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Smith RN, Rosales IA, Tomaszewski KT, Mahowald GT, Araujo-Medina M, Acheampong E, Bruce A, Rios A, Otsuka T, Tsuji T, Hotta K, Colvin R. Utility of Banff Human Organ Transplant Gene Panel in Human Kidney Transplant Biopsies. Transplantation 2023; 107:1188-1199. [PMID: 36525551 PMCID: PMC10132999 DOI: 10.1097/tp.0000000000004389] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Microarray transcript analysis of human renal transplantation biopsies has successfully identified the many patterns of graft rejection. To evaluate an alternative, this report tests whether gene expression from the Banff Human Organ Transplant (B-HOT) probe set panel, derived from validated microarrays, can identify the relevant allograft diagnoses directly from archival human renal transplant formalin-fixed paraffin-embedded biopsies. To test this hypothesis, principal components (PCs) of gene expressions were used to identify allograft diagnoses, to classify diagnoses, and to determine whether the PC data were rich enough to identify diagnostic subtypes by clustering, which are all needed if the B-HOT panel can substitute for microarrays. METHODS RNA was isolated from routine, archival formalin-fixed paraffin-embedded tissue renal biopsy cores with both rejection and nonrejection diagnoses. The B-HOT panel expression of 770 genes was analyzed by PCs, which were then tested to determine their ability to identify diagnoses. RESULTS PCs of microarray gene sets identified the Banff categories of renal allograft diagnoses, modeled well the aggregate diagnoses, showing a similar correspondence with the pathologic diagnoses as microarrays. Clustering of the PCs identified diagnostic subtypes including non-chronic antibody-mediated rejection with high endothelial expression. PCs of cell types and pathways identified new mechanistic patterns including differential expression of B and plasma cells. CONCLUSIONS Using PCs of gene expression from the B-Hot panel confirms the utility of the B-HOT panel to identify allograft diagnoses and is similar to microarrays. The B-HOT panel will accelerate and expand transcript analysis and will be useful for longitudinal and outcome studies.
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Affiliation(s)
- Rex N Smith
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Transplantation Sciences, Massachusetts General Hospital, Boston, MA
| | - Ivy A Rosales
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Transplantation Sciences, Massachusetts General Hospital, Boston, MA
| | - Kristen T Tomaszewski
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Transplantation Sciences, Massachusetts General Hospital, Boston, MA
| | - Grace T Mahowald
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Milagros Araujo-Medina
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Ellen Acheampong
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Amy Bruce
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Andrea Rios
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Takuya Otsuka
- Department of Surgical Pathology, Hokkaido University Hospital, Sapporo, Japan
| | - Takahiro Tsuji
- Department of Pathology, Sapporo City General Hospital, Sapporo, Japan
| | - Kiyohiko Hotta
- Department of Urology, Hokkaido University Hospital, Sapporo, Japan
| | - Robert Colvin
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Transplantation Sciences, Massachusetts General Hospital, Boston, MA
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Smith RN. In-silico performance, validation, and modeling of the Nanostring Banff Human Organ transplant gene panel using archival data from human kidney transplants. BMC Med Genomics 2021; 14:86. [PMID: 33740956 PMCID: PMC7977303 DOI: 10.1186/s12920-021-00891-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 01/31/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND RNA gene expression of renal transplantation biopsies is commonly used to identify the immunological patterns of graft rejection. Mostly done with microarrays, seminal findings defined the patterns of gene sets associated with rejection and non-rejection kidney allograft diagnoses. To make gene expression more accessible, the Molecular Diagnostics Working Group of the Banff Foundation for Allograft Pathology and NanoString Technologies partnered to create the Banff Human Organ Transplant Panel (BHOT), a gene panel set of 770 genes as a surrogate for microarrays (~ 50,000 genes). The advantage of this platform is that gene expressions are quantifiable on formalin fixed and paraffin embedded archival tissue samples, making gene expression analyses more accessible. The purpose of this report is to test in silico the utility of the BHOT panel as a surrogate for microarrays on archival microarray data and test the performance of the modelled BHOT data. METHODS BHOT genes as a subset of genes from downloaded archival public microarray data on human renal allograft gene expression were analyzed and modelled by a variety of statistical methods. RESULTS Three methods of parsing genes verify that the BHOT panel readily identifies renal rejection and non-rejection diagnoses using in silico statistical analyses of seminal archival databases. Multiple modelling algorithms show a highly variable pattern of misclassifications per sample, either between differently constructed principal components or between modelling algorithms. The misclassifications are related to the gene expression heterogeneity within a given diagnosis because clustering the data into 9 groups modelled with fewer misclassifications. CONCLUSION This report supports using the Banff Human Organ Transplant Panel for gene expression of human renal allografts as a surrogate for microarrays on archival tissue. The data modelled satisfactorily with aggregate diagnoses although with limited per sample accuracy and, thereby, reflects and confirms the modelling complexity and the challenges of modelling gene expression as previously reported.
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Affiliation(s)
- R N Smith
- Department of Pathology, Massachusetts General Hospital, 501 Warren Bldg, 55 Fruit Street, Boston, MA, 02114, USA.
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Mengel M, Loupy A, Haas M, Roufosse C, Naesens M, Akalin E, Clahsen‐van Groningen MC, Dagobert J, Demetris AJ, Duong van Huyen J, Gueguen J, Issa F, Robin B, Rosales I, Von der Thüsen JH, Sanchez‐Fueyo A, Smith RN, Wood K, Adam B, Colvin RB. Banff 2019 Meeting Report: Molecular diagnostics in solid organ transplantation-Consensus for the Banff Human Organ Transplant (B-HOT) gene panel and open source multicenter validation. Am J Transplant 2020; 20:2305-2317. [PMID: 32428337 PMCID: PMC7496585 DOI: 10.1111/ajt.16059] [Citation(s) in RCA: 108] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/19/2020] [Accepted: 04/27/2020] [Indexed: 02/06/2023]
Abstract
This meeting report from the XV Banff conference describes the creation of a multiorgan transplant gene panel by the Banff Molecular Diagnostics Working Group (MDWG). This Banff Human Organ Transplant (B-HOT) panel is the culmination of previous work by the MDWG to identify a broadly useful gene panel based on whole transcriptome technology. A data-driven process distilled a gene list from peer-reviewed comprehensive microarray studies that discovered and validated their use in kidney, liver, heart, and lung transplant biopsies. These were supplemented by genes that define relevant cellular pathways and cell types plus 12 reference genes used for normalization. The 770 gene B-HOT panel includes the most pertinent genes related to rejection, tolerance, viral infections, and innate and adaptive immune responses. This commercially available panel uses the NanoString platform, which can quantitate transcripts from formalin-fixed paraffin-embedded samples. The B-HOT panel will facilitate multicenter collaborative clinical research using archival samples and permit the development of an open source large database of standardized analyses, thereby expediting clinical validation studies. The MDWG believes that a pathogenesis and pathway based molecular approach will be valuable for investigators and promote therapeutic decision-making and clinical trials.
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Affiliation(s)
- Michael Mengel
- Department of Laboratory Medicine and PathologyUniversity of AlbertaEdmontonCanada
| | - Alexandre Loupy
- Paris Translational Research Center for Organ TransplantationINSERM U970 and Necker HospitalUniversity of ParisParisFrance
| | - Mark Haas
- Department of Pathology and Laboratory MedicineCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Candice Roufosse
- Department of Immunology and InflammationImperial College London and North West London PathologyLondonUK
| | - Maarten Naesens
- Department of Microbiology, Immunology and TransplantationKU LeuvenLeuvenBelgium,Department of NephrologyUniversity Hospitals LeuvenLeuvenBelgium
| | - Enver Akalin
- Montefiore‐Einstein Center for TransplantationMontefiore Medical CenterBronxNew YorkUSA
| | | | - Jessy Dagobert
- Paris Translational Research Center for Organ TransplantationINSERM U970 and Necker HospitalUniversity of ParisParisFrance
| | - Anthony J. Demetris
- Department of PathologyUniversity of Pittsburgh Medical CenterMontefiore, PittsburghPennsylvaniaUSA
| | - Jean‐Paul Duong van Huyen
- Paris Translational Research Center for Organ TransplantationINSERM U970 and Necker HospitalUniversity of ParisParisFrance
| | - Juliette Gueguen
- Paris Translational Research Center for Organ TransplantationINSERM U970 and Necker HospitalUniversity of ParisParisFrance
| | - Fadi Issa
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Blaise Robin
- Paris Translational Research Center for Organ TransplantationINSERM U970 and Necker HospitalUniversity of ParisParisFrance
| | - Ivy Rosales
- Department of PathologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | | | | | - Rex N. Smith
- Department of PathologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Kathryn Wood
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Benjamin Adam
- Department of Laboratory Medicine and PathologyUniversity of AlbertaEdmontonCanada
| | - Robert B. Colvin
- Department of PathologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
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Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring. Transplantation 2020; 103:1306-1322. [PMID: 30768568 DOI: 10.1097/tp.0000000000002656] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Traditional histopathological allograft biopsy evaluation provides, within hours, diagnoses, prognostic information, and mechanistic insights into disease processes. However, proponents of an array of alternative monitoring platforms, broadly classified as "invasive" or "noninvasive" depending on whether allograft tissue is needed, question the value proposition of tissue histopathology. The authors explore the pros and cons of current analytical methods relative to the value of traditional and illustrate advancements of next-generation histopathological evaluation of tissue biopsies. We describe the continuing value of traditional histopathological tissue assessment and "next-generation pathology (NGP)," broadly defined as staining/labeling techniques coupled with digital imaging and automated image analysis. Noninvasive imaging and fluid (blood and urine) analyses promote low-risk, global organ assessment, and "molecular" data output, respectively; invasive alternatives promote objective, "mechanistic" insights by creating gene lists with variably increased/decreased expression compared with steady state/baseline. Proponents of alternative approaches contrast their preferred methods with traditional histopathology and: (1) fail to cite the main value of traditional and NGP-retention of spatial and inferred temporal context available for innumerable objective analyses and (2) belie an unfamiliarity with the impact of advances in imaging and software-guided analytics on emerging histopathology practices. Illustrative NGP examples demonstrate the value of multidimensional data that preserve tissue-based spatial and temporal contexts. We outline a path forward for clinical NGP implementation where "software-assisted sign-out" will enable pathologists to conduct objective analyses that can be incorporated into their final reports and improve patient care.
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Adam N, Coutance G, Viailly PJ, Drieux F, Ruminy P, Sater AA, Toquet C, Rouvier P, François A, Chenard MP, Epailly E, Guillemain R, Pattier S, Gay A, Varnous S, Taupin JL, Rabant M, Loupy A, Bruneval P, Duong Van Huyen JP. Reverse transcriptase multiplex ligation-dependent probe amplification in endomyocardial biopsies for the diagnosis of cardiac allograft rejection. J Heart Lung Transplant 2020; 39:115-124. [DOI: 10.1016/j.healun.2019.11.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2019] [Revised: 11/17/2019] [Accepted: 11/20/2019] [Indexed: 12/29/2022] Open
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Donadei C, Angeletti A, Cantarelli C, D'Agati VD, La Manna G, Fiaccadori E, Horwitz JK, Xiong H, Guglielmo C, Hartzell S, Madsen JC, Maggiore U, Heeger PS, Cravedi P. Erythropoietin inhibits SGK1-dependent TH17 induction and TH17-dependent kidney disease. JCI Insight 2019; 5:127428. [PMID: 31013255 DOI: 10.1172/jci.insight.127428] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
IL-17-producing CD4+ cells (TH17) are pathogenically linked to autoimmunity including to autoimmune kidney disease. Erythropoietin's (EPO) newly recognized immunoregulatory functions and its predominant intra-renal source suggested that EPO physiologically regulates TH17 differentiation, thereby serving as a barrier to the development of autoimmune kidney disease. Using in vitro studies of human and murine cells and in vivo models, we show that EPO ligation of its receptor (EPO-R) on CD4+ T cells directly inhibits TH17 generation and promotes trans-differentiation of TH17 into IL-17-FOXP3+CD4+ T cells. Mechanistically, EPO/EPO-R ligation abrogates upregulation of SGK1 gene expression and blocks p38 activity to prevent SGK1 phosphorylation, thereby inhibiting RORC-mediated transcription of IL-17 and IL-23 receptor genes. In a murine model of TH17-dependent aristolochic acid (ArA)-induced, interstitial kidney disease associated with reduced renal EPO production, we demonstrate that transgenic EPO overexpression or recombinant EPO (rEPO) administration limits TH17 formation and clinical/histological disease expression. EPO/EPO-R ligations on CD4+ T cells abrogate, while absence of T cell-expressed EPO-R augments, TH17 induction and clinical/histological expression of pristane-induced glomerulonephritis (associated with decreased intrarenal EPO). rEPO prevents spontaneous glomerulonephritis and TH17 generation in MRL-lpr mice. Together, our findings indicate that EPO physiologically and therapeutically modulate TH17 cells to limit expression of TH17-associated autoimmune kidney disease.
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Affiliation(s)
- Chiara Donadei
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Nephrology Dialysis and Renal Transplantation Unit, S. Orsola University Hospital, Bologna, Italy
| | - Andrea Angeletti
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Nephrology Dialysis and Renal Transplantation Unit, S. Orsola University Hospital, Bologna, Italy
| | - Chiara Cantarelli
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Dipartimento di Medicina e Chirurgia (Università di Parma), UO Nefrologia (Azienda Ospedaliera-Universitaria Parma), Parma, Italy
| | - Vivette D D'Agati
- Department of Pathology, College of Physicians and Surgeons of Columbia University, New York, New York, USA
| | - Gaetano La Manna
- Nephrology Dialysis and Renal Transplantation Unit, S. Orsola University Hospital, Bologna, Italy
| | - Enrico Fiaccadori
- Dipartimento di Medicina e Chirurgia (Università di Parma), UO Nefrologia (Azienda Ospedaliera-Universitaria Parma), Parma, Italy
| | - Julian K Horwitz
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Huabao Xiong
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Chiara Guglielmo
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Susan Hartzell
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Joren C Madsen
- Center for Transplantation Sciences and Division of Cardiac Surgery, Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Umberto Maggiore
- Dipartimento di Medicina e Chirurgia (Università di Parma), UO Nefrologia (Azienda Ospedaliera-Universitaria Parma), Parma, Italy
| | - Peter S Heeger
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Paolo Cravedi
- Department of Medicine, Translational Transplant Research Center, Precision Institute of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Immunomics of Renal Allograft Acute T Cell-Mediated Rejection Biopsies of Tacrolimus- and Belatacept-Treated Patients. Transplant Direct 2018; 5:e418. [PMID: 30656216 PMCID: PMC6324913 DOI: 10.1097/txd.0000000000000857] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 11/02/2018] [Accepted: 11/10/2018] [Indexed: 12/14/2022] Open
Abstract
Supplemental digital content is available in the text. Background Belatacept-based therapy in kidney transplant recipient has been shown to increase long-term renal allograft and patient survival compared with calcineurin inhibitor–based therapy, however, with an increased risk of acute T cell-mediated rejection (aTCMR). An improved understanding of costimulation blockade-resistant rejections could lead to a more personalized approach to belatacept therapy. Here, immunomic profiles of aTCMR biopsies of patients treated with either tacrolimus or belatacept were compared. Methods Formalin-fixed paraffin-embedded renal transplant biopsies were used for immunohistochemistry and gene expression analysis using the innovative NanoString technique. To validate NanoString, transcriptomic profiles of patients with and without biopsy-proven aTCMR were compared. Biopsies from 31 patients were studied: 14 tacrolimus-treated patients with aTCMR, 11 belatacept-treated patients with aTCMR, and 6 controls without rejection. Results A distinct pattern was seen in biopsies with aTCMR compared to negative controls: 78 genes had a higher expression in the aTCMR group (false discovery rate P value <.05 to 1.42e–05). The most significant were T cell-associated genes (CD3, CD8, and CD4; P < 1.98e-04), γ-interferon-inducible genes (CCL5, CXCL9, CXCL11, CXCL10, TBX21; P < 1.33e-04) plus effector genes (GNLY, GZMB, ITGAX; P < 2.82e-03). Immunophenotypical analysis of the classic immune markers of the innate and adaptive immune system was comparable between patients treated with either tacrolimus or belatacept. In addition, the transcriptome of both groups was not significantly different. Conclusions In this small pilot study, no difference was found in immunomics of aTCMR biopsies of tacrolimus- and belatacept-treated patients. This suggests that clinically diagnosed aTCMR reflects a final common pathway of allorecognition which is unaffected by the type of immunosuppressive therapy.
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