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Related Experiment Video

Updated: Mar 7, 2026

Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation
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Published on: September 6, 2017

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New developments in transplant proteomics.

Julie Ho1, Patricia Hirt-Minkowski, John A Wilkins

  • 1aManitoba Centre for Proteomics and Systems Biology, University of Manitoba and Health Sciences Centre bSection of Biomedical Proteomics cSection of Nephrology, Department of Internal Medicine dDepartment of Immunology, University of Manitoba, Winnipeg, Manitoba, Canada eTransplantation Immunology and Nephrology, University Hospital Basel, Basel, Switzerland.

Current Opinion in Nephrology and Hypertension
|February 22, 2017
PubMed
Summary
This summary is machine-generated.

Novel proteomics identified urine MMP7 and peptide signatures as biomarkers for renal allograft rejection. Further exploration of proteoforms in blood cells may improve early detection and treatment outcomes.

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Area of Science:

  • Proteomics
  • Biomarker Discovery
  • Transplant Immunology

Background:

  • Renal allograft rejection is a primary cause of graft loss despite current immunosuppression.
  • Early detection and treatment of rejection are crucial for improving transplant outcomes.

Purpose of the Study:

  • To review proteomics applications in renal allograft rejection.
  • To explore recent discovery-based studies and innovative biomarker development approaches.

Main Methods:

  • Proteomics techniques including LC-MS/MS, TRAQ, label-free MS, and SRM-MS were employed.
  • Analysis of urine and peripheral blood mononuclear cells (PBMCs).

Main Results:

  • Urine matrix metalloproteinase 7 (MMP7) identified as a biomarker for subclinical and clinical rejection.
  • A novel peptide signature differentiated stable allografts from rejection and BKV nephropathy.
  • Differential proteoform expression found in PBMCs between healthy transplants and rejection.

Conclusions:

  • Proteomics offers promising biomarker candidates for renal allograft rejection.
  • Integration of multi-omics data and functional proteomics (e.g., proteoforms) may enhance understanding and diagnostics.
  • External validation of identified biomarkers is essential.