{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T03:08:24Z","timestamp":1792724904382,"version":"4.5.0"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Transplant Res"],"published-print":{"date-parts":[[2013,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Immune monitoring by flow cytometry is a fast and highly informative way of studying the effects of novel therapeutics aimed at reducing transplant rejection or treating autoimmune diseases. The ONE Study consortium has recently initiated a series of clinical trials aimed at using different cell therapies to promote tolerance to renal allografts. To compare the effectiveness of different cell therapies, the consortium developed a robust immune monitoring strategy, including procedures for whole blood (WB) leukocyte subset profiling by flow cytometry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Six leukocyte profiling panels computing 7- to 9-surface marker antigens for monitoring the major leukocyte subsets as well as characteristics of T cell, B cell, and dendritic cell (DC) subsets were designed. The precision and variability of these panels were estimated. The assay was standardized within eight international laboratories using Flow-Set Pro beads for mean fluorescence intensity target definition and the flow cytometer setup procedure. Standardization was demonstrated by performing inter-site comparisons.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Optimized methods for sample collection, storage, preparation, and analysis were established, including protocols for gating target subsets. WB specimen age testing demonstrated that staining must be performed within 4 hours of sample collection to keep variability low, meaning less than or equal to 10% for the majority of defined leukocyte subsets. Inter-site comparisons between all participating centers testing shipped normal WB revealed good precision, with a variability of 0.05% to 30% between sites. Intra-assay analyses revealed a variability of 0.05% to 20% for the majority of subpopulations. This was dependent on the frequency of the particular subset, with smaller subsets showing higher variability. The intra-assay variability performance defined limits of quantitation (LoQ) for subsets, which will be the basis for assessing statistically significant differences achieved by the different cell therapies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Local performance and central analysis of the ONE Study flow cytometry panel yields acceptable variability in a standardized assay at multiple international sites. These panels and procedures with WB allow unmanipulated analysis of changes in absolute cell numbers of leukocyte subsets in single- or multicenter clinical trials. Accordingly, we propose the ONE Study panel may be adopted as a standardized method for monitoring patients in clinical trials enrolling transplant patients, particularly trials of novel tolerance promoting therapies, to facilitate fair and meaningful comparisons between trials.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/2047-1440-2-17","type":"journal-article","created":{"date-parts":[[2013,10,25]],"date-time":"2013-10-25T14:35:03Z","timestamp":1382711703000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":197,"title":["Standardization of whole blood immune phenotype monitoring for clinical trials: panels and methods from the ONE study"],"prefix":"10.1186","volume":"2","author":[{"given":"Mathias","family":"Streitz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tewfik","family":"Miloud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Kapinsky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael R","family":"Reed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Magari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward K","family":"Geissler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James A","family":"Hutchinson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katrin","family":"Vogt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephan","family":"Schlickeiser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anders Handrup","family":"Kverneland","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Meisel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hans-Dieter","family":"Volk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Birgit","family":"Sawitzki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2013,10,25]]},"reference":[{"issue":"3","key":"37_CR1","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1016\/j.smim.2011.07.007","volume":"23","author":"M Battaglia","year":"2011","unstructured":"Battaglia M, Roncarolo MG: Immune intervention with T regulatory cells: past lessons and future perspectives for type 1 diabetes. 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