title: Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates.
abstract: BACKGROUND
  Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy.
  
  
  RESULTS
  Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy.
  
  
  CONCLUSIONS
  Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize medicine to ultimately improve overall outcomes in highly sensitized kidney transplant candidates.
authors.affiliation: Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, United States of America.
authors.forename: Julie M
authors.initials: JM
authors.lastname: Yabu
authors.affiliation: CytoAnalytics, Denver, CO, United States of America.
authors.forename: Janet C
authors.initials: JC
authors.lastname: Siebert
authors.affiliation: Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Palo Alto, CA, United States of America.
authors.forename: Holden T
authors.initials: HT
authors.lastname: Maecker
mesh_terms: D051997:ADP-ribosyl Cyclase 1 / Q000378:metabolism; D000328:Adult; D000368:Aged; D001323:Autoantibodies / Q000032:analysis; D001402:B-Lymphocytes / Q000276:immunology; D000069286:Bortezomib / Q000627:therapeutic use; D015496:CD4-Positive T-Lymphocytes / Q000276:immunology* / Q000378:metabolism; D003888:Desensitization, Immunologic; D005260:Female; D006684:HLA-DR Antigens / Q000276:immunology*; D006650:Histocompatibility Testing; D006801:Humans; D016756:Immunoglobulins, Intravenous / Q000627:therapeutic use; D007676:Kidney Failure, Chronic / Q000378:metabolism / Q000473:pathology / Q000628:therapy*; D016030:Kidney Transplantation; D008137:Longitudinal Studies; D008297:Male; D008869:Microtubule-Associated Proteins / Q000235:genetics / Q000378:metabolism; D008875:Middle Aged; D011446:Prospective Studies; D000069283:Rituximab / Q000627:therapeutic use; D059467:Transcriptome
chemical_list: D001323:Autoantibodies; D006684:HLA-DR Antigens; D016756:Immunoglobulins, Intravenous; D008869:Microtubule-Associated Proteins; C583274:TNF receptor-associated factor 3 interacting protein 3, human; D000069283:Rituximab; D000069286:Bortezomib; D051997:ADP-ribosyl Cyclase 1