From big flow cytometry datasets to smart diagnostic strategies: The EuroFlow approach.

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.

Automated pattern-guided principal component analysis vs expert-based immunophenotypic classification of B-cell chronic lymphoproliferative disorders: a step forward in the standardization of clinical immunophenotyping.

Immunophenotypic characterization of B-cell chronic lymphoproliferative disorders (B-CLPD) is becoming increasingly complex due to usage of progressively larger panels of reagents and a high number of World Health Organization (WHO) entities. Typically, data analysis is performed separately for each stained aliquot of a sample; subsequently, an expert interprets the overall immunophenotypic profile (IP) of neoplastic B-cells and assigns it to specific diagnostic categories. We constructed a principal component analysis (PCA)-based tool to guide immunophenotypic classification of B-CLPD. Three reference groups of immunophenotypic data files-B-cell chronic lymphocytic leukemias (B-CLL; n = 10), mantle cell (MCL; n = 10) and follicular lymphomas (FL; n = 10)--were built. Subsequently, each of the 175 cases studied was evaluated and assigned to either one of the three reference groups or to none of them (other B-CLPD). Most cases (89%) were correctly assigned to their corresponding WHO diagnostic group with overall positive and negative predictive values of 89 and 96%, respectively. The efficiency of the PCA-based approach was particularly high among typical B-CLL, MCL and FL vs other B-CLPD cases. In summary, PCA-guided immunophenotypic classification of B-CLPD is a promising tool for standardized interpretation of tumor IP, their classification into well-defined entities and comprehensive evaluation of antibody panels.

A probabilistic approach for the evaluation of minimal residual disease by multiparameter flow cytometry in leukemic B-cell chronic lymphoproliferative disorders.

Multiparameter flow cytometry has become an essential tool for monitoring response to therapy in hematological malignancies, including B-cell chronic lymphoproliferative disorders (B-CLPD). However, depending on the expertise of the operator minimal residual disease (MRD) can be misidentified, given that data analysis is based on the definition of expert-based bidimensional plots, where an operator selects the subpopulations of interest. Here, we propose and evaluate a probabilistic approach based on pattern classification tools and the Bayes theorem, for automated analysis of flow cytometry data from a group of 50 B-CLPD versus normal peripheral blood B-cells under MRD conditions, with the aim of reducing operator-associated subjectivity. The proposed approach provided a tool for MRD detection in B-CLPD by flow cytometry with a sensitivity of < or =8 x 10(-5) (median of < or =2 x 10(-7)). Furthermore, in 86% of B-CLPD cases tested, no events corresponding to normal B-cells were wrongly identified as belonging to the neoplastic B-cell population at a level of < or =10(-7). Thus, this approach based on the search for minimal numbers of neoplastic B-cells similar to those detected at diagnosis could potentially be applied with both a high sensitivity and specificity to investigate for the presence of MRD in virtually all B-CLPD. Further studies evaluating its efficiency in larger series of patients, where reactive conditions and non-neoplastic disorders are also included, are required to confirm these results.

Immunophenotyping of blood lymphocytes in childhood. Reference values for lymphocyte subpopulations.

OBJECTIVE: Immunophenotyping of blood lymphocytes is an important tool in the diagnosis of hematologic and immunologic disorders. Because of maturation and expansion of the immune system in the first years of life, the relative and the absolute size of lymphocyte subpopulations vary during childhood. Therefore we wished to obtain reference values for the relative and the absolute size of all relevant blood lymphocyte subpopulations in childhood. STUDY DESIGN: We used the lysed whole blood method for analysis of lymphocyte subpopulations in 429 blood samples from neonates (n = 20), healthy children (n = 358), and adults (n = 51). The following age groups were used: 1 week to 2 months (n = 13), 2 to 5 months (n = 46), 5 to 9 months (n = 105), 9 to 15 months (n = 70), 15 to 24 months (n = 33), 2 to 5 years (n = 33), 5 to 10 years (n = 35), and 10 to 16 years (n = 23). RESULTS: Our results show that the absolute number of CD19+ B lymphocytes increases twofold immediately after birth, remains stable until 2 years of age, and subsequently gradually decreases 6.5-fold from 2 years to adult age. The CD3+ T lymphocytes increase 1.5-fold immediately after birth and decrease threefold from 2 years to adult age. The absolute size of the CD3+/CD4+ T-lymphocyte subpopulation follows the same pattern as the total CD3+ population, but the CD3+/CD8+ T lymphocytes remain stable from birth up to 2 years of age, followed by a gradual threefold decrease toward adult levels. In contrast to B and T lymphocytes, the absolute number of natural killer cells decreases almost threefold in the first 2 months of life and remains stable thereafter. Our study also showed that changes in the absolute size of lymphocyte subpopulations are not always consistent with changes in their relative size. This demonstrates that the relative counts of lymphocyte subsets do not reflect their actual size and are therefore of limited value. CONCLUSION: On the basis of this study we strongly recommend that immunophenotyping of blood lymphocytes for the diagnosis of hematologic and immunologic disorders be based on the absolute rather than on the relative size of lymphocyte subpopulations. Our data can be used as age-matched reference values for blood lymphocyte immunophenotyping.