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1.
J Immunol Methods ; 475: 112631, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31306640

RESUMO

The rise in the analytical speed of mutiparameter flow cytometers made possible by the introduction of digital instruments, has brought up the possibility to manage progressively higher number of parameters simultaneously on significantly greater numbers of individual cells. This has led to an exponential increase in the complexity and volume of flow cytometry data generated about cells present in individual samples evaluated in a single measurement. This increase demands for new developments in flow cytometry data analysis, graphical representation, and visualization and interpretation tools to address the new big data challenges, i.e. processing data files of ≥10-25 parameters per cell in samples with >5-10 million cells (= up to 250 million data points per cell sample) obtained in a few minutes. Here, we present a comprehensive review of some of the tools developed by the EuroFlow consortium for processing flow cytometric big data files in diagnostic laboratories, particularly focused on automated EuroFlow approaches for: i) identification of all cell populations coexisting in a sample (automated gating); ii) smart classification of aberrant cell populations in routine diagnostics; iii) automated reporting; together with iv) new tools developed to visualize n-dimensional data in 2-dimensional plots to support expert-guided automated data analysis. The concept of using reference data bases implemented into software programs, in combination with multivariate statistical analysis pioneered by EuroFlow, provides an innovative, highly efficient and fast approach for diagnostic screening, classification and monitoring of patients with distinct hematological and immune disorders, as well as other diseases.


Assuntos
Big Data , Conjuntos de Dados como Assunto , Citometria de Fluxo/métodos , Imunofenotipagem/métodos , Humanos
2.
Leukemia ; 31(10): 2094-2103, 2017 10.
Artigo em Inglês | MEDLINE | ID: mdl-28104919

RESUMO

Flow cytometry has become a highly valuable method to monitor minimal residual disease (MRD) and evaluate the depth of complete response (CR) in bone marrow (BM) of multiple myeloma (MM) after therapy. However, current flow-MRD has lower sensitivity than molecular methods and lacks standardization. Here we report on a novel next generation flow (NGF) approach for highly sensitive and standardized MRD detection in MM. An optimized 2-tube 8-color antibody panel was constructed in five cycles of design-evaluation-redesign. In addition, a bulk-lysis procedure was established for acquisition of ⩾107 cells/sample, and novel software tools were constructed for automatic plasma cell gating. Multicenter evaluation of 110 follow-up BM from MM patients in very good partial response (VGPR) or CR showed a higher sensitivity for NGF-MRD vs conventional 8-color flow-MRD -MRD-positive rate of 47 vs 34% (P=0.003)-. Thus, 25% of patients classified as MRD-negative by conventional 8-color flow were MRD-positive by NGF, translating into a significantly longer progression-free survival for MRD-negative vs MRD-positive CR patients by NGF (75% progression-free survival not reached vs 7 months; P=0.02). This study establishes EuroFlow-based NGF as a highly sensitive, fully standardized approach for MRD detection in MM which overcomes the major limitations of conventional flow-MRD methods and is ready for implementation in routine diagnostics.


Assuntos
Citometria de Fluxo/métodos , Imunofenotipagem/métodos , Mieloma Múltiplo/diagnóstico , Plasmócitos/patologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Especificidade de Anticorpos , Contagem de Células , Desenho de Equipamento , Feminino , Citometria de Fluxo/instrumentação , Humanos , Imunofenotipagem/instrumentação , Masculino , Pessoa de Meia-Idade , Mieloma Múltiplo/tratamento farmacológico , Mieloma Múltiplo/patologia , Neoplasia Residual , Sensibilidade e Especificidade , Software , Manejo de Espécimes , Resultado do Tratamento
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