Strategies for improving the reporting of human immunophenotypes by flow cytometry

Journal for ImmunoTherapy of Cancer

Allan B Dietz¹  Mabel Ryder³  Yi Lin²  Michael P Gustafson¹ 

[1] Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st St. SW, Rochester, MN 55905, USA;Division of Hematology, Mayo Clinic, 200 1st St. SW, Rochester, MN 55905, USA;Division of Endocrinology, Mayo Clinic, 200 1st St. SW, Rochester, MN 55905, USA

关键词: Biomarkers;    Human immunology;    Myeloid derived suppressor cells;    Immunophenotypes;    Flow cytometry;   

Others  :  803368
DOI  :  10.1186/2051-1426-2-18

 received in 2014-02-04, accepted in 2014-05-07,  发布年份 2014

【 摘 要 】

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.

【 授权许可】

   
2014 Gustafson et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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