Flowsom: An R-Based Evaluation Strategy for Flow Cytometry-Based Measurable Residual Disease (MRD) Diagnostics in Acute Myeloid Leukemia (AML)

Patients with Acute Myeloid Leukemia (AML) frequently relapse due to chemorefractory AML cells persisting after intensive chemotherapy at levels below the 5% morphological detection threshold (measurable residual disease, MRD). MRD has been established as an important prognostic factor for relapse-f...

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Bibliographic Details
Published in:Blood 2019-11, Vol.134 (Supplement_1), p.4656-4656
Main Authors: Bücklein, Veit, Stein, Alexandra, Tast, Benjamin, Koehnke, Thomas, Spiekermann, Karsten, Lacombe, Francis, Subklewe, Marion
Format: Article
Language:English
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Summary:Patients with Acute Myeloid Leukemia (AML) frequently relapse due to chemorefractory AML cells persisting after intensive chemotherapy at levels below the 5% morphological detection threshold (measurable residual disease, MRD). MRD has been established as an important prognostic factor for relapse-free and overall survival, making it highly relevant for post-remission treatment stratification. In contrast to MRD assessment by molecular techniques, multiparameter flow cytometry (MFC)-based MRD measurements are applicable in more than 95% of AML patients, while still offering a sensitivity of 10-4 to 10-5. Current MFC MRD assessment strategies measure 8-10 fluorochromes in parallel, resulting in a high-dimensional data set. However, evaluation of this data is usually performed by scatterplot-based manual, two-dimensional analysis. This leads to loss of information and significant inter-observer variability in MRD diagnostics. We therefore established a computational data analysis strategy for MFC MRD diagnostics, based on the unsupervised FlowSOM algorithm. By comparison with healthy bone marrow (HBM) data, FlowSOM analysis can identify aberrant (sub-)populations of cells, clustered in nodes (according to similarity of their antigen profile). These nodes can be denoted as “nodes of interest” (NOI) to simplify MRD analysis after clustering. Aim of the project was to establish FlowSOM analysis protocols and retrospectively evaluate their prognostic significance in a cohort of 46 patients with known outcomes. Bone marrow samples of these patients were analyzed at aplasia (day 16 after initiation of induction chemotherapy). Only patients with morphological blast clearance at aplasia were included. Healthy reference FlowSOM trees were established by merging flow data of 17 HBM. Analysis protocols were developed to report individual (“any node” approach) and cumulative (“sum node” approach) differences in NOI percentages when comparing HBM and MRD samples. We then performed FlowSOM MRD analyses in a patient subcohort of 19 AML patients. Importantly, for these analyses, we excluded patients who underwent allogeneic stem cell transplantation in first remission (non-HSCT subcohort). Median follow-up time was 8.3 (range 2-40) months for this subcohort. Receiver operating characteristic (ROC) analyses were used to determine optimal threshold values to differentiate relapse (n=5) and non-relapse (n=14) patients within the cohort. For “sum node” analysis strategies (defi
ISSN:0006-4971
1528-0020
DOI:10.1182/blood-2019-129866