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1. Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study

Author

Lhermitte, Ludovic, Barreau, Sylvain, Morf, Daniela, Fernandez, Paula, Grigore, Georgiana, Barrena, Susana, de Bie, Maaike, Flores-Montero, Juan, Brüggemann, Monika, Mejstrikova, Ester, Nierkens, Stefan, Burgos, Leire, Caetano, Joana, Gaipa, Giuseppe, Buracchi, Chiara, da Costa, Elaine Sobral, Sedek, Lukasz, Szczepański, Tomasz, Aanei, Carmen-Mariana, van der Sluijs-Gelling, Alita, Delgado, Alejandro Hernández, Fluxa, Rafael, Lecrevisse, Quentin, Pedreira, Carlos E., van Dongen, Jacques J.M., Orfao, Alberto, van der Velden, Vincent H.J., van Dongen, J. J.M., Bitter, W.M., Lubbers, B.R., Teodosio, C.I., Zlei, M., van der Sluijs-Gelling, A.J., de Bie, F., de Bruin-Versteeg, S., van der Burg, M., Schilham, M.W., van der Velden, V. H.J., Langerak, A.W., te Marvelde, J., Bras, A.E., Schilperoord-Vermeulen, J., Jugooa, R., Heezen, K.C., Orfao, A., Almeida, J., Vidriales, M.B., Flores-Montero, J., Pérez-Andrés, M., Matarraz, S., Martín, L., Lecrevisse, Q., Pérez-Morán, J.J., Puig, N., Almeida, A. Medina, Gomes da Silva, M., Faria, T., Brüggemann, M., Ritgen, M., Szczepanowski, M., Kohlscheen, S., Laqua, A., Harbst, E., Finke, J., Asnafi, V., Lhermitte, L., Duroyon, E., Trka, J., Hrusak, O., Kalina, T., Mejstrikova, E., Novakova, M., Thurner, D., Kanderova, V., Szczepanski, T., Sędek, L., Bulsa, J., Slota, L., Kulis, J., Pedreira, C.E., da Costa, E. Sobral, Nierkens, S., de Jong, A., de Koning, A., Lima, M., Santos, A.H., Böttcher, S., Lange, S., Engelmann, R., Paape, D., Machka, C., Gaipa, G., Burracchi, C., Bugarin, C., Lopez-Granados, E., del Pino Molina, L., Campos-Guyotat, L., Aanei, C., Miguel, J. F. San, Paiva, B., Burgos, L., Villamor-Casas, N., Magnano, L., Philippé, J., Bonroy, C., Denys, B., Willems, A., Breughe, P., de Wolf, J., Sousa, A.E., Silva, S.L., Fernandez, P., and Morf, D.

Published
2021
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2. Flow cytometric analysis of myelodysplasia: Pre-analytical and technical issues-Recommendations from the European LeukemiaNet

Author

van der Velden, VHJ, Preijers, F, Johansson, U, Westers, TM, Dunlop, A, Porwit, A, Bene, MC, Valent, P, te Marvelde, J, Wagner-Ballon, O, Oelschlaegel, U, Saft, L, Kordasti, S, Ireland, R, Cremers, E, Alhan, C, Duetz, C, Hobo, W, Chapuis, N, Fontenay, M, Bettelheim, P, Eidenshink-Brodersen, L, Font, P, Loken, MR, Matarraz, S, Ogata, K, Orfao, A, Psarra, K, Subira, D, Wells, DA, Della Porta, MG, Burbury, K, Bellos, F, Weiss, E, Kern, W, van de Loosdrecht, A, van der Velden, VHJ, Preijers, F, Johansson, U, Westers, TM, Dunlop, A, Porwit, A, Bene, MC, Valent, P, te Marvelde, J, Wagner-Ballon, O, Oelschlaegel, U, Saft, L, Kordasti, S, Ireland, R, Cremers, E, Alhan, C, Duetz, C, Hobo, W, Chapuis, N, Fontenay, M, Bettelheim, P, Eidenshink-Brodersen, L, Font, P, Loken, MR, Matarraz, S, Ogata, K, Orfao, A, Psarra, K, Subira, D, Wells, DA, Della Porta, MG, Burbury, K, Bellos, F, Weiss, E, Kern, W, and van de Loosdrecht, A

Abstract

BACKGROUND: Flow cytometry (FCM) aids the diagnosis and prognostic stratification of patients with suspected or confirmed myelodysplastic syndrome (MDS). Over the past few years, significant progress has been made in the FCM field concerning technical issues (including software and hardware) and pre-analytical procedures. METHODS: Recommendations are made based on the data and expert discussions generated from 13 yearly meetings of the European LeukemiaNet international MDS Flow working group. RESULTS: We report here on the experiences and recommendations concerning (1) the optimal methods of sample processing and handling, (2) antibody panels and fluorochromes, and (3) current hardware technologies. CONCLUSIONS: These recommendations will support and facilitate the appropriate application of FCM assays in the diagnostic workup of MDS patients. Further standardization and harmonization will be required to integrate FCM in MDS diagnostic evaluations in daily practice.

Published
2023

3. Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study

Author

Lhermitte, L, Barreau, S, Morf, D, Fernandez, P, Grigore, G, Barrena, S, de Bie, M, Flores-Montero, J, Bruggemann, M, Mejstrikova, E, Nierkens, S, Burgos, L, Caetano, J, Gaipa, G, Buracchi, C, da Costa, E, Sedek, L, Szczepanski, T, Aanei, C, van der Sluijs-Gelling, A, Delgado, A, Fluxa, R, Lecrevisse, Q, Pedreira, C, van Dongen, J, Orfao, A, van der Velden, V, Bitter, W, Lubbers, B, Teodosio, C, Zlei, M, de Bie, F, de Bruin-Versteeg, S, van der Burg, M, Schilham, M, Langerak, A, te Marvelde, J, Bras, A, Schilperoord-Vermeulen, J, Jugooa, R, Heezen, K, Almeida, J, Vidriales, M, Perez-Andres, M, Matarraz, S, Martin, L, Perez-Moran, J, Puig, N, Almeida, A, Gomes da Silva, M, Faria, T, Ritgen, M, Szczepanowski, M, Kohlscheen, S, Laqua, A, Harbst, E, Finke, J, Asnafi, V, Duroyon, E, Trka, J, Hrusak, O, Kalina, T, Novakova, M, Thurner, D, Kanderova, V, Bulsa, J, Slota, L, Kulis, J, de Jong, A, de Koning, A, Lima, M, Santos, A, Bottcher, S, Lange, S, Engelmann, R, Paape, D, Machka, C, Burracchi, C, Bugarin, C, Lopez-Granados, E, del Pino Molina, L, Campos-Guyotat, L, Miguel, J, Paiva, B, Villamor-Casas, N, Magnano, L, Philippe, J, Bonroy, C, Denys, B, Willems, A, Breughe, P, de Wolf, J, Sousa, A, Silva, S, Lhermitte L., Barreau S., Morf D., Fernandez P., Grigore G., Barrena S., de Bie M., Flores-Montero J., Bruggemann M., Mejstrikova E., Nierkens S., Burgos L., Caetano J., Gaipa G., Buracchi C., da Costa E. S., Sedek L., Szczepanski T., Aanei C. -M., van der Sluijs-Gelling A., Delgado A. H., Fluxa R., Lecrevisse Q., Pedreira C. E., van Dongen J. J. M., Orfao A., van der Velden V. H. J., Bitter W. M., Lubbers B. R., Teodosio C. I., Zlei M., van der Sluijs-Gelling A. J., de Bie F., de Bruin-Versteeg S., van der Burg M., Schilham M. W., Langerak A. W., te Marvelde J., Bras A. E., Schilperoord-Vermeulen J., Jugooa R., Heezen K. C., Almeida J., Vidriales M. B., Perez-Andres M., Matarraz S., Martin L., Perez-Moran J. J., Puig N., Almeida A. M., Gomes da Silva M., Faria T., Ritgen M., Szczepanowski M., Kohlscheen S., Laqua A., Harbst E., Finke J., Asnafi V., Duroyon E., Trka J., Hrusak O., Kalina T., Novakova M., Thurner D., Kanderova V., Bulsa J., Slota L., Kulis J., de Jong A., de Koning A., Lima M., Santos A. H., Bottcher S., Lange S., Engelmann R., Paape D., Machka C., Burracchi C., Bugarin C., Lopez-Granados E., del Pino Molina L., Campos-Guyotat L., Aanei C., Miguel J. F. S., Paiva B., Villamor-Casas N., Magnano L., Philippe J., Bonroy C., Denys B., Willems A., Breughe P., de Wolf J., Sousa A. E., Silva S. L., Lhermitte, L, Barreau, S, Morf, D, Fernandez, P, Grigore, G, Barrena, S, de Bie, M, Flores-Montero, J, Bruggemann, M, Mejstrikova, E, Nierkens, S, Burgos, L, Caetano, J, Gaipa, G, Buracchi, C, da Costa, E, Sedek, L, Szczepanski, T, Aanei, C, van der Sluijs-Gelling, A, Delgado, A, Fluxa, R, Lecrevisse, Q, Pedreira, C, van Dongen, J, Orfao, A, van der Velden, V, Bitter, W, Lubbers, B, Teodosio, C, Zlei, M, de Bie, F, de Bruin-Versteeg, S, van der Burg, M, Schilham, M, Langerak, A, te Marvelde, J, Bras, A, Schilperoord-Vermeulen, J, Jugooa, R, Heezen, K, Almeida, J, Vidriales, M, Perez-Andres, M, Matarraz, S, Martin, L, Perez-Moran, J, Puig, N, Almeida, A, Gomes da Silva, M, Faria, T, Ritgen, M, Szczepanowski, M, Kohlscheen, S, Laqua, A, Harbst, E, Finke, J, Asnafi, V, Duroyon, E, Trka, J, Hrusak, O, Kalina, T, Novakova, M, Thurner, D, Kanderova, V, Bulsa, J, Slota, L, Kulis, J, de Jong, A, de Koning, A, Lima, M, Santos, A, Bottcher, S, Lange, S, Engelmann, R, Paape, D, Machka, C, Burracchi, C, Bugarin, C, Lopez-Granados, E, del Pino Molina, L, Campos-Guyotat, L, Miguel, J, Paiva, B, Villamor-Casas, N, Magnano, L, Philippe, J, Bonroy, C, Denys, B, Willems, A, Breughe, P, de Wolf, J, Sousa, A, Silva, S, Lhermitte L., Barreau S., Morf D., Fernandez P., Grigore G., Barrena S., de Bie M., Flores-Montero J., Bruggemann M., Mejstrikova E., Nierkens S., Burgos L., Caetano J., Gaipa G., Buracchi C., da Costa E. S., Sedek L., Szczepanski T., Aanei C. -M., van der Sluijs-Gelling A., Delgado A. H., Fluxa R., Lecrevisse Q., Pedreira C. E., van Dongen J. J. M., Orfao A., van der Velden V. H. J., Bitter W. M., Lubbers B. R., Teodosio C. I., Zlei M., van der Sluijs-Gelling A. J., de Bie F., de Bruin-Versteeg S., van der Burg M., Schilham M. W., Langerak A. W., te Marvelde J., Bras A. E., Schilperoord-Vermeulen J., Jugooa R., Heezen K. C., Almeida J., Vidriales M. B., Perez-Andres M., Matarraz S., Martin L., Perez-Moran J. J., Puig N., Almeida A. M., Gomes da Silva M., Faria T., Ritgen M., Szczepanowski M., Kohlscheen S., Laqua A., Harbst E., Finke J., Asnafi V., Duroyon E., Trka J., Hrusak O., Kalina T., Novakova M., Thurner D., Kanderova V., Bulsa J., Slota L., Kulis J., de Jong A., de Koning A., Lima M., Santos A. H., Bottcher S., Lange S., Engelmann R., Paape D., Machka C., Burracchi C., Bugarin C., Lopez-Granados E., del Pino Molina L., Campos-Guyotat L., Aanei C., Miguel J. F. S., Paiva B., Villamor-Casas N., Magnano L., Philippe J., Bonroy C., Denys B., Willems A., Breughe P., de Wolf J., Sousa A. E., and Silva S. L.

Abstract

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 (r2 > 0.95 for all cell types in PB and r2 > 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). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a “sample-in and result-out” approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal p

Published
2021

4. Standardization of flow cytometry in myelodysplastic syndromes: a report from an international consortium and the European LeukemiaNet Working Group

Author

Westers, T M, Ireland, R, Kern, W, Alhan, C, Balleisen, J S, Bettelheim, P, Burbury, K, Cullen, M, Cutler, J A, Della Porta, M G, Dräger, A M, Feuillard, J, Font, P, Germing, U, Haase, D, Johansson, U, Kordasti, S, Loken, M R, Malcovati, L, te Marvelde, J G, Matarraz, S, Milne, T, Moshaver, B, Mufti, G J, Ogata, K, Orfao, A, Porwit, A, Psarra, K, Richards, S J, Subirá, D, Tindell, V, Vallespi, T, Valent, P, van der Velden, V H J, de Witte, T M, Wells, D A, Zettl, F, Béné, M C, and van de Loosdrecht, A A

Published
2012
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6. The variable biological signature of refractory cytopenia of childhood (RCC), a retrospective EWOG-MDS study

Author

de Winter, D. T. C., Langerak, A. W., te Marvelde, J., Dworzak, M. N., De Moerloose, B., Stary, J., Locatelli, Franco, Hasle, H., de Vries, A. C. H., Schmugge, M., Niemeyer, C. M., van den Heuvel-Eibrink, M. M., van der Velden, V. H. J., Locatelli F. (ORCID:0000-0002-7976-3654), de Winter, D. T. C., Langerak, A. W., te Marvelde, J., Dworzak, M. N., De Moerloose, B., Stary, J., Locatelli, Franco, Hasle, H., de Vries, A. C. H., Schmugge, M., Niemeyer, C. M., van den Heuvel-Eibrink, M. M., van der Velden, V. H. J., and Locatelli F. (ORCID:0000-0002-7976-3654)

Abstract

NO ABSTRACT

Published
2021

10. Standardized flow cytometry for highly sensitive MRD measurements in B-cell acute lymphoblastic leukemia

Author

Theunissen, P, Mejstrikova, E, Sedek, L, Van Der Sluijs-Gelling, A, Gaipa, G, Bartels, M, Sobral da Costa, E, Kotrova, M, Novakova, M, Sonneveld, E, Buracchi, C, Bonaccorso, P, Oliveira, E, Te Marvelde, J, Szczepanski, T, Lhermitte, L, Hrusak, O, Lecrevisse, Q, Grigore, G, Fronkova, E, Trka, J, Bruggemann, M, Orfao, A, Van Dongen, J, Van Der Velden, V, Theunissen P., Mejstrikova E., Sedek L., Van Der Sluijs-Gelling A. J., Gaipa G., Bartels M., Sobral da Costa E., Kotrova M., Novakova M., Sonneveld E., Buracchi C., Bonaccorso P., Oliveira E., Te Marvelde J. G., Szczepanski T., Lhermitte L., Hrusak O., Lecrevisse Q., Grigore G. E., Fronkova E., Trka J., Bruggemann M., Orfao A., Van Dongen J. J. M., Van Der Velden V. H. J., Theunissen, P, Mejstrikova, E, Sedek, L, Van Der Sluijs-Gelling, A, Gaipa, G, Bartels, M, Sobral da Costa, E, Kotrova, M, Novakova, M, Sonneveld, E, Buracchi, C, Bonaccorso, P, Oliveira, E, Te Marvelde, J, Szczepanski, T, Lhermitte, L, Hrusak, O, Lecrevisse, Q, Grigore, G, Fronkova, E, Trka, J, Bruggemann, M, Orfao, A, Van Dongen, J, Van Der Velden, V, Theunissen P., Mejstrikova E., Sedek L., Van Der Sluijs-Gelling A. J., Gaipa G., Bartels M., Sobral da Costa E., Kotrova M., Novakova M., Sonneveld E., Buracchi C., Bonaccorso P., Oliveira E., Te Marvelde J. G., Szczepanski T., Lhermitte L., Hrusak O., Lecrevisse Q., Grigore G. E., Fronkova E., Trka J., Bruggemann M., Orfao A., Van Dongen J. J. M., and Van Der Velden V. H. J.

Abstract

A fully-standardized EuroFlow 8–color antibody panel and laboratory procedure was stepwise designed to measure minimal residual disease (MRD) in B-cell precursor (BCP) acute lymphoblastic leukemia (ALL) patients with a sensitivity of £1025, comparable to real-time quantitative polymerase chain reaction (RQ-PCR)–based MRD detection via antigen-receptor rearrangements. Leukocyte markers and the corresponding antibodies and fluorochromes were selected based on their contribution in separating BCP-ALL cells from normal/regenerating BCP cells in multidimensional principal component analyses. After 5 multicenter design-test-evaluate-redesign phases with a total of 319 BCP-ALL patients at diagnosis, two 8-color antibody tubes were selected, which allowed separation between normal and malignant BCP cells in 99% of studied patients. These 2 tubes were tested with a new erythrocyte bulk-lysis protocol allowing acquisition of high cell numbers in 377 bone marrow follow-up samples of 178 BCP-ALL patients. Comparison with RQ-PCR–based MRD data showed a clear positive relation between the percentage concordant cases and the number of cells acquired. For those samples with >4 million cells acquired, concordant results were obtained in 93% of samples. Most discordances were clarified upon high-throughput sequencing of antigen-receptor rearrangements and blind multicenter reanalysis of flow cytometric data, resulting in an unprecedented concordance of 98% (97% for samples with MRD < 0.01%). In conclusion, the fully standardized EuroFlow BCP-ALL MRD strategy is applicable in >98% of patients with sensitivities at least similar to RQ-PCR (£1025), if sufficient cells (>4 3 106, preferably more) are evaluated.

Published
2017

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

Author

Lhermitte, L, Mejstrikova, E, Van Der Sluijs-Gelling, A, Grigore, G, Sedek, L, Bras, A, Gaipa, G, Sobral Da Costa, E, Novakova, M, Sonneveld, E, Buracchi, C, De Sa Bacelar, T, Te Marvelde, J, Trinquand, A, Asnafi, V, Szczepanski, T, Matarraz, S, Lopez, A, Vidriales, B, Bulsa, J, Hrusak, O, Kalina, T, Lecrevisse, Q, Martin Ayuso, M, Bruggemann, M, Verde, J, Fernandez, P, Burgos, L, Paiva, B, Pedreira, C, Van Dongen, J, Orfao, A, Van Der Velden, V, Lhermitte, L, Mejstrikova, E, Van Der Sluijs-Gelling, A, Grigore, G, Sedek, L, Bras, A, Gaipa, G, Sobral Da Costa, E, Novakova, M, Sonneveld, E, Buracchi, C, De Sa Bacelar, T, Te Marvelde, J, Trinquand, A, Asnafi, V, Szczepanski, T, Matarraz, S, Lopez, A, Vidriales, B, Bulsa, J, Hrusak, O, Kalina, T, Lecrevisse, Q, Martin Ayuso, M, Bruggemann, M, Verde, J, Fernandez, P, Burgos, L, Paiva, B, Pedreira, C, Van Dongen, J, Orfao, A, and Van Der Velden, V

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.

Published
2018

12. Bone marrow immunophenotyping by flow cytometry in refractory cytopenia of childhood

Author

Aalbers, A. M., Van Den Heuvel-Eibrink, M. M., Baumann, I., Dworzak, M., Hasle, H., Locatelli, Franco, De Moerloose, B., Schmugge, M., Mejstrikova, E., Novakova, M., Zecca, M., Michel Zwaan, C., Te Marvelde, J. G., Langerak, A. W., Van Dongen, J. J., Pieters, R., Niemeyer, C. M., Van Der Velden, V. H., Locatelli F. (ORCID:0000-0002-7976-3654), Aalbers, A. M., Van Den Heuvel-Eibrink, M. M., Baumann, I., Dworzak, M., Hasle, H., Locatelli, Franco, De Moerloose, B., Schmugge, M., Mejstrikova, E., Novakova, M., Zecca, M., Michel Zwaan, C., Te Marvelde, J. G., Langerak, A. W., Van Dongen, J. J., Pieters, R., Niemeyer, C. M., Van Der Velden, V. H., and Locatelli F. (ORCID:0000-0002-7976-3654)

Abstract

Refractory cytopenia of childhood is the most common type of childhood myelodysplastic syndrome. Because the majority of children with refractory cytopenia have a normal karyotype and a hypocellular bone marrow, differentiating refractory cytopenia from the immune-mediated bone marrow failure syndrome (very) severe aplastic anemia can be challenging. Flow cytometric immunophenotyping of bone marrow has been shown to be a valuable diagnostic tool in differentiating myelodysplastic syndrome from non-clonal cytopenias in adults. Here, we performed the first comprehensive flow cytometric analysis of immature myeloid, lymphoid cells and erythroid cells, and granulocytes, monocytes, and lymphoid cells in bone marrow obtained from a large prospective cohort of 81 children with refractory cytopenia. Children with refractory cyotopenia had a strongly reduced myeloid compartment, but not as severe as children with aplastic anemia. Furthermore, the number of flow cytometric abnormalities was significantly higher in children with refractory cytopenia than in healthy controls and in children with aplastic anemia, but lower than in advanced myelodysplastic syndrome. We conclude that flow cytometric immunophenotyping could be a relevant addition to histopathology in the diagnosis of refractory cytopenia of childhood. (The multi-center studies EWOG-MDS RC06 and EWOG-MDS 2006 are registered at clinicaltrials.gov identifiers 00499070 and00662090, respectively).

Published
2015

13. Bone marrow immunophenotyping by flow cytometry in refractory cytopenia of childhood

Author

Aalbers, A. M., primary, van den Heuvel-Eibrink, M. M., additional, Baumann, I., additional, Dworzak, M., additional, Hasle, H., additional, Locatelli, F., additional, De Moerloose, B., additional, Schmugge, M., additional, Mejstrikova, E., additional, Novakova, M., additional, Zecca, M., additional, Zwaan, C. M., additional, te Marvelde, J. G., additional, Langerak, A. W., additional, van Dongen, J. J. M., additional, Pieters, R., additional, Niemeyer, C. M., additional, and van der Velden, V. H. J., additional

Published
2014
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14. Defining consensus leukemia-associated immunophenotypes for detection of minimal residual disease in acute myeloid leukemia in a multicenter setting

Author

Feller, N, primary, van der Velden, V H J, additional, Brooimans, R A, additional, Boeckx, N, additional, Preijers, F, additional, Kelder, A, additional, de Greef, I, additional, Westra, G, additional, te Marvelde, J G, additional, Aerts, P, additional, Wind, H, additional, Leenders, M, additional, Gratama, J W, additional, and Schuurhuis, G J, additional

Published
2013
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15. Standardization of flow cytometry in myelodysplastic syndromes: report from the first European LeukemiaNet working conference on flow cytometry in myelodysplastic syndromes

Author

van de Loosdrecht, A. A., primary, Alhan, C., additional, Bene, M. C., additional, Della Porta, M. G., additional, Drager, A. M., additional, Feuillard, J., additional, Font, P., additional, Germing, U., additional, Haase, D., additional, Homburg, C. H., additional, Ireland, R., additional, Jansen, J. H., additional, Kern, W., additional, Malcovati, L., additional, te Marvelde, J. G., additional, Mufti, G. J., additional, Ogata, K., additional, Orfao, A., additional, Ossenkoppele, G. J., additional, Porwit, A., additional, Preijers, F. W., additional, Richards, S. J., additional, Schuurhuis, G. J., additional, Subira, D., additional, Valent, P., additional, van der Velden, V. H.J., additional, Vyas, P., additional, Westra, A. H., additional, de Witte, T. M., additional, Wells, D. A., additional, Loken, M. R., additional, and Westers, T. M., additional

Published
2009
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16. Flow cytometric detection of intracellular antigens for immunophenotyping of normal and malignant leukocytes: testing of a new fixation-permeabilization solution.

Author

Van Lochem, E G, Groeneveld, K, Marvelde, JG Te, Van den Beemd, M W M, Hooijkaas, H, Van Dongen, J J M, Te Marvelde, J G, Van den Beemd, M W, and Van Dongen, J J

Subjects
FLOW cytometry, ANTIGENS, IMMUNOPHENOTYPING, LEUKEMIA, LYMPHOMAS, ANTIGEN analysis, LEUCOCYTES
Abstract

Analyzes commercially available fixation and permeabilization solutions for the flow cytometric detection of intracellular antigens. Methods to detect flow cytometry of intracellular antigens; Flow cytometric analysis of terminal deoxynucleotidyl transferase; Importance of flow cytometric detection of intracellular antigens for immunophenotyping of leukemia and lymphomas.

Published
1997
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17. Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study

Author

Ludovic Lhermitte, Sylvain Barreau, Daniela Morf, Paula Fernandez, Georgiana Grigore, Susana Barrena, Maaike de Bie, Juan Flores-Montero, Monika Brüggemann, Ester Mejstrikova, Stefan Nierkens, Leire Burgos, Joana Caetano, Giuseppe Gaipa, Chiara Buracchi, Elaine Sobral da Costa, Lukasz Sedek, Tomasz Szczepański, Carmen-Mariana Aanei, Alita van der Sluijs-Gelling, Alejandro Hernández Delgado, Rafael Fluxa, Quentin Lecrevisse, Carlos E. Pedreira, Jacques J.M. van Dongen, Alberto Orfao, Vincent H.J. van der Velden, J. J.M. van Dongen, W.M. Bitter, B.R. Lubbers, C.I. Teodosio, M. Zlei, A.J. van der Sluijs-Gelling, F. de Bie, S. de Bruin-Versteeg, M. van der Burg, M.W. Schilham, V. H.J. van der Velden, A.W. Langerak, J. te Marvelde, A.E. Bras, J. Schilperoord-Vermeulen, R. Jugooa, K.C. Heezen, A. Orfao, J. Almeida, M.B. Vidriales, J. Flores-Montero, M. Pérez-Andrés, S. Matarraz, L. Martín, Q. Lecrevisse, J.J. Pérez-Morán, N. Puig, A. Medina Almeida, M. Gomes da Silva, T. Faria, M. Brüggemann, M. Ritgen, M. Szczepanowski, S. Kohlscheen, A. Laqua, E. Harbst, J. Finke, V. Asnafi, L. Lhermitte, E. Duroyon, J. Trka, O. Hrusak, T. Kalina, E. Mejstrikova, M. Novakova, D. Thurner, V. Kanderova, T. Szczepanski, L. Sędek, J. Bulsa, L. Slota, J. Kulis, C.E. Pedreira, E. Sobral da Costa, S. Nierkens, A. de Jong, A. de Koning, M. Lima, A.H. Santos, S. Böttcher, S. Lange, R. Engelmann, D. Paape, C. Machka, G. Gaipa, C. Burracchi, C. Bugarin, E. Lopez-Granados, L. del Pino Molina, L. Campos-Guyotat, C. Aanei, J. F. San Miguel, B. Paiva, L. Burgos, N. Villamor-Casas, L. Magnano, J. Philippé, C. Bonroy, B. Denys, A. Willems, P. Breughe, J. de Wolf, A.E. Sousa, S.L. Silva, P. Fernandez, D. Morf, European Commission, Instituto de Salud Carlos III, Ministerio de Economía y Competitividad (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Silesian University of Technology, Lhermitte, L, Barreau, S, Morf, D, Fernandez, P, Grigore, G, Barrena, S, de Bie, M, Flores-Montero, J, Bruggemann, M, Mejstrikova, E, Nierkens, S, Burgos, L, Caetano, J, Gaipa, G, Buracchi, C, da Costa, E, Sedek, L, Szczepanski, T, Aanei, C, van der Sluijs-Gelling, A, Delgado, A, Fluxa, R, Lecrevisse, Q, Pedreira, C, van Dongen, J, Orfao, A, van der Velden, V, Bitter, W, Lubbers, B, Teodosio, C, Zlei, M, de Bie, F, de Bruin-Versteeg, S, van der Burg, M, Schilham, M, Langerak, A, te Marvelde, J, Bras, A, Schilperoord-Vermeulen, J, Jugooa, R, Heezen, K, Almeida, J, Vidriales, M, Perez-Andres, M, Matarraz, S, Martin, L, Perez-Moran, J, Puig, N, Almeida, A, Gomes da Silva, M, Faria, T, Ritgen, M, Szczepanowski, M, Kohlscheen, S, Laqua, A, Harbst, E, Finke, J, Asnafi, V, Duroyon, E, Trka, J, Hrusak, O, Kalina, T, Novakova, M, Thurner, D, Kanderova, V, Bulsa, J, Slota, L, Kulis, J, de Jong, A, de Koning, A, Lima, M, Santos, A, Bottcher, S, Lange, S, Engelmann, R, Paape, D, Machka, C, Burracchi, C, Bugarin, C, Lopez-Granados, E, del Pino Molina, L, Campos-Guyotat, L, Miguel, J, Paiva, B, Villamor-Casas, N, Magnano, L, Philippe, J, Bonroy, C, Denys, B, Willems, A, Breughe, P, de Wolf, J, Sousa, A, Silva, S, and Immunology

Subjects
0301 basic medicine, Pathology, medicine.medical_specialty, Standardization, Computer science, Leukaemia, Laboratory techniques and procedures, Article, Immunophenotyping, Pathology and Forensic Medicine, 03 medical and health sciences, 0302 clinical medicine, EuroFlow, Leukocytes, medicine, Humans, Leukaemia, Flow cytometry, Future, Acute leukemia, Orientation (computer vision), business.industry, Laboratory techniques and procedures, Pattern recognition, Flow Cytometry, Peripheral blood, Leukemia, Myeloid, Acute, Identification (information), 030104 developmental biology, Área de Biomedicina, T cell subset, Artificial intelligence, business, Algorithms, 030215 immunology
Abstract

© The Author(s) 2020., 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 ( 0.95 for all cell types in PB and r2 > 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). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a “sample-in and result-out” approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures., The EuroFlow Consortium received support from the FP6- 2004-LIFESCIHEALTH-5 program of the European Commission (grant LSHB-CT-2006-018708) as Specific Targeted Research Project (STREP). The Prague team received support from the grant number NV18-03-00343. The Salamanca team received support from the Instituto de Salud Carlos III (ISCIII) (PI16/00787-FEDER) and from Agencia Estatal de Investigación (RTC-2016-4865-1-FEDER), Ministerio de Economía y Competitividad, Madrid, Spain. AHD is supported from the program DI-17-09591 from Agencia Estatal de Investigación, Ministerio de Ciencia, Innovación y Universidades, Madrid, Spain. SB is supported from the program PTQ16-08364 from Agencia Estatal de Investigación, Ministerio de Ciencia, Innovación y Universidades, Madrid, Spain. Medical University of Silesia in Katowice team was supported by the Strategmed III PersonALL grant [No. 304586/5/NCBR/2017] from the Polish National Center of Research and Development. 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).

Published
2021

18. Standardized flow cytometry for highly sensitive MRD measurements in B-cell acute lymphoblastic leukemia

Author

Prisca M J Theunissen, Edwin Sonneveld, Lukasz Sedek, Giuseppe Gaipa, Ludovic Lhermitte, Monika Brüggemann, Elaine Sobral da Costa, Vincent H.J. van der Velden, Alberto Orfao, Ester Mejstrikova, Jan Trka, Alita J. van der Sluijs-Gelling, Quentin Lecrevisse, Georgiana Grigore, Jeroen G. te Marvelde, Paola Bonaccorso, Tomasz Szczepański, Eva Froňková, Chiara Buracchi, Marius Bartels, Ondrej Hrusak, Michaela Novakova, Elen Oliveira, Michaela Kotrova, Jacques J.M. van Dongen, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), Ministerio de Educación, Cultura y Deporte (España), Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, European Commission, Ministry of Health of the Czech Republic, Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil), Czech Science Foundation, Immunology, Theunissen, P, Mejstrikova, E, Sedek, L, Van Der Sluijs-Gelling, A, Gaipa, G, Bartels, M, Sobral da Costa, E, Kotrova, M, Novakova, M, Sonneveld, E, Buracchi, C, Bonaccorso, P, Oliveira, E, Te Marvelde, J, Szczepanski, T, Lhermitte, L, Hrusak, O, Lecrevisse, Q, Grigore, G, Fronkova, E, Trka, J, Bruggemann, M, Orfao, A, Van Dongen, J, and Van Der Velden, V

Subjects
Adult, Male, Pathology, medicine.medical_specialty, Neoplasm, Residual, Adolescent, Immunology, MRD, flow cytometry, B-cell acute lymphoblastic leukemia, Receptors, Antigen, B-Cell, Biology, Real-Time Polymerase Chain Reaction, Sensitivity and Specificity, Biochemistry, Flow cytometry, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Antigen, EuroFlow, Precursor B-Cell Lymphoblastic Leukemia-Lymphoma, Acute lymphocytic leukemia, medicine, Humans, Child, Aged, Gene Rearrangement, medicine.diagnostic_test, Infant, Newborn, Infant, Cell Biology, Hematology, Gene rearrangement, Middle Aged, Flow Cytometry, medicine.disease, Minimal residual disease, medicine.anatomical_structure, Child, Preschool, 030220 oncology & carcinogenesis, biology.protein, Female, Bone marrow, Antibody, 030215 immunology
Abstract

A fully-standardized EuroFlow 8–color antibody panel and laboratory procedure was stepwise designed to measure minimal residual disease (MRD) in B-cell precursor (BCP) acute lymphoblastic leukemia (ALL) patients with a sensitivity of £10, comparable to real-time quantitative polymerase chain reaction (RQ-PCR)–based MRD detection via antigen-receptor rearrangements. Leukocyte markers and the corresponding antibodies and fluorochromes were selected based on their contribution in separating BCP-ALL cells from normal/regenerating BCP cells in multidimensional principal component analyses. After 5 multicenter design-test-evaluate-redesign phases with a total of 319 BCP-ALL patients at diagnosis, two 8-color antibody tubes were selected, which allowed separation between normal and malignant BCP cells in 99% of studied patients. These 2 tubes were tested with a new erythrocyte bulk-lysis protocol allowing acquisition of high cell numbers in 377 bone marrow follow-up samples of 178 BCP-ALL patients. Comparison with RQ-PCR–based MRD data showed a clear positive relation between the percentage concordant cases and the number of cells acquired. For those samples with >4 million cells acquired, concordant results were obtained in 93% of samples. Most discordances were clarified upon high-throughput sequencing of antigen-receptor rearrangements and blind multicenter reanalysis of flow cytometric data, resulting in an unprecedented concordance of 98% (97% for samples with MRD < 0.01%). In conclusion, the fully standardized EuroFlow BCP-ALL MRD strategy is applicable in >98% of patients with sensitivities at least similar to RQ-PCR (£10), if sufficient cells (>4 3 10, preferably more) are evaluated., E.F. was supported by the Grant Agency of the Czech Republic (project of Centre of Excellence No. P302/12/G101). L.S., T.S., and P.T. were supported by European Research Area Network (ERA-NET) PrioMedChild, grant 40-41800-98-027. E.M. was supported by Ministry of Health of the Czech Republic, grant 15-28525A. M.K. was supported by the University Hospital Motol, Prague, Czech Republic (00064203). E.S.d.C., Q.L., and A.O. acknowledge the Bilateral Cooperation Program between Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasília, Brazil) and Dirección General de Políticas Universitárias–Ministério de Educación, Cultura y Deportes (Madrid, Spain) (311/15). E.S.d.C. acknowledges Research Foundation of the State of Rio de Janeiro, Rio de Janeiro, Brazil (E26/110.105/2014, E26/102.191/2013) and Conselho Nacional de Desenvolvimento Científico e Tecnológico–CNPQ of Brazil (400194/2014-7). G.G., C.B., and P.B. were supported by Fondazione Tettamanti.

Published
2017
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19. Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia

Author

Lhermitte, L., Mejstrikova, E., Sluijs-Gelling, A.J. van der, Grigore, G.E., Sedek, L., Bras, A.E., Gaipa, G., Costa, E.S. da, Novakova, M., Sonneveld, E., Buracchi, C., Bacelar, T.D., Marvelde, J.G.T., Trinquand, A., Asnafi, V., Szczepanski, T., Matarraz, S., Lopez, A., Vidriales, B., Bulsa, J., Hrusak, O., Kalina, T., Lecrevisse, Q., Ayuso, M.M., Bruggemann, M., Verde, J., Fernandez, P., Burgos, L., Paiva, B., Pedreira, C.E., Dongen, J.J.M. van, Orfao, A., Velden, V.H.J. van der, EuroFlow Consortium, Instituto de Salud Carlos III, Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil), Ministerio de Sanidad y Consumo (España), Polish Academy of Sciences, Fundações de Amparo à Pesquisa (Brasil), Ministerio de Economía y Competitividad (España), Immunology, Lhermitte, L, Mejstrikova, E, Van Der Sluijs-Gelling, A, Grigore, G, Sedek, L, Bras, A, Gaipa, G, Sobral Da Costa, E, Novakova, M, Sonneveld, E, Buracchi, C, De Sa Bacelar, T, Te Marvelde, J, Trinquand, A, Asnafi, V, Szczepanski, T, Matarraz, S, Lopez, A, Vidriales, B, Bulsa, J, Hrusak, O, Kalina, T, Lecrevisse, Q, Martin Ayuso, M, Bruggemann, M, Verde, J, Fernandez, P, Burgos, L, Paiva, B, Pedreira, C, Van Dongen, J, Orfao, A, and Van Der Velden, V

Subjects
Adult, Male, 0301 basic medicine, Cancer Research, Myeloid, Adolescent, T-cell acute lymphoblastic leukemia (T-ALL), Immunophenotyping, Young Adult, 03 medical and health sciences, Text mining, Acute leukemia (AL), EuroFlow, medicine, Humans, AL orientation tube (ALOT), Child, Aged, Aged, 80 and over, Acute leukemia, Leukemia, business.industry, Orientation (computer vision), Infant, Newborn, Infant, Myeloid leukemia, Pattern recognition, Hematology, Middle Aged, Precursor Cell Lymphoblastic Leukemia-Lymphoma, medicine.disease, Leukemia, Myeloid, Acute, Statistical classification, 030104 developmental biology, medicine.anatomical_structure, Oncology, Child, Preschool, Acute Disease, B-cell precursor (BCP), Female, Original Article, Artificial intelligence, business
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., The research was performed within the EuroFlow Consortium, which started with an EU-FP6 grant (LSHB-CT-2006-018708) and obtained sustainability by protecting and licensing intellectual property, thereby obtaining royalties, which are exclusively being used for supporting the EuroFlow research program (chairmen: JJMvD and AO). LS, JB and TS were supported by STRATEGMED3/304586/5/NCBR/2017 PersonALL grant of the Polish National Center for Research and Development. ESC acknowledges FAPERJ, Rio de Janeiro, Brazil (E26/110.105/2014; E26/102.191/2013) and Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPQ of Brazil (400194/2014-7). AO, SM and AL acknowledge the Instituto de Salud Carlos III (MINECO, Madrid, Spain) for the DTS15/00119, and CIBERONC-FEDER-CB16/12/00400 grants. EM, OH, TK and MN were supported by Ministry of Health grant number 15-28525A and NPU LO1604. The research for this manuscript was in part performed within the framework of the Erasmus Postgraduate School Molecular Medicine.

Published
2018

20. Impact of Pre-Analytical and Analytical Variables Associated with Sample Preparation on Flow Cytometric Stainings Obtained with EuroFlow Panels.

Author

Sędek Ł, Flores-Montero J, van der Sluijs A, Kulis J, Te Marvelde J, Philippé J, Böttcher S, Bitter M, Caetano J, van der Velden VHJ, Sonneveld E, Buracchi C, Santos AH, Lima M, Szczepański T, van Dongen JJM, and Orfao A

Abstract

Objective interpretation of FC results may still be hampered by limited technical standardization. The EuroFlow consortium conducted a series of experiments to determine the impact of different variables on the relative distribution and the median fluorescence intensity (MFI) of markers stained on different cell populations, from both healthy donors and patients' samples with distinct hematological malignancies. The use of different anticoagulants; the time interval between sample collection, preparation, and acquisition; pH of washing buffers; and the use of cell surface membrane-only (SM) vs. cell surface plus intracytoplasmic (SM+CY) staining protocols, were evaluated. Our results showed that only monocytes were represented at higher percentages in EDTA- vs. heparin-anticoagulated samples. Application of SM or SM+CY protocols resulted in slight differences in the percentage of neutrophils and debris determined only with particular antibody combinations. In turn, storage of samples for 24 h at RT was associated with greater percentage of debris and cell doublets when the plasma cell disorder panel was used. Furthermore, 24 h storage of stained cells at RT was selectively detrimental for MFI levels of CD19 and CD45 on mature B- and T-cells (but not on leukemic blasts, clonal B- and plasma cells, neutrophils, and NK cells). The obtained results showed that the variables evaluated might need to be tailored for sample and cell type(s) as well as to the specific markers compared; however, defining of well-balanced boundaries for storage time, staining-to-acquisition delay, and pH of washing buffer would be a valid recommendation for most applications and circumstances described herein.

Published
2022
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21. B-Cell Regeneration Profile and Minimal Residual Disease Status in Bone Marrow of Treated Multiple Myeloma Patients.

Author

Mendonça de Pontes R, Flores-Montero J, Sanoja-Flores L, Puig N, Pessoa de Magalhães RJ, Corral-Mateos A, Salgado AB, García-Sánchez O, Pérez-Morán J, Mateos MV, Burgos L, Paiva B, Te Marvelde J, van der Velden VHJ, Aguilar C, Bárez A, García-Mateo A, Labrador J, Leoz P, Aguilera-Sanz C, Durie B, van Dongen JJM, Maiolino A, Sobral da Costa E, and Orfao A

Abstract

B-cell regeneration during therapy has been considered as a strong prognostic factor in multiple myeloma (MM). However, the effects of therapy and hemodilution in bone marrow (BM) B-cell recovery have not been systematically evaluated during follow-up. MM (n = 177) and adult (≥50y) healthy donor (HD; n = 14) BM samples were studied by next-generation flow (NGF) to simultaneously assess measurable residual disease (MRD) and residual normal B-cell populations. BM hemodilution was detected in 41 out of 177 (23%) patient samples, leading to lower total B-cell, B-cell precursor (BCP) and normal plasma cell (nPC) counts. Among MM BM, decreased percentages (vs. HD) of BCP, transitional/naïve B-cell (TBC/NBC) and nPC populations were observed at diagnosis. BM BCP increased after induction therapy, whereas TBC/NBC counts remained abnormally low. At day+100 postautologous stem cell transplantation, a greater increase in BCP with recovered TBC/NBC cell numbers but persistently low memory B-cell and nPC counts were found. At the end of therapy, complete response (CR) BM samples showed higher CD19 - nPC counts vs. non-CR specimens. MRD positivity was associated with higher BCP and nPC percentages. Hemodilution showed a negative impact on BM B-cell distribution. Different BM B-cell regeneration profiles are present in MM at diagnosis and after therapy with no significant association with patient outcome.

Published
2021
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22. Standardization of flow cytometric minimal residual disease assessment in international clinical trials - a feasibility study from the European Myeloma Network.

Author

Hofste op Bruinink D, Oliva S, Rihova L, Schmitz A, Gilestro M, Te Marvelde J, Kralova R, Høholt H, Broijl A, Johnsen HE, Hajek R, Boccadoro M, Sonneveld P, Omedè P, and Van der Velden VHJ

Subjects
Feasibility Studies, Flow Cytometry, Humans, Neoplasm, Residual, Reference Standards, Multiple Myeloma diagnosis, Multiple Myeloma therapy
Published
2020
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23. Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia.

Author

Lhermitte L, Mejstrikova E, van der Sluijs-Gelling AJ, Grigore GE, Sedek L, Bras AE, Gaipa G, Sobral da Costa E, Novakova M, Sonneveld E, Buracchi C, de Sá Bacelar T, Te Marvelde JG, Trinquand A, Asnafi V, Szczepanski T, Matarraz S, Lopez A, Vidriales B, Bulsa J, Hrusak O, Kalina T, Lecrevisse Q, Martin Ayuso M, Brüggemann M, Verde J, Fernandez P, Burgos L, Paiva B, Pedreira CE, van Dongen JJM, Orfao A, and van der Velden VHJ

Subjects
Acute Disease, Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Humans, Immunophenotyping methods, Infant, Infant, Newborn, Male, Middle Aged, Precursor Cell Lymphoblastic Leukemia-Lymphoma pathology, Young Adult, Leukemia, Myeloid, Acute pathology
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.

Published
2018
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24. Targeting of the CD33-calicheamicin immunoconjugate Mylotarg (CMA-676) in acute myeloid leukemia: in vivo and in vitro saturation and internalization by leukemic and normal myeloid cells.

Author

van Der Velden VH, te Marvelde JG, Hoogeveen PG, Bernstein ID, Houtsmuller AB, Berger MS, and van Dongen JJ

Subjects
Adult, Aminoglycosides, Anti-Bacterial Agents metabolism, Anti-Bacterial Agents therapeutic use, Antibodies, Monoclonal metabolism, Antibodies, Monoclonal therapeutic use, Antigens, CD metabolism, Antigens, Differentiation, Myelomonocytic metabolism, Antineoplastic Agents metabolism, Antineoplastic Agents therapeutic use, Apoptosis drug effects, Granulocytes metabolism, HL-60 Cells, Humans, Kinetics, Microscopy, Confocal, Monocytes metabolism, Recurrence, Sialic Acid Binding Ig-like Lectin 3, Tumor Cells, Cultured, Anti-Bacterial Agents pharmacokinetics, Antibodies, Monoclonal pharmacokinetics, Antineoplastic Agents pharmacokinetics, Leukemia, Myeloid, Acute drug therapy
Abstract

Antibody-targeted chemotherapy is a promising therapy in patients with acute myeloid leukemia (AML). In a phase II study of Mylotarg (CMA-676, gemtuzumab ozogamicin), which consists of a CD33 antibody linked to calicheamicin, saturation and internalization by leukemic and normal myeloid cells were analyzed in 122 patients with relapsed AML. Peripheral blood samples were obtained just before and 3 and 6 hours after the start of the first and second Mylotarg treatment cycles. Within 3 to 6 hours after infusion, near complete saturation of CD33 antigenic sites by Mylotarg was reached for AML blasts, monocytes, and granulocytes, whereas Mylotarg did not bind to lymphocytes. Saturation levels prior to the start of the second Mylotarg treatment cycle were significantly increased compared with background levels before the start of the first cycle. This apparently was caused by remaining circulating Mylotarg from the first treatment cycle (approximately 2 weeks earlier). On binding of Mylotarg to the CD33 antigen, Mylotarg was rapidly internalized, as determined by the decrease in maximal surface membrane Mylotarg binding. Internalization of Mylotarg was also demonstrated in myeloid cells in vitro and was confirmed by confocal laser microscopy. In vitro studies using pulse labeling with Mylotarg showed a continuous renewed membrane expression of CD33 antigens, which can significantly increase the internalization process and thereby the intracellular accumulation of the drug. Finally, Mylotarg induced dose-dependent apoptosis in myeloid cells in vitro. These data indicate that Mylotarg is rapidly and specifically targeted to CD33(+) cells, followed by internalization and subsequent induction of cell death.

Published
2001
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