Strategies for improving the reporting of human immunophenotypes by flow cytometry.

Background: Flow cytometry is the gold standard for phenotyping and quantifying immune cells. New technologies have greatly increased our capacity to measure both routine and complex immunophenotypes. The reporting of immunophenotype data is not consistent in human studies yet it is quite critical for understanding disease specific changes, responses to immunotherapies, and normal immune homeostasis. Here we examine the barriers that hinder cross comparisons of flow cytometry data collected from human studies and clinical trials.
Findings: We demonstrate that phenotypes reported as percentages within a cell compartment (i.e. myeloid derived suppressor cells as a percent of mononuclear cells) without providing data on the parent population may contribute to misleading conclusions. The enumeration of phenotypes as cell counts (cells/μl) provides a basis to more accurately compare the relationships among phenotypes. Finally, we provide evidence that density gradient centrifugation, which eliminates the ability to measure phenotypes as cell counts, can affect the expression of surface markers and consequently alter the distribution of particular immunophenotypes.
Conclusions: We propose that by measuring immunophenotypes as cell counts from minimally manipulated samples (whole blood) will improve the reporting of flow data and facilitate more direct comparisons of data across human studies.