The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Standardization of whole blood immune phenotype monitoring for clinical trials: panels and methods from the ONE study
Open accessAbstract
Background: 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. Methods: 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. Results: 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. Conclusions: 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.
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Cites
Interpreting flow cytometry data: a guide for the perplexed
Herzenberg, L. A., Tung, J., Moore, W. A., Herzenberg, L. A., & Parks, D. R. (2006) · Nature Immunology · doi:10.1038/ni0706-681 · Cited by 464
Mechanisms of Rejection: Current Perspectives
Wood, K. J., & Goto, R. (2012) · Transplantation · doi:10.1097/tp.0b013e31823cab44 · Cited by 369
Gilani, S. R., Vuga, L. J., Lindell, K. O., Gibson, K. F., Xue, J., Kaminski, N., Valentine, V. G., Lindsay, E. K., George, M. P., Steele, C., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0008959 · Cited by 203
Sleep-dependent activity of T cells and regulatory T cells
Bollinger, T., Bollinger, A., Skrum, L., Dimitrov, S., Lange, T., & Solbach, W. (2009) · Clinical and Experimental Immunology · doi:10.1111/j.1365-2249.2008.03822.x · Cited by 167
A model for harmonizing flow cytometry in clinical trials
the FOCIS Human Immunophenotyping Consortium, Maecker, H. T., & McCoy, J. P. (2010) · Nature Immunology · doi:10.1038/ni1110-975 · Cited by 155 · cited 5×
“The variables that need to be controlled to ensure standardization have been reviewed elsewhere and different models for standardization of sample handling, instrument setup, data acquisition, and data analysis have been proposed [17-20].”
BackgroundMethodInfluentialLévi, F. A., Canon, C., Touitou, Y., Reinberg, A., & Mathé, G. (1988) · Journal of Clinical Investigation · doi:10.1172/jci113333 · Cited by 104
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Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)
Cossarizza, A., Chang, H., Radbruch, A., Abrignani, S., Addo, R., Akdis, M., Andrä, I., Andreata, F., Annunziato, F., Arranz, E., et al. (2021) · European Journal of Immunology · doi:10.1002/eji.202170126 · Cited by 531
Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium
Finak, G., Langweiler, M., Jaimes, M., Malek, M., Taghiyar, J., Korin, Y., Raddassi, K., Devine, L., Obermoser, G., Pekalski, M. L., et al. (2016) · Scientific Reports · doi:10.1038/srep20686 · Cited by 285
Complement activation induces excessive T cell cytotoxicity in severe COVID-19
Georg, P., Astaburuaga-García, R., Bonaguro, L., Brumhard, S., Michalick, L., Lippert, L. J., Kostevc, T., Gäbel, C., Schneider, M., Streitz, M., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.040 · Cited by 218
Self-citationKverneland, A. H., Streitz, M., Geissler, E., Hutchinson, J., Vogt, K., Boës, D., Niemann, N., Pedersen, A. E., Schlickeiser, S., & Sawitzki, B. (2016) · Cytometry Part A · doi:10.1002/cyto.a.22855 · Cited by 99
Self-citationIvison, S., Malek, M., Garcia, R. V., Broady, R., Halpin, A., Richaud, M., Brant, R. F., Wang, S.-I., Goupil, M., Guan, Q., et al. (2018) · JCI Insight · doi:10.1172/jci.insight.121867 · Cited by 49
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Metadata
- Authors
- Streitz, M., Miloud, T., Kapinsky, M., Reed, M. R., Magari, R., Geissler, E. K., Hutchinson, J. A., Vogt, K., Schlickeiser, S., Kverneland, A. H., Meisel, C., Volk, H.-D., & Sawitzki, B.
- Venue
- Transplantation Research
- Published
- 2013-10-25
- Volume
- 2
- Issue
- 1
- Pages
- 17-17
- ISSN
- 2047-1440 (ISSN-L)
- OpenAlex
- W2151829671
- Cited by
- 214
- References
- 6
- FWCI
- 11.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Streitz, M., Miloud, T., Kapinsky, M., Reed, M. R., Magari, R., Geissler, E. K., Hutchinson, J. A., Vogt, K., Schlickeiser, S., Kverneland, A. H., Meisel, C., Volk, H.-D., & Sawitzki, B. (2013). Standardization of whole blood immune phenotype monitoring for clinical trials: panels and methods from the ONE study. Transplantation Research. https://doi.org/10.1186/2047-1440-2-17
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