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Leukemia. 2018 Apr;32(4):874-881. doi: 10.1038/leu.2017.313. Epub 2017 Nov 1.

Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia.

Author information

1
Université Paris Descartes-Sorbonne Paris Cité, Institut Necker-Enfants-Malades, INSERM UMR1151, Paris, France.
2
Biological Hematology, AP-HP Necker-Enfants-Malades, Paris, France.
3
CLIP-Childhood Leukaemia Investigation Prague, Department of Paediatric Haematology and Oncology, Second Faculty of Medicine, Charles University, University Hospital Motol, Prague, Czech Republic.
4
Dutch Childhood Oncology Group, The Hague, The Netherlands.
5
Department of Immunohematology and Blood Transfusion (IHB), Leiden University Medical Center, Leiden, The Netherlands.
6
Cytognos SL, Salamanca, Spain.
7
Department of Microbiology and Immunology, Zabrze, Medical University of Silesia (SUM), Katowice, Poland.
8
Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
9
Tettamanti Research Center, Pediatric Clinic University of Milano Bicocca, Monza (MB),Italy.
10
Department of Pediatrics, Faculty of Medicine, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
11
Department of Pediatric Hematology and Oncology, Zabrze, Medical University of Silesia (SUM), Katowice, Poland.
12
Cancer Research Center (IBMCC-CSIC), Department of Medicine and Cytometry Service, University of Salamanca (USAL), Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain and Centro de Investigación Biomédica en Red de Cáncer, Instituto Carlos III, Madrid, Spain.
13
Hematology Service, University Hospital of Salamanca, Salamanca, Spain.
14
Department of Hematology, University of Schleswig-Holstein, Campus Kiel, Kiel, Germany.
15
Institute for Laboratory Medicin, Kantonsspital Aarau AG, Aarau, Switzerland.
16
Clinica Universidad de Navarra-Centro De Investigaciones Medicas Aplicadas (CIMA), University of Navarra, Pamplona, Spain.
17
COPPE-Computation Engineering & Systems Post-graduation, Federal University of Rio de Janeiro, Rio de Janeiro(UFRJ), Brazil.

Abstract

Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide towards the relevant classification panel (T-cell acute lymphoblastic leukemia (T-ALL), B-cell precursor (BCP)-ALL and/or acute myeloid leukemia (AML)) and final diagnosis. Now we built a reference database with 656 typical AL samples (145 T-ALL, 377 BCP-ALL, 134 AML), processed and analyzed via standardized protocols. Using principal component analysis (PCA)-based plots and automated classification algorithms for direct comparison of single-cells from individual patients against the database, another 783 cases were subsequently evaluated. Depending on the database-guided results, patients were categorized as: (i) typical T, B or Myeloid without or; (ii) with a transitional component to another lineage; (iii) atypical; or (iv) mixed-lineage. Using this automated algorithm, in 781/783 cases (99.7%) the right panel was selected, and data comparable to the final WHO-diagnosis was already provided in >93% of cases (85% T-ALL, 97% BCP-ALL, 95% AML and 87% mixed-phenotype AL patients), even without data on the full-characterization panels. Our results show that database-guided analysis facilitates standardized interpretation of ALOT results and allows accurate selection of the relevant classification panels, hence providing a solid basis for designing future WHO AL classifications.

PMID:
29089646
PMCID:
PMC5886046
DOI:
10.1038/leu.2017.313
[Indexed for MEDLINE]
Free PMC Article

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