Fernandez, P. (P.)

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    Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia
    (Springer Nature, 2018) Verde, J. (Javier); Marvelde, J. (Jeroen) te; Grigore, G. (Georgiana); Martin-Ayuso, M. (M.); Asnaf, V. (V.); Novakova, M. (Michaela); Buracchi, C. (Chiara); Fernandez, P. (P.); Bulsa, J. (J.); Orfao, A. (Alberto); Vidriales, M.B. (María Belén); Trinquand, A. (A.); Kalina, T. (Tomas); Mejstrikova, E. (Ester); Sedek, L. (Lukasz); Bras, A.E. (Anne E.); Matarraz, S. (Sergio); Lhermitte, L. (Ludovic); Sobral-da-Costa, E. (Elaine); Szczepanski, T. (Tomasz); Hrusak, O. (O.); Burgos, L. (Leire); Brüggemann, M. (Monika); López, A. (Andrés); Dongen, J.J.M. (Jacques J. M.) van; Paiva, B. (Bruno); Gaipa, G. (Giuseppe); Sonneveld, E. (E.); Sluijs-Gelling, A. (Alita) van der; Lecrevisse, Q. (Quentin); Sá-Bacelar, T. (T.) de; Velden, V.H.J. (Vicent H. J.) van der; Pedreira, C.E. (Carlos E.)
    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.