ArticlePloS one2016
Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 1-Overview of Knowledge Discovery Techniques in Artificial Intelligence.Frontiers in pharmacology · 2020Pooled it
- B cell repertoires in HLA-sensitized kidney transplant candidates undergoing desensitization therapy.Journal of translational medicine · 2017Trial
- Identification of metabolism-related key genes as potential biomarkers for pathogenesis of immune thrombocytopenia.Scientific reports · 2024Article
- Full spectrum flow cytometry and mass cytometry: A 32-marker panel comparison.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2022Article
- The promise of machine learning applications in solid organ transplantation.NPJ digital medicine · 2022Review
- Progress and applications of mass cytometry in sketching immune landscapes.Clinical and translational medicine · 2020Review
- Phenotypic and Transcriptomic Lymphocytes Changes in Allograft Recipients After Intravenous Immunoglobulin Therapy in Kidney Transplant Recipients.Frontiers in immunology · 2020Article
- Regulatory T cells in solid organ transplantation.Clinical & translational immunology · 2020Review
- Using the Immunophenotype to Predict Response to Biologic Drugs in Rheumatoid Arthritis.Journal of personalized medicine · 2019Review
- Circulating B Cells With Memory and Antibody-Secreting Phenotypes Are Detectable in Pediatric Kidney Transplant Recipients Before the Development of Antibody-Mediated Rejection.Transplantation direct · 2019Article
- Pretransplant transcriptomic signature in peripheral blood predicts early acute rejection.JCI insight · 2019Article
- Visualizing microbiome-immune system interplay.Immunotherapy · 2019Article
- Applying Mass Cytometry to the Analysis of Lymphoid Populations in Transplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2017Review
- Immunotherapy biomarkers 2016: overcoming the barriers.Journal for immunotherapy of cancer · 2017Article
- Current status of alloimmunity.Current opinion in nephrology and hypertension · 2016Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundKidney 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. METHODS AND
findingsSingle-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.
conclusionsMeasuring 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.
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