Lecrevisse, Q. (Quentin)
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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.
- Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study(2021) Fluxá, R. (Rafael); Montero, J. (Juan); Grigore, G. (Georgiana); Buracchi, C. (Chiara); Fernández, P. (Paula); Morf, D. (Daniela); Orfao, A. (Alberto); Nierkens, S. (Stefan); Mejstrikova, E. (Ester); Barrena, S. (Susana); Sedek, L. (Lukasz); Bie, M. (Maaike) de; Lhermitte, L. (Ludovic); Sobral-da-Costa, E. (Elaine); Szczepanski, T. (Tomasz); Barreau, S. (Sylvain); Aanei, C.M. (Carmen Mariana); Burgos, L. (Leire); Brüggemann, M. (Monika); Dongen, J.J.M. (Jacques J. M.) van; Caetano, J. (Joana); Gaipa, G. (Giuseppe); Hernández-Delgado, A. (Alejandro); Sluijs-Gelling, A. (Alita) van der; Lecrevisse, Q. (Quentin); 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 toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB,n = 41) and bone marrow (BM;n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r(2) > 0.95 for all cell types in PB andr(2) > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool).
- Flow cytometry for fast screening and automated risk assessment in systemic light-chain amyloidosis(Nature, 2019) González, M.E. (María Esther); Cedena, M.T. (María Teresa); Verde, J. (Javier); Pérez, J.J. (José J.); Martínez-López, J. (Joaquín); Krsnik, I. (Isabel); Gironella, M. (Mercedes); Orfao, A. (Alberto); Vidriales, M.B. (María Belén); Ocio, E.M. (Enrique M.); Mateos, M.V. (María Victoria); Arriba, F. (Felipe) de; Puerta, J.E. (José Enrique) de la; Puig, N. (Noemí); Labrador, J. (Jorge); Burgos, L. (Leire); Lasa, M. (Marta); Palomera, L. (Luis); Lahuerta, J.J. (Juan José); Pérez-Montaña, A. (Albert); Gómez-Toboso, D. (Dolores); Paiva, B. (Bruno); Lecumberri, R. (Ramón); Oriol, A. (Albert); Rubia, J. (Javier) de la; Prosper-Cardoso, F. (Felipe); Casanova, M. (María); Lecrevisse, Q. (Quentin); Merino, J. (Juana); San-Miguel, J.F. (Jesús F.); Moreno, C. (Cristina); Cabañas, V. (Valentín); García-de-Coca, A. (Alfonso)Early diagnosis and risk stratification are key to improve outcomes in light-chain (AL) amyloidosis. Here we used multidimensional-flow-cytometry (MFC) to characterize bone marrow (BM) plasma cells (PCs) from a series of 166 patients including newly-diagnosed AL amyloidosis (N = 94), MGUS (N = 20) and multiple myeloma (MM, N = 52) vs. healthy adults (N = 30). MFC detected clonality in virtually all AL amyloidosis (99%) patients. Furthermore, we developed an automated risk-stratification system based on BMPCs features, with independent prognostic impact on progression-free and overall survival of AL amyloidosis patients (hazard ratio: ≥ 2.9;P ≤ .03). Simultaneous assessment of the clonal PCs immunophenotypic protein expression profile and the BM cellular composition, mapped AL amyloidosis in the crossroad between MGUS and MM; however, lack of homogenously-positive CD56 expression, reduction of B-cell precursors and a predominantly-clonal PC compartment in the absence of an MM-like tumor PC expansion, emerged as hallmarks of AL amyloidosis (ROC-AUC = 0.74;P < .001), and might potentially be used as biomarkers for the identification of MGUS and MM patients, who are candidates for monitoring pre-symptomatic organ damage related to AL amyloidosis. Altogether, this study addressed the need for consensus on how to use flow cytometry in AL amyloidosis, and proposes a standardized MFC-based automated risk classification ready for implementation in clinical practice.
- Expert-independent classification of mature B-cell neoplasms using standardized flow cytometry: a multicentric study(2022) Böttcher, S. (Sebastian); Fluxá, R. (Rafael); Verde, J. (Javier); Montero, J. (Juan); Grigore, G. (Georgiana); Novakova, M. (Michaela); Fernández, P. (Paula); Orfao, A. (Alberto); Kalina, T. (Tomas); Engelmann, R. (Robby); Ritgen, M. (Matthias); Burgos, L. (Leire); Lange, S. (Sandra); Dongen, J.J.M. (Jacques J. M.) van; Caetano, J. (Joana); Lecrevisse, Q. (Quentin); Philippé, J. (Jan); Velden, V.H.J. (Vicent H. J.) van der; Pedreira, C.E. (Carlos E.)Reproducible expert-independent flow-cytometric criteria for the differential diagnoses between mature B-cell neoplasms are lacking. We developed an algorithm-driven classification for these lymphomas by flow cytometry and compared it to the WHO gold standard diagnosis. Overall, 662 samples from 662 patients representing 9 disease categories were analyzed at 9 laboratories using the previously published EuroFlow 5-tube-8-color B-cell chronic lymphoproliferative disease antibody panel. Expression levels of all 26 markers from the panel were plotted by B-cell entity to construct a univariate, fully standardized diagnostic reference library. For multivariate data analysis, we subsequently used canonical correlation analysis of 176 training cases to project the multidimensional space of all 26 immunophenotypic parameters into 36 2-dimensional plots for each possible pairwise differential diagnosis. Diagnostic boundaries were fitted according to the distribution of the immunophenotypes of a given differential diagnosis. A diagnostic algorithm based on these projections was developed and subsequently validated using 486 independent cases. Negative predictive values exceeding 92.1% were observed for all disease categories except for follicular lymphoma. Particularly high positive predictive values were returned in chronic lymphocytic leukemia (99.1%), hairy cell leukemia (97.2%), follicular lymphoma (97.2%), and mantle cell lymphoma (95.4%). Burkitt and CD101 diffuse large B-cell lymphomas were difficult to distinguish by the algorithm. A similar ambiguity was observed between marginal zone, lymphoplasmacytic, and CD102 diffuse large B-cell lymphomas. The specificity of the approach exceeded 98% for all entities. The univariate immunophenotypic library and the multivariate expert-independent diagnostic algorithm might contribute to increased reproducibility of future diagnostics in mature B-cell neoplasms.
- EuroFlow Lymphoid Screening Tube (LST) data base for automated identification of blood lymphocyte subsets(Elsevier BV, 2019) Böttcher, S. (Sebastian); Muñoz, N. (Noemí); Fluxá, R. (Rafael); Montero, J. (Juan); Grigore, G. (Georgiana); Santos, A.H. (Ana Helena); Fernández, P. (Paula); Orfao, A. (Alberto); Hernandez, J.M. (J. M.); Barrena, S. (Susana); Sedek, L. (Lukasz); Almeida, J. (J.); Hernández, A. (Alejando); Dongen, J.J.M. (Jacques J. M.) van; Paiva, B. (Bruno); Lima, M. (Margarida); Lecrevisse, Q. (Quentin); Velden, V.H.J. (Vicent H. J.) van derIn recent years the volume and complexity of flow cytometry data has increased substantially. This has led to a greater number of identifiable cell populations in a single measurement. Consequently, new gating strategies and new approaches for cell population definition are required. Here we describe how the EuroFlow Lymphoid Screening Tube (LST) reference data base for peripheral blood (PB) samples was designed, constructed and validated for automated gating of the distinct lymphoid (and myeloid) subsets in PB of patients with chronic lymphoproliferative disorders (CLPD). A total of 46 healthy/reactive PB samples which fulfilled predefined technical requirements, were used to construct the LST-PB reference data base. In addition, another set of 92 PB samples (corresponding to 10 healthy subjects, 51 B-cell CLPD and 31 T/NK-cell CLPD patients), were used to validate the automated gating and cell-population labeling tools with the Infinicyt software. An overall high performance of the LST-PB data base was observed with a median percentage of alarmed cellular events of 0.8% in 10 healthy donor samples and of 44.4% in CLPD data files containing 49.8% (range: 1.3–96%) tumor cells. The higher percent of alarmed cellular events in every CLPD sample was due to aberrant phenotypes (75.6% cases) and/or to abnormally increased cell counts (86.6% samples). All 18 (22%) data files that only displayed numerical alterations, corresponded to T/NK-cell CLPD cases which showed a lower incidence of aberrant phenotypes (41%) vs B-cell CLPD cases (100%). Comparison between automated vs expert-bases manual classification of normal (r2 = 0.96) and tumor cell populations (rho = 0.99) showed a high degree of correlation. In summary, our results show that automated gating of cell populations based on the EuroFlow LST-PB data base provides an innovative, reliable and reproducible tool for fast and simplified identification of normal vs pathological B and T/NK lymphocytes in PB of CLPD patients.