Noninvasive and predictive biomarkers of organ transplant rejection

Georgia Institute Of Technology, Atlanta GA

Investigators

Linked publications, trials & patents

Abstract

Project Summary/Abstract Organ transplantation remains the single most effective treatment for end-stage organ failure, and in 2014, approximately 30,000 organs were transplanted despite the well over 123,000 men, women and children needing the lifesaving operation. Consequently, detecting the onset of organ rejection is an important part of clinical management, and is critical for the survival and health of the recipient. The invasive biopsy is the gold standard for diagnosing graft injury, yet it lacks sensitivity and specificity, and detects pathological changes at advanced and irreversible stages of allograft damage. Thus there remains a need for noninvasive and predictive biomarkers that indicate damage when changes are occurring at the molecular level before changes in tissue morphology. This proposal aims to develop activity-based probes that are engineered to be administered intravenously and then amplify diagnostic signals into urine at the earliest stages of rejection. Proteases play central roles in immunity and their activity mediate organ rejection; these include granzymes secreted by anti-graft CD8 T cells, caspases activated by cells undergoing apoptosis, complement activation by antibody-mediated rejection, and matrix metalloproteinases upregulated during fibrosis. We will develop activity-base probes called synthetic biomarkers that are made of a library of mass-barcoded peptide substrates conjugated to the surface of a nanoparticle core. After infusion, synthetic biomarkers carry out a precise chain of events to detect organ transplant rejection: they accumulate at sites of disease, present their surface-conjugated peptides for local proteases to cleave, and release cleavage fragments into urine for multiplexed detection by mass spectrometry. Synthetic biomarkers may dramatically increase diagnostic sensitivity and specificity; the former, by amplifying detection signals via protease turnover combined with urinary enrichment, and the latter, by mass-barcoded multiplexed analysis to identify combinations of peptides that detect disease with increased specificity. We will used activity-based synthetic biomarkers to identify predictive biomarkers in animal models of acute cellular rejection and costimulation independent acute rejection. If successful, this platform technology may have additional applications across a broad landscape in biomedicine including monitoring the efficacy of immunotherapies, bacterial infections and point-of-care diagnostics.