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The purpose of this study was to determine whether the development of a standardized approach to the collection of intestinal tissue from healthy volunteers, isolation of gut associated lymphoid tissue mucosal mononuclear cells (MMC), and characterization of mucosal T cell phenotypes by flow cytometry was sufficient to minimize differences in the normative ranges of flow parameters generated at two trial sites. Forty healthy male study participants were enrolled in Pittsburgh and Los Angeles. MMC were isolated from rectal biopsies using the same biopsy acquisition and enzymatic digestion protocols. As an additional comparator, peripheral blood mononuclear cells (PBMC) were collected from the study participants. For quality control, cryopreserved PBMC from a single donor were supplied to both sites from a central repository (qPBMC). Using a jointly optimized standard operating procedure, cells were isolated from tissue and blood and stained with monoclonal antibodies targeted to T cell phenotypic markers. Site-specific flow data were analyzed by an independent center which analyzed all data from both sites. Ranges for frequencies for overall CD4+ and CD8+ T cells, derived from the qPBMC samples, were equivalent at both UCLA and MWRI. However, there were significant differences across sites for the majority of T cell activation and memory subsets in qPBMC as well as PBMC and MMC. Standardized protocols to collect, stain, and analyze MMC and PBMC, including centralized analysis, can reduce but not exclude variability in reporting flow data within multi-site studies. Based on these data, centralized processing, flow cytometry, and analysis of samples may provide more robust data across multi-site studies. Centralized processing requires either shipping of fresh samples or cryopreservation and the decision to perform centralized versus site processing needs to take into account the drawbacks and restrictions associated with each method.

plos one

Exploring the Feasibility of Multi-Site Flow Cytometric Processing of Gut Associated Lymphoid Tissue with Centralized Data Analysis for Multi-Site Clinical Trials