Loss of hematopoietic progenitors heterogeneity is an adverse prognostic factor in lower-risk myelodysplastic neoplasms.

Myelodysplastic neoplasms (MDS) are characterized by clonal evolution starting from the compartment of hematopoietic stem and progenitors cells (HSPCs), leading in some cases to leukemic transformation. We hypothesized that deciphering the diversity of the HSPCs compartment may allow for the early detection of an emergent sub-clone that drives disease progression. Deep analysis of HSPCs repartition by multiparametric flow cytometry revealed a strong disorder of the hematopoietic branching system in most patients at diagnosis with different phenotypic signatures closely related to specific MDS features. In two independent cohorts of 131 and 584 MDS, the HSPCs heterogeneity quantified through entropy calculation was decreased in 47% and 46% of cases, reflecting a more advanced state of the disease with deeper cytopenias, higher IPSS-R risk and accumulation of somatic mutations. We demonstrated that patients with lower-risk MDS and low CD34 + CD38+HSPCs entropy had an adverse outcome and that this parameter is as an independent predictive biomarker for progression free survival, leukemia free survival and overall survival. Analysis of HSPCs repartition at diagnosis represents therefore a very powerful tool to identify lower-risk MDS patients with a worse outcome and valuable for clinical decision-making, which could be fully integrated in the MDS diagnostic workflow.

Use of a hybrid intelligence decision tree to identify mature B-cell neoplasms.

BACKGROUND: Mature B-cell neoplasms are challenging to diagnose due to their heterogeneity and overlapping clinical and biological features. In this study, we present a new workflow strategy that leverages a large amount of flow cytometry data and an artificial intelligence approach to classify these neoplasms. METHODS: By combining mathematical tools, such as classification algorithms and regression tree (CART) models, with biological expertise, we have developed a decision tree that accurately identifies mature B-cell neoplasms. This includes chronic lymphocytic leukemia (CLL), for which cytometry has been extensively used, as well as other non-CLL subtypes. RESULTS: The decision tree is easy to use and proposes a diagnosis and classification of mature B-cell neoplasms to the users. It can identify the majority of CLL cases using just three markers: CD5, CD43, and CD200. CONCLUSION: This approach has the potential to improve the accuracy and efficiency of mature B-cell neoplasm diagnosis.

Prognostic Impact of Unsupervised Early Assessment of Bulk and Leukemic Stem Cell Measurable Residual Disease in Acute Myeloid Leukemia.

PURPOSE: Acute myeloid leukemias (AML) are clonal diseases that develop from leukemic stem cells (LSC) that carry an independent prognostic impact on the initial response to induction chemotherapy, demonstrating the clinical relevance of LSC abundance in AML. In 2018, the European LeukemiaNet published recommendations for the detection of measurable residual disease (Bulk MRD) and suggested the exploration of LSC MRD and the use of multiparametric displays. EXPERIMENTAL DESIGN: We evaluated the performance of unsupervised clustering for the post-induction assessment of bulk and LSC MRD in 155 patients with AML who received intensive conventional chemotherapy treatment. RESULTS: The median overall survival (OS) for Bulk+ MRD patients was 16.7 months and was not reached for negative patients (HR, 3.82; P < 0.0001). The median OS of LSC+ MRD patients was 25.0 months and not reached for negative patients (HR, 2.84; P = 0.001). Interestingly, 1-year (y) and 3-y OS were 60% and 39% in Bulk+, 91% and 52% in Bulk-LSC+ and 92% and 88% in Bulk-LSC-. CONCLUSIONS: In this study, we confirm the prognostic impact of post-induction multiparametric flow cytometry Bulk MRD in patients with AML. Focusing on LSCs, we identified a group of patients with negative Bulk MRD but positive LSC MRD (25.8% of our cohort) with an intermediate prognosis, demonstrating the interest of MRD analysis focusing on leukemic chemoresistant subpopulations.

Phenotypically-defined stages of leukemia arrest predict main driver mutations subgroups, and outcome in acute myeloid leukemia.

Classifications of acute myeloid leukemia (AML) patients rely on morphologic, cytogenetic, and molecular features. Here we have established a novel flow cytometry-based immunophenotypic stratification showing that AML blasts are blocked at specific stages of differentiation where features of normal myelopoiesis are preserved. Six stages of leukemia differentiation-arrest categories based on CD34, CD117, CD13, CD33, MPO, and HLA-DR expression were identified in two independent cohorts of 2087 and 1209 AML patients. Hematopoietic stem cell/multipotent progenitor-like AMLs display low proliferation rate, inv(3) or RUNX1 mutations, and high leukemic stem cell frequency as well as poor outcome, whereas granulocyte-monocyte progenitor-like AMLs have CEBPA mutations, RUNX1-RUNX1T1 or CBFB-MYH11 translocations, lower leukemic stem cell frequency, higher chemosensitivity, and better outcome. NPM1 mutations correlate with most mature stages of leukemia arrest together with TET2 or IDH mutations in granulocyte progenitors-like AML or with DNMT3A mutations in monocyte progenitors-like AML. Overall, we demonstrate that AML is arrested at specific stages of myeloid differentiation (SLA classification) that significantly correlate with AML genetic lesions, clinical presentation, stem cell properties, chemosensitivity, response to therapy, and outcome.

CD158k and PD-1 expressions define heterogeneous subtypes of Sezary syndrome.

Sezary syndrome (SS) is a rare leukemic form of cutaneous T-cell lymphoma. Diagnosis mainly depends on flow cytometry, but results are not specific enough to be unequivocal. The difficulty in defining a single marker that could characterize Sezary cells may be the consequence of different pathological subtypes. In this study, we used multivariate flow cytometry analyses. We chose to investigate the expression of classical CD3, CD4, CD7, and CD26 and the new association of 2 markers CD158k and PD-1. We performed lymphocyte computational phenotypic analyses during diagnosis and follow-up of patients with SS to define new SS classes and improve the sensitivity of the diagnosis and the follow-up flow cytometry method. Three classes of SS, defined by different immunophenotypic profiles, CD158k+ SS, CD158k-PD-1+ SS, CD158k and PD-1 double-negative SS, showed different CD8+ and B-cell environments. Such a study could help to diagnose and define biological markers of susceptibility/resistance to treatment, including immunotherapy.

[Multiple myeloma immunophenotyping: method validation]. / Immunophénotypage du myélome multiple : validation de la méthode.

Flow cytometric immunophenotyping has become essential for management of multiple myeloma (assessment of clonality, prognostic information on the risk of progression in gammopathy of undetermined significance, minimal residual disease monitoring). Immunophenotyping of bone marrow plasma cells is routinely used in the haematology laboratory of the University Hospital of Toulouse. To guarantee the reliability of this technique, the laboratory decided to check this method in compliance with the NF ISO EN 15189, standard for medical laboratories requirements. As expected, the method showed good technical performances. However, this initiative has demonstrated the importance of the sample quality and of the control of the preanalytical and analytical conditions. This process led us to maximize our professional pratices.

IgG lymphoplasmacytic lymphoma: a case report.

Lymphoplasmacytic lymphoma is rare. Although most cases of LPL are Waldenström macroglobulinemia associated with an immunoglobulin M, there are exceptions. Indeed, few cases are immunoglobulin A-secreting or immunoglobulin G-secreting. These cases are poorly described and raise diagnostic difficulties. The purpose of this article is to describe an IgG lymphoplamacytic lymphoma case diagnosed recently in the hematology laboratory University Hospital of Toulouse.

Verification of a quantitative method: complete blood count by flow cytometry, the HematoFlowTM system (Beckman Coulter).

The HematoFlow™ system is used in the hematology laboratory of the University Hospital of Bordeaux since July, 2011. The HematoFlow™ solution is the combination of a sample preparator (FP1000) and a 5 color flow cytometer (FC500) linked by a middleware (Remisol™). This system is used in second line when flags are activated by the hematology instrument and/or if the sample comes from the OncoHematology Department. Improvements in hematology disease diagnosis and follow-up were possible using this system. The laboratory has now entered in an accreditation procedure and needs to check this method in compliance with the COFRAC requirements.