Quality Assessment of a Large Multi-Center Flow Cytometric Dataset of Acute Myeloid Leukemia Patients—A EuroFlow Study

Anne E. Bras, Sergio Matarraz, EuroFlow Consortium, Stefan Nierkens, Paula Fernández, Jan Philippé, Carmen Mariana Aanei, Fabiana Vieira de Mello, Leire Burgos, Alita J. van der Sluijs-Gelling, Georgiana Emilia Grigore, Jacques J.M. van Dongen, Alberto Orfao, Vincent H.J. van der Velden*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Flowcytometric analysis allows for detailed identification and characterization of large numbers of cells in blood, bone marrow, and other body fluids and tissue samples and therefore contributes to the diagnostics of hematological malignancies. Novel data analysis tools allow for multidimensional analysis and comparison of patient samples with reference databases of normal, reactive, and/or leukemia/lymphoma patient samples. Building such reference databases requires strict quality assessment (QA) procedures. Here, we compiled a dataset and developed a QA methodology of the EuroFlow Acute Myeloid Leukemia (AML) database, based on the eight-color EuroFlow AML panel consisting of six different antibody combinations, including four backbone markers. In total, 1142 AML cases and 42 normal bone marrow samples were included in this analysis. QA was performed on 803 AML cases using multidimensional analysis of backbone markers, as well as tube-specific markers, and data were compared using classical analysis employing median and peak expression values. Validation of the QA procedure was performed by re-analysis of >300 cases and by running an independent cohort of 339 AML cases. Initial evaluation of the final cohort confirmed specific immunophenotypic patterns in AML subgroups; the dataset therefore can reliably be used for more detailed exploration of the immunophenotypic variability of AML. Our data show the potential pitfalls and provide possible solutions for constructing large flowcytometric databases. In addition, the provided approach may facilitate the building of other databases and thereby support the development of novel tools for (semi)automated QA and subsequent data analysis.

Original languageEnglish
Article number2011
Issue number8
Publication statusPublished - 15 Apr 2022

Bibliographical note

Funding: The EuroFlow Consortium received support from the FP6-2004-LIFESCIHEALTH-5 program of the European Commission (grant LSHB-CT-2006-018708) as a Specific Targeted Research Project (STREP). The EuroFlow Consortium is part of the European Scientific Foundation for Hemato Oncology (ESLHO), a Scientific Working Group (SWG) of the European Hematology Association (EHA). S.M. was supported by Acción Estratégica en Salud (AES) (Grant PI21_01115) and the grant of CIBERONC of the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación, Madrid, Spain and FONDOS FEDER (no. CB16/12/00400).

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© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


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