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Exploring the single-cell immune landscape of kidney allograft inflammation using imaging mass cytometry.
Alexander, Mariam P; Zaidi, Mark; Larson, Nicholas; Mullan, Aidan; Pavelko, Kevin D; Stegall, Mark D; Bentall, Andrew; Wouters, Bradly G; McKee, Trevor; Taner, Timucin.
Afiliação
  • Alexander MP; Department of Pathology and Laboratory Medicine, Mayo Clinic, Rochester, Minnesota, USA. Electronic address: alexander.mariam@mayo.edu.
  • Zaidi M; Department of Medical Biophysics, University of Toronto, Canada.
  • Larson N; Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Mullan A; Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Pavelko KD; Immune Monitoring Core Laboratory, Mayo Clinic, Rochester, Minnesota, USA.
  • Stegall MD; Departments of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA.
  • Bentall A; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA.
  • Wouters BG; Department of Medical Biophysics, University of Toronto, Canada; Princess Margaret Cancer Center, University Health Network, University of Toronto, Toronto, Ontario, Canada.
  • McKee T; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada; Pathomics Inc., Toronto, Ontario, Canada.
  • Taner T; Departments of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA.
Am J Transplant ; 24(4): 549-563, 2024 Apr.
Article em En | MEDLINE | ID: mdl-37979921
ABSTRACT
Kidney allograft inflammation, mostly attributed to rejection and infection, is an important cause of graft injury and loss. Standard histopathological assessment of allograft inflammation provides limited insights into biological processes and the immune landscape. Here, using imaging mass cytometry with a panel of 28 validated biomarkers, we explored the single-cell landscape of kidney allograft inflammation in 32 kidney transplant biopsies and 247 high-dimensional histopathology images of various phenotypes of allograft inflammation (antibody-mediated rejection, T cell-mediated rejection, BK nephropathy, and chronic pyelonephritis). Using novel analytical tools, for cell segmentation, we segmented over 900 000 cells and developed a tissue-based classifier using over 3000 manually annotated kidney microstructures (glomeruli, tubules, interstitium, and arteries). Using PhenoGraph, we identified 11 immune and 9 nonimmune clusters and found a high prevalence of memory T cell and macrophage-enriched immune populations across phenotypes. Additionally, we trained a machine learning classifier to identify spatial biomarkers that could discriminate between the different allograft inflammatory phenotypes. Further validation of imaging mass cytometry in larger cohorts and with more biomarkers will likely help interrogate kidney allograft inflammation in more depth than has been possible to date.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Inflamação / Rim Limite: Humans Idioma: En Revista: Am J Transplant Assunto da revista: TRANSPLANTE Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Inflamação / Rim Limite: Humans Idioma: En Revista: Am J Transplant Assunto da revista: TRANSPLANTE Ano de publicação: 2024 Tipo de documento: Article