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

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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.

Authors

Sabine Ivison, Mehrnoush Malek, Rosa V. Garcia, Raewyn Broady, Anne Halpin, Manon Richaud, Rollin F. Brant, Szu-I Wang, Mathieu Goupil, Qingdong Guan, Peter Ashton, Jason Warren, Amr Rajab, Simon Urschel, Deepali Kumar, Mathias Streitz, Birgit Sawitzki, Stephan Schlickeiser, Janetta J. Bijl, Donna A. Wall, Jean-Sebastien Delisle, Lori J. West, Ryan R. Brinkman, Megan K. Levings