A method for identification and analysis of non-overlapping myeloid immunophenotypes in humans
Michael P Gustafson1, Yi Lin2, Mary L Maas1
1Human Cellular Therapy Laboratory, Division of Transfusion Medicine, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States of America.
Insights
This study introduces a new flow cytometry method for precisely identifying human leukocyte populations. The novel approach standardizes immunophenotyping for improved clinical trial biomarker discovery.
Area of Science:
- Immunology
- Biotechnology
Background:
- Flow cytometry biomarker development is hindered by inconsistent sample processing and immunophenotyping.
- Accurate cell function analysis requires precise identification of homogeneous cell populations.
Purpose of the Study:
- To develop a standardized method for identifying and analyzing human leukocyte populations using flow cytometry.
- To overcome limitations in current flow cytometry protocols for clinical research.
Main Methods:
- Utilized eight 10-color flow cytometric protocols with novel software analysis.
- Employed un-manipulated biological sample preparation for direct quantitation.
- Developed specific myeloid protocols to define distinct phenotypes, including myeloid-derived suppressor cells (MDSCs).
Main Results:
- Enabled direct quantitation of leukocytes and non-overlapping immunophenotypes.
- Successfully defined distinct myeloid cell phenotypes: monocytes, granulocytes, dendritic cells, immature myeloid cells, and MDSCs.
- Identified CD123 as a key marker for immature MDSCs (LIN-CD33+HLA-DR-).
Conclusions:
- The developed method allows comprehensive analysis of peripheral blood leukocytes.
- This approach facilitates standardization across laboratories for human studies.
- Improved immunophenotyping enhances biomarker discovery and clinical trial reliability.
Abstract:
The development of flow cytometric biomarkers in human studies and clinical trials has been slowed by inconsistent sample processing, use of cell surface markers, and reporting of immunophenotypes. Additionally, the function(s) of distinct cell types as biomarkers cannot be accurately defined without the proper identification of homogeneous populations. As such, we developed a method for the identification and analysis of human leukocyte populations by the use of eight 10-color flow cytometric protocols in combination with novel software analyses. This method utilizes un-manipulated biological sample preparation that allows for the direct quantitation of leukocytes and non-overlapping immunophenotypes. We specifically designed myeloid protocols that enable us to define distinct phenotypes that include mature monocytes, granulocytes, circulating dendritic cells, immature myeloid cells, and myeloid derived suppressor cells (MDSCs). We also identified CD123 as an additional distinguishing marker for the phenotypic characterization of immature LIN-CD33+HLA-DR- MDSCs. Our approach permits the comprehensive analysis of all peripheral blood leukocytes and yields data that is highly amenable for standardization across inter-laboratory comparisons for human studies.
