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JCI Insight. 2018 Dec 6;3(23). pii: 121867. doi: 10.1172/jci.insight.121867. [Epub ahead of print]

A standardized immune phenotyping and automated data analysis platform for multicenter biomarker studies.

Author information

1
Department of Surgery, University of British Columbia, Vancouver, British Columbia, Canada.
2
BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada.
3
Terry Fox Laboratory, BC Cancer, Vancouver, British Columbia, Canada.
4
Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
5
Alberta Transplant Institute, University of Alberta, Edmonton, Alberta, Canada.
6
Hôpital Maisonneuve-Rosemont, University of Montreal, Montreal, Quebec, Canada.
7
Department of Pediatrics and Child Health/Internal Medicine, University of Manitoba/Cancer Care Manitoba, Winnipeg, Manitoba, Canada.
8
Toronto General Research Institute, University of Toronto, Toronto, Ontario, Canada.
9
Health Sciences Centre, Diagnostic Services Manitoba, Winnipeg, Manitoba, Canada.
10
Department of Laboratory Medicine, Toronto General Hospital, Toronto, Ontario, Canada.
11
Institute of Medical Immunology, Charité, Universitätsmedizin Berlin, Berlin, Germany.
12
Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.

Abstract

The analysis and validation of flow cytometry-based biomarkers in clinical studies are limited by the lack of standardized protocols that are reproducible across multiple centers and suitable for use with either unfractionated blood or cryopreserved PBMCs. Here we report the development of a platform that standardizes a set of flow cytometry panels across multiple centers, with high reproducibility in blood or PBMCs from either healthy subjects or patients 100 days after hematopoietic stem cell transplantation. Inter-center comparisons of replicate samples showed low variation, with interindividual variation exceeding inter-center variation for most populations (coefficients of variability <20% and interclass correlation coefficients >0.75). Exceptions included low-abundance populations defined by markers with indistinct expression boundaries (e.g., plasmablasts, monocyte subsets) or populations defined by markers sensitive to cryopreservation, such as CD62L and CD45RA. Automated gating pipelines were developed and validated on an independent data set, revealing high Spearman's correlations (rs >0.9) with manual analyses. This workflow, which includes pre-formatted antibody cocktails, standardized protocols for acquisition, and validated automated analysis pipelines, can be readily implemented in multicenter clinical trials. This approach facilitates the collection of robust immune phenotyping data and comparison of data from independent studies.

KEYWORDS:

Adaptive immunity; Immunology; Innate immunity; Stem cell transplantation; Transplantation

PMID:
30518691
DOI:
10.1172/jci.insight.121867
Free PMC Article

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