were correlated: r = 0.68, P < 0.001. Equivalent gene expression profiles were obtained with both assays in 81% of the samples. CONCLUSIONS The 17-gene panel RT-MLPA assay, developed here for formalin-fixed paraffin-embedded kidney transplant biopsies, classified kidney transplant rejection with an overall accurate prediction ratio of 0.83. PODCAST This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_04_10_CJN10100822.mp3.
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Affiliation(s)
- Tristan de Nattes
- Nephrology – Kidney Transplant Unit, Rouen University Hospital, Rouen, France
- Univ Rouen Normandie, INSERM U1234, Rouen, France
- Department of Immunology and Inflammation, Centre for Inflammatory Diseases, Imperial College, London, United Kingdom
| | - Jack Beadle
- Department of Immunology and Inflammation, Centre for Inflammatory Diseases, Imperial College, London, United Kingdom
| | - Frederic Toulza
- Department of Immunology and Inflammation, Centre for Inflammatory Diseases, Imperial College, London, United Kingdom
| | - Edvin Candon
- Nephrology – Kidney Transplant Unit, Rouen University Hospital, Rouen, France
| | - Philippe Ruminy
- Univ Rouen Normandie, INSERM U1245, Centre Henri Becquerel, Rouen, France
| | - Arnaud François
- Pathology Department, Rouen University Hospital, Rouen, France
| | - Dominique Bertrand
- Nephrology – Kidney Transplant Unit, Rouen University Hospital, Rouen, France
| | - Dominique Guerrot
- Nephrology – Kidney Transplant Unit, Rouen University Hospital, Rouen, France
| | - Fanny Drieux
- Univ Rouen Normandie, INSERM U1245, Centre Henri Becquerel, Rouen, France
- Pathology Department, Rouen University Hospital, Rouen, France
| | - Candice Roufosse
- Department of Immunology and Inflammation, Centre for Inflammatory Diseases, Imperial College, London, United Kingdom
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Fixed but Feasible: New Opportunities for Molecular Diagnostics in Transplantation. Transplantation 2022; 107:1023-1024. [PMID: 36477569 DOI: 10.1097/tp.0000000000004390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Shi T, Roskin K, Baker BM, Woodle ES, Hildeman D. Advanced Genomics-Based Approaches for Defining Allograft Rejection With Single Cell Resolution. Front Immunol 2021; 12:750754. [PMID: 34721421 PMCID: PMC8551864 DOI: 10.3389/fimmu.2021.750754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 09/13/2021] [Indexed: 12/20/2022] Open
Abstract
Solid organ transplant recipients require long-term immunosuppression for prevention of rejection. Calcineurin inhibitor (CNI)-based immunosuppressive regimens have remained the primary means for immunosuppression for four decades now, yet little is known about their effects on graft resident and infiltrating immune cell populations. Similarly, the understanding of rejection biology under specific types of immunosuppression remains to be defined. Furthermore, development of innovative, rationally designed targeted therapeutics for mitigating or preventing rejection requires a fundamental understanding of the immunobiology that underlies the rejection process. The established use of microarray technologies in transplantation has provided great insight into gene transcripts associated with allograft rejection but does not characterize rejection on a single cell level. Therefore, the development of novel genomics tools, such as single cell sequencing techniques, combined with powerful bioinformatics approaches, has enabled characterization of immune processes at the single cell level. This can provide profound insights into the rejection process, including identification of resident and infiltrating cell transcriptomes, cell-cell interactions, and T cell receptor α/β repertoires. In this review, we discuss genomic analysis techniques, including microarray, bulk RNAseq (bulkSeq), single-cell RNAseq (scRNAseq), and spatial transcriptomic (ST) techniques, including considerations of their benefits and limitations. Further, other techniques, such as chromatin analysis via assay for transposase-accessible chromatin sequencing (ATACseq), bioinformatic regulatory network analyses, and protein-based approaches are also examined. Application of these tools will play a crucial role in redefining transplant rejection with single cell resolution and likely aid in the development of future immunomodulatory therapies in solid organ transplantation.
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Affiliation(s)
- Tiffany Shi
- Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.,Immunology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH, United States.,Medical Scientist Training Program, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Krishna Roskin
- Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.,Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Brian M Baker
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, United States
| | - E Steve Woodle
- Division of Transplantation, Department of Surgery, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - David Hildeman
- Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.,Immunology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH, United States
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Kung VL, Sandhu R, Haas M, Huang E. Chronic active T cell–mediated rejection is variably responsive to immunosuppressive therapy. Kidney Int 2021; 100:391-400. [DOI: 10.1016/j.kint.2021.03.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 02/24/2021] [Accepted: 03/09/2021] [Indexed: 02/07/2023]
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Toulza F, Dominy K, Willicombe M, Beadle J, Santos E, Cook HT, Szydlo RM, McLean A, Roufosse C. Diagnostic application of transcripts associated with antibody-mediated rejection in kidney transplant biopsies. Nephrol Dial Transplant 2021; 37:1576-1584. [PMID: 34320215 PMCID: PMC9317169 DOI: 10.1093/ndt/gfab231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Indexed: 11/22/2022] Open
Abstract
Background The diagnosis of antibody-mediated rejection (AMR) is reached using the Banff Classification for Allograft Pathology, which now includes gene expression analysis. In this study, we investigate the application of ‘increased expression of thoroughly validated gene transcripts/classifiers strongly associated with AMR’ as diagnostic criteria. Method We used quantitative real-time polymerase chain reaction for 10 genes associated with AMR in a retrospective cohort of 297 transplant biopsies, including biopsies that met the full diagnostic criteria for AMR, even without molecular data (AMR, n = 27), biopsies that showed features of AMR, but that would only meet criteria for AMR with increased transcripts [suspicious for AMR (AMRsusp), n = 49] and biopsies that would never meet criteria for AMR (No-AMR, n = 221). Results A 10-gene AMR score trained by a receiver-operating characteristic to identify AMR found 16 cases with a high score among the AMRsusp cases (AMRsusp-high) that had significantly worse graft survival than those with a low score (AMRsusp-low; n = 33). In both univariate and multivariate Cox regression analysis, the AMR 10-gene score was significantly associated with an increased hazard ratio (HR) for graft loss (GL) in the AMRsusp group (HR = 1.109, P = 0.004 and HR = 1.138, P = 0.012, respectively), but not in the whole cohort. Net reclassification index and integrated discrimination improvement analyses demonstrated improved risk classification and superior discrimination, respectively, for GL when considering the gene score in addition to histological and serological data, but only in the AMRsusp group, not the whole cohort. Conclusions This study provides evidence that a gene score strongly associated with AMR helps identify cases at higher risk of GL in biopsies that are suspicious for AMR but do not meet full criteria.
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Affiliation(s)
- Frederic Toulza
- Imperial College, Centre for Inflammatory Disease, Dept Immunology and Inflammation, London, United Kingdom
| | - Kathy Dominy
- Molecular Pathology Laboratory, North West London Pathology, London, United Kingdom
| | - Michelle Willicombe
- Imperial College, Centre for Inflammatory Disease, Dept Immunology and Inflammation, London, United Kingdom.,Imperial College Renal and Transplant Centre, Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Jack Beadle
- Imperial College, Centre for Inflammatory Disease, Dept Immunology and Inflammation, London, United Kingdom
| | - Eva Santos
- Histocompatibility and Immunogenetics, North West London Pathology, London, United Kingdom
| | - H Terence Cook
- Imperial College, Centre for Inflammatory Disease, Dept Immunology and Inflammation, London, United Kingdom
| | - Richard M Szydlo
- Imperial College, Medical Statistician, Dept Immunology and Inflammation, London, United Kingdom
| | - Adam McLean
- Imperial College Renal and Transplant Centre, Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Candice Roufosse
- Imperial College, Centre for Inflammatory Disease, Dept Immunology and Inflammation, London, United Kingdom
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