Issue Highlights — May 2021

Abstract

This May 2021 issue of Cytometry B (Clinical Cytometry) consists of one review paper on cerebrospinal fluid (CSF) analysis by flow cytometry in hematological malignancies, together with nine manuscripts containing original research in the field of clinical cytometry, related to myeloid neoplasms e.g. myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), MDS/MPN and hypereosinophilic syndromes (HES), to the flow cytometric detection of T-cell clonality in the diagnostic work-up of mature/peripheral T cell neoplasms and two technical papers related to the diagnosis of Fanconi anemia and stabilization protocols for flow cytometric evaluation of bronchoalveolar lavage samples. Three letters to the editor and two case reports including a dendritic cell neoplasm arising in a patient also diagnosed of MDS/MPN and a transient red cell aplasia due to parvovirus B19 infection, complete the May issue of Cytometry B. Leptomeningeal involvement is a rather common finding at diagnosis and relapse in acute lymphoblastic leukemia (ALL), lymphoblastic lymphoma (LL), blastic plasmacytoid dendritic cell leukemia/lymphoma, and to a less extent also in aggressive non-Hodgkin lymphomas (NHL) including both Burkitt lymphoma and diffuse large B cell lymphoma (DLBCL including double- and triple-hit DLBCL), and acute myeloblastic leukemia (AML) (Lenk et al., 2020; Martin-Martin et al., 2016; Wilson et al., 2014; Döhner et al., 2017). Because of this, diagnostic algorithms and follow-up algorithms have been established and adopted (even worldwide) for systematic vs selective search for leukemia cells in cerebrospinal fluid of ALL/LL and aggressive NHL, in parallel to administration of central nervous system (CNS) prophylaxis, followed by intrathecal therapy in infiltrated cases (Lenk et al., 2020; Peñalver et al., 2017). Despite cytomorphology remains the gold standard for detection of leukemia/lymphoma cells in CSF, in the last decades flow cytometry has proven to be a well-suited complementary approach due to its higher sensitivity and specificity (Wilson et al., 2014; Shalabi et al., 2020; Jaime-Perez et al., 2018; Hedge et al., 2005; Quijano et al., 2009). However, compared to blood and bone marrow aspirated samples, CSF samples display unique features that require special attention and dedicated protocols (Greig et al., 2014; Kraan et al., 2008; van Dongen et al. 2012). Thus, CSF is a paucicellular fluid where cells have an extremely low viability, leading to a significantly shortened half-life vs blood (Quijano et al., 2009; Greig et al., 2014; de Graaf et al., 2011). Therefore, validated antibody panels in combination with standard operating procedures have been proposed for the diagnostic screen of leptomeningeal involvement in CSF, both for ALL/LL and aggressive NHL (e.g. Burkitt lymphoma and diffuse large B-cell lymphoma) (Peñalver et al., 2017; Kraan et al., 2008; van Dongen et al., 2012). In this May issue of Cytometry B Del Principe et al. (2021) provide a comprehensive review of the role of flow cytometry in the diagnosis of CSF involvement in hematological malignancies, paying special attention to open issues related to the low sample cellularity, pre-analytical procedures required to preserve cells and minimize the negative impact of low cell viability in CSF, and analytical procedures involving (i) selection of antibody combinations/panels, (ii) management of blood contamination, (iii) interpretation of flow cytometry findings and (iv) definition of thresholds for positivity. Finally, specific recommendations related to the above issues and reporting of results are also provided. Diagnosis and classification of hematologic malignancies currently relies on data provided by conventional cytomorphology and histopathology, together with data derived from immunophenotyping and genetic/molecular assays, in combination with other clinical and laboratory features of the disease (Swerdlow et al., 2017). Among several methods, flow cytometry is preferred for immunophenotyping data of acute leukemias, mature/peripheral B, T and NK leukemias and leukemic lymphomas, and other myeloid neoplasms such as MDS, MDS/MPN, MPN, mastocytosis and HES (Swerdlow et al., 2017). However, in contrast to acute leukemias (including ALL, AML and ambiguous lineage acute leukemia), chronic lymphoproliferative disorders and mastocytosis, where flow cytometry immunophenotyping plays a pivotal role in the i.e., World Health Organization (WHO) diagnosis and classification of the disease, the diagnostic utility of flow cytometry immunophenotyping in other myeloid malignancies such as MDS, MDS/MPN, MPN and HES is considered clinically less relevant (Swerdlow et al., 2017). Despite this, multiple studies have shown so far the utility of flow cytometry in the diagnostic work-up of patients suspected of suffering from MDS and MDS/MPN, as progressively recognized by the WHO (Swerdlow et al., 2017). Thus, several flow cytometry immunophenotyping-based diagnostic scores and guidelines for use of flow cytometry in MDS and MDS/MPN have been proposed (Swerdlow et al., 2017; Porwit et al., 2014; Valent et al., 2017; Westers et al., 2017a; Westers et al., 2017b; Valent et al., 2019). This contrasts with more limited data that exists on the potential diagnostic utility of immunophenotyping in MPN, HES, or the altered proliferation profiles in these and other, myeloid neoplasms (Shameli et al., 2020; Ouyang et al., 2015; Herborg et al., 2018; Matarraz et al., 2012; Matarraz et al., 2011). In this issue of Cytometry B six original research papers and a case report have used flow cytometry to study MDS, MDS/MPN, MPN and HES (Shestakova et al., 2021; Davydova et al., 2021; Mestrum et al., 2021; Panda et al., 2021; Vijayasekharan et al., 2021; Hu et al., 2021; Espasa et al., 2021). In the first of these six papers, Shestakova et al. (2021) explored the utility of automated leucocyte parameters including cell volume, conductivity and light scatter properties (VCS parameters) as assessed in an automated hematological analyzer, as a read-out for dysplastic MDS-associated features. Results showed overall altered (lower and more heterogeneous) light scatter features of neutrophils in MDS (compared to controls); of note such alterations were more prominent in high-risk vs low-risk cases(Shestakova et al., 2021). In the second manuscript, Davydova et al. (2021) investigated the diagnostic performance for MDS of three previously proposed flow cytometry scores (i.e., the Ogata et al score (Ogata et al., 2006), the Wells et al risk model (Chu et al., 2011) and the integrated flow cytometry score(Della Porta et al., 2012)) based on a series of 102 MDS and 83 reactive cytopenic patients, in addition to 35 healthy donors studied with a 6-color antibody panel. Despite all three score models contributed to the diagnosis of MDS, the integrated flow cytometry score emerged as the model associated with the highest accuracy with both a sensitivity and specificity of >87% (Davydova et al., 2021). The third paper focused on searching for altered proliferation profiles in different maturation-associated compartments of erythroid, myeloid and monocytic bone marrow cells from MPN, MDS and MDS/MPN patients as assessed by expression of the Ki-67 marker flow cytometry (Mestrum et al., 2021). Results showed three different profiles that discriminate the three MPN, MDS, and MDS/MPN patient groups. These consisted of increased Ki67 expression at all maturation stages of all three lineage-associated cell compartments in MPN, while a decreased expression of Ki-67 was observed in the earliest maturation stages in MDS, and an increased percentage of Ki-67+ cells restricted to the more mature cell compartments was detected in MDS/MPN cases (Mestrum et al., 2021). In the following manuscript, Panda et al. (2021) investigate mast cell differentiation of blast cells in patients with myeloid neoplasias not fulfilling diagnostic criteria for systemic mastocytosis or myelomastocytic leukemia (Swerdlow et al., 2017). Overall, 9 patients showed blasts with a CD117hi CD34het HLADR-/lo CD203c+ immature mast cell-associated immunophenotype, supporting the potential existence a small percentage of underdiagnosed myelomastocytic leukemia cases; diagnosis of these nine patients corresponded to CML at any phase of the disease (n=4), to newly diagnosed and secondary AML (n=4) and to one chronic myelomonocytic leukemia, whose features are described in detail in the manuscript (Panda et al., 2021). In the fifth paper of this series of manuscripts on myeloid neoplasias, Vijayasekharan et al. (2021) report on a retrospective analysis of the value of identifying a population of haematopoietic precursor cells with mixed-lineage phenotype in a series of 12 pediatric patients diagnosed with chronic phase CML. Preliminary results reported for the 12 CML patients included in this study showed that among 5 cases in which precursor cells with a mixed B-myeloid (B/M or B/T/M) phenotype were detected a greater frequency (3/5 patients) of progression to acute leukemia associated with Imatinib-resistant gene mutations was observed vs. that found in cases with aberrant myeloid-only precursors (0/5 cases), suggesting immunophenotyping of pediatric CML patients during chronic phase of the disease could contribute to identify patients at higher risk of progression to acute leukemia with Imatinib-resistant mutations (2021). Finally, the sixth manuscript on myeloid neoplasms reports on flow cytometry immunophenotypic findings in seven patients diagnosed with lymphocytic variant of HES, out of a series of 136 patients referred to a single institution for the diagnostic work-up of eosinophilia (Hu et al., 2021). In this report, Hu et al. (2021) showed that flow cytometry immunophenotyping was critical (and complementary to molecular analyses) for systematic demonstration of aberrant CD3- CD7-/lo CD4+ CD5+ CD2+ CD8- T-cells associated with T cell clonality, in all seven patients. Two interesting case reports (Espasa et al., 2021; Michael et al., 2021) complete this series of manuscripts on myeloid neoplasias included in this issue of Cytometry B. In the first one a patient diagnosed with composite blastic plasmacytoid dendritic cell neoplasm and chronic myelomonocytic leukemia in whom flow cytometry immunophenotyping was key to identify which of the two compartments of CD4+ HLADR+ CD56+ leukemia cells coexisting in this patient was responsible for the patient skin lesions (CD123hi CD303+ plasmacytoid dendritic cells) vs blood/bone marrow involvement (cells with a typical monocyte phenotype), is described (Espasa et al., 2021). In the second case report, flow cytometry findings related to morphological data in a case of transient aplasia due to parvovirus B19 infection, in the absence of immunophenotypic and morphologic dysplasia, are described (Michael et al., 2021). Altogether, the results presented in this series of papers reinforce the value of flow cytometry in the diagnosis of myeloid neoplasms. Assessment of T cell clonality is a cornerstone in the diagnostic screening of T-cell neoplasms, particularly in samples where clonal mature T cells only represent a minor population (Mahe et al., 2018). For decades, assessment of T cell clonality has relied exclusively on molecular techniques (Mahe et al., 2018). However, these techniques remain labour intensive, some have limited sensitivity and they do not provide the opportunity for simultaneous demonstration of aberrant features of the T cell clones identified. Because of this, for the last 20 years flow cytometric evaluation of the T-cell receptor (TCR)Vβ repertoire based on a panel of antibodies directed against up to 24 different TCRVβ families was adopted by many centers for fast assessment of T-cell clonality in the diagnostic screening of mature/peripheral T cell neoplasms (Langerak et al., 2001; Lima et al., 2001; Tembhare et al., 2011). During this period, flow cytometric analysis of the TCRVβ repertoire in patients suspected of having a mature/peripheral T cell neoplasm has proven of great diagnostic utility in TCRαβ+ CD3+ tumors, particularly when tumor cells express an aberrant phenotype associated with a TCRVβ family represented in among the 24 investigated (Langerak et al., 2001; Lima et al., 2001; Tembhare et al., 2011). However, flow cytometric analysis of the TCRVβ repertoire is a complex, relatively low sensitive and rather expensive assay, because it requires staining for up to 24 different antibody reagents which only identify a fraction of between 50% and 80% of all T-cells, due to the lack of antibody reagents specific for several TCRVβ families not represented among the available TCRVβ reagents (Langerak et al., 2001; Lima et al., 2001; Tembhare et al., 2011; van den Beemd et al., 2000). This, together with the low frequency of mature/peripheral T cell neoplasms, compared to B-cell leukemia/lymphoma and to a less extent also myeloid malignancies (Swerdlow et al., 2017), has hampered adoption of flow cytometric analysis of the TCRVβ repertoire for the diagnostic work-up of mature/peripheral T cell neoplasms in many laboratories worldwide. Recently, antibody reagents specific for the constant region 1 of the TCRβ chain (TRβC1) have been produced (Novikov et al., 2019) which have proven to be of great potential utility for rapid flow cytometry-based assessment of T-cell clonality (Novikov et al., 2019; Shi et al., 2020; Horna, Shi, Jevremovic et al., 2021; Horna, Olteanu, Jevremovic et al., 2021; Horna, Shi, Olteanu et al., 2021), in a similar way the pattern of expression of the immunoglobulin kappa vs lambda light chains are used for detection of B cell clonality. In this issue of Cytometry B, Berg et al. (2021) confirm and extend on previous observations in blood and bone marrow samples, (Novikov et al., 2019; Shi et al., 2020; Horna, Shi, Jevremovic et al., 2021; Horna, Shi, Olteanu et al., 2021) and demonstrate further the utility of assessing TRβC1 expression in combination with a panel of other conventional T-cell associated markers to assess T cell clonality in immunophenotypically defined subsets of mature T cells in tissue biopsies and other body fluids (e.g., CSF, pleural effusions and peritoneal fluid) (Berg et al., 2021). Based on their results on a series of 46 mature/peripheral T cell neoplasms and 97 patients with no T cell malignancy, they conclude that detection of T cell clonality in phenotypically defined subsets of T cells using the single TRβC1 antibody staining in tissue biopsies and distinct body fluids is a simple, fast and robust assay, which might be ready to be incorporated in routine diagnostic flow cytometry laboratories (Berg et al., 2021). Fast and robust diagnosis of Fanconi anemia is critical for adequate patient management and to avoid disease complications due to inappropriate cytotoxic therapies (e.g. chemotherapy based on DNA interstrand crosslinking agents) administered for some manifestations of the disease (e.g. hematological malignancies) (Ebens et al., 2017). Despite this, at present, the diagnosis of Fanconi anemia still remains challenging, at least in a subset of patients, and sometimes it might be even missed, due to the great genetic and phenotypic heterogeneity of the disease, pointing out the need for new, fast, accurate and robust assays in the diagnostic work up of Fanconi anemia (Ebens et al., 2017). Here, Hammarsten and Muslimovic (2021) report on the use of a novel cell division assay to exclude the diagnosis of Fanconi anemia prior to chemotherapy, in suspicious patients. The cell division assay proposed for exclusion of Fanconi anemia (Hammarsten & Muslimovic, 2021) was initially developed by these authors for in vitro assessment of cell sensitivity to cytotoxic drugs(Mathew et al., 2016). It is based on the incorporation of 5-ethynyl-2’-deoxiuridine (EdU) in the cell DNA to detect cells that are actively diving in culture(Mathew et al., 2016). In this issue of Cytometry B, Hammarsten and Muslimovic (2021) provide preliminary data that demonstrate that the proposed cell division assay detects in vitro sensitivity of primary cells (n=3) and cell lines from Fanconi anemia patients for two different DNA interstrand crosslinking chemotherapeutic agents (i.e., mitomycin C and cyclophosphamide). These results set the basis for the potential future application of this cost-effective flow cytometric assay (Hammarsten & Muslimovic, 2021; Mathew et al., 2016) in the diagnostic screening of Fanconi anemia among patients with aplastic anemia, MDS, acute leukemia and congenital disease conditions associated with Fanconi anemia, including those in whom therapy with DNA interstrand crosslinking chemotherapeutic agents (e.g. prior to hematopoietic stem cell transplantation) are indicated. Bronchoalveolar lavage (BAL) is a common procedure in the diagnostic work-up of patients suspicious of interstitial lung disease (Gharsalli et al., 2018; Meyer et al., 2012). Diagnostic procedures in BAL samples include the assessment of cell concentration and differential counts as assessed by conventional e.g. cytomorphologic procedures, in addition to immunophenotyping (Gharsalli et al., 2018; Meyer et al., 2012). For immunophenotypic characterization of lymphocytes and other cell populations in BAL samples, flow cytometry is long established as the preferred method, its results contributing to the differential diagnosis of sarcoidosis, extrinsic allergic alveolitis or idiopathic pulmonary fibrosis (Barry et al., 2002). However, cells present in BAL samples are prone to an accelerated (<4h) deterioration. Thus, preservation of sample cellularity in BAL samples requires special attention, no standardized protocols being available in this regard. In this issue of Cytometry B, Eidhof et al. (2021) compare three different methods to stabilize BAL cells (vs native BAL cells as reference) for immediate vs delayed flow cytometry immunophenotypic analysis performed for a period of up to 28 days after sample collection. Direct comparison of a local paraformaldehyde-based stabilization protocol against two commercially available stabilization reagents (i.e., TransFix and Streck Cell Preservative) showed stable light scatter patterns, white blood cell and lymphocyte subset counts, with only minor differences among the three methods; this contrasted with rapid deterioration of cells observed in native (non-stabilized) BAL samples (Eidhof et al., 2021). Based on these results, authors provide strong evidence for the need of stabilization of BAL samples for robust flow cytometry analyses, particularly when these are performed >24h after sample collection (Eidhof et al., 2021).