Response to DA-EPOCH-R is associated with activation of 'fitter' cytotoxic T-cells in patients with newly diagnosed double and triple hit high-grade B-cell lymphoma.

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T cell characteristics impact response and resistance to T cell-redirecting bispecific antibodies in multiple myeloma.

PURPOSE: Bispecific antibodies (BsAbs) directed against B-cell maturation antigen (BCMA; teclistamab) or the orphan G protein-coupled receptor GPRC5D (talquetamab) induce deep and durable responses in heavily pretreated MM patients. However, mechanisms underlying primary and acquired resistance remain poorly understood. EXPERIMENTAL DESIGN: The anti-MM activity of teclistamab and talquetamab was evaluated in bone marrow (BM) samples from MM patients. T-cell phenotype and function were assessed in BM/peripheral blood samples obtained from MM patients who were treated with these BsAbs. RESULTS: In ex vivo killing assays with 41 BM samples from BsAb-naïve MM patients, teclistamab- and talquetamab-mediated MM lysis were strongly correlated (r=0.73, P<0.0001). Both BsAbs exhibited poor activity in samples with high regulatory T-cell (Treg) numbers and a low T-cell/MM cell-ratio. Furthermore, comprehensive phenotyping of BM samples derived from patients treated with teclistamab or talquetamab, revealed that high frequencies of PD-1+ CD4+ T-cells, CTLA4+ CD4+ T-cells, and CD38+ CD4+ T-cells were associated with primary resistance. Although this lack of response was linked to modest increase in expression of inhibitory receptors, increasing T-cell/MM cell-ratios by adding extra T-cells enhanced sensitivity to BsAbs. Further, treatment with BsAbs resulted in an increased proportion of T-cells expressing exhaustion markers (PD-1, TIGIT, and TIM-3), which was accompanied by reduced T-cell proliferative potential and cytokine secretion, as well as impaired anti-tumor efficacy in ex vivo experiments. CONCLUSIONS: Primary resistance is characterized by a low T-cell/MM cell-ratio and Treg-driven immunosuppression, while reduced T-cell fitness due to continuous BsAb-mediated T-cell activation may contribute to development of acquired resistance.

Myelodysplastic neoplasms dissected into indolent, leukaemic and unfavourable subtypes by computational clustering of haematopoietic stem and progenitor cells.

Myelodysplastic neoplasms (MDS) encompass haematological malignancies, which are characterised by dysplasia, ineffective haematopoiesis and the risk of progression towards acute myeloid leukaemia (AML). Myelodysplastic neoplasms are notorious for their heterogeneity: clinical outcomes range from a near-normal life expectancy to leukaemic transformation or premature death due to cytopenia. The Molecular International Prognostic Scoring System made progress in the dissection of MDS by clinical outcomes. To contribute to the risk stratification of MDS by immunophenotypic profiles, this study performed computational clustering of flow cytometry data of CD34+ cells in 67 MDS, 67 AML patients and 49 controls. Our data revealed heterogeneity also within the MDS-derived CD34+ compartment. In MDS, maintenance of lymphoid progenitors and megakaryocytic-erythroid progenitors predicted favourable outcomes, whereas expansion of granulocyte-monocyte progenitors increased the risk of leukaemic transformation. The proliferation of haematopoietic stem cells and common myeloid progenitors with downregulated CD44 expression, suggestive of impaired haematopoietic differentiation, characterised a distinct MDS subtype with a poor overall survival. This exploratory study demonstrates the prognostic value of known and previously unexplored CD34+ populations and suggests the feasibility of dissecting MDS into a more indolent, a leukaemic and another unfavourable subtype.

Distinct peripheral T-cell and NK-cell profiles in HGBL-MYC/BCL2 vs patients with DLBCL NOS.

ABSTRACT: Patients with high-grade B-cell lymphoma with MYC and BCL2 rearrangements (HGBL-MYC/BCL2) respond poorly to immunochemotherapy compared with patients with diffuse large B-cell lymphoma not otherwise specified (DLBCL NOS) without a MYC rearrangement. This suggests a negative impact of lymphoma-intrinsic MYC on the immune system. To investigate this, we compared circulating T cells and natural killer (NK) cells of patients with HGBL-MYC/BCL2 (n = 66), patients with DLBCL NOS (n = 53), and age-matched healthy donors (HDs; n = 16) by flow cytometry and performed proliferation, cytokine production, and cytotoxicity assays. Compared with HDs, both lymphoma subtypes displayed similar frequencies of CD8+ T cells but decreased CD4+ T cells. Regulatory T-cell (Treg) frequencies were reduced only in patients with DLBCL NOS. Activated (HLA-DR+/CD38+) T cells, PD-1+CD4+ T cells, and PD-1+Tregs were increased in both lymphoma subtypes, but PD-1+CD8+ T cells were increased only in HGBL-MYC/BCL2. Patients with DLBCL NOS, but not patients with HGBL-MYC/BCL2, exhibited higher frequencies of senescent T cells than HDs. Functional assays showed no overt differences between both lymphoma groups and HDs. Deeper analyses revealed that PD-1+ T cells of patients with HGBL-MYC/BCL2 were exhausted with impaired cytokine production and degranulation. Patients with DLBCL NOS, but not patients with HGBL-MYC/BCL2, exhibited higher frequencies of NK cells expressing inhibiting receptor NKG2A. Both lymphoma subtypes exhibited lower TIM-3+- and DNAM-1+-expressing NK cells. Although NK cells of patients with HGBL-MYC/BCL2 showed less degranulation, they were not defective in cytotoxicity. In conclusion, our results demonstrate an increased exhaustion in circulating T cells of patients with HGBL-MYC/BCL2. Nonetheless, the overall intact peripheral T-cell and NK-cell functions in these patients emphasize the importance of investigating potential immune evasion in the microenvironment of MYC-rearranged lymphomas.

NK Cell Phenotype Is Associated With Response and Resistance to Daratumumab in Relapsed/Refractory Multiple Myeloma.

The CD38-targeting antibody daratumumab has marked activity in multiple myeloma (MM). Natural killer (NK) cells play an important role during daratumumab therapy by mediating antibody-dependent cellular cytotoxicity via their FcγRIII receptor (CD16), but they are also rapidly decreased following initiation of daratumumab treatment. We characterized the NK cell phenotype at baseline and during daratumumab monotherapy by flow cytometry and cytometry by time of flight to assess its impact on response and development of resistance (DARA-ATRA study; NCT02751255). At baseline, nonresponding patients had a significantly lower proportion of CD16+ and granzyme B+ NK cells, and higher frequency of TIM-3+ and HLA-DR+ NK cells, consistent with a more activated/exhausted phenotype. These NK cell characteristics were also predictive of inferior progression-free survival and overall survival. Upon initiation of daratumumab treatment, NK cells were rapidly depleted. Persisting NK cells exhibited an activated and exhausted phenotype with reduced expression of CD16 and granzyme B, and increased expression of TIM-3 and HLA-DR. We observed that addition of healthy donor-derived purified NK cells to BM samples from patients with either primary or acquired daratumumab-resistance improved daratumumab-mediated MM cell killing. In conclusion, NK cell dysfunction plays a role in primary and acquired daratumumab resistance. This study supports the clinical evaluation of daratumumab combined with adoptive transfer of NK cells.

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

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.

Clinical application of flow cytometry in patients with unexplained cytopenia and suspected myelodysplastic syndrome: A report of the European LeukemiaNet International MDS-Flow Cytometry Working Group.

This article discusses the rationale for inclusion of flow cytometry (FCM) in the diagnostic investigation and evaluation of cytopenias of uncertain origin and suspected myelodysplastic syndromes (MDS) by the European LeukemiaNet international MDS Flow Working Group (ELN iMDS Flow WG). The WHO 2016 classification recognizes that FCM contributes to the diagnosis of MDS and may be useful for prognostication, prediction, and evaluation of response to therapy and follow-up of MDS patients.

The flow cytometry myeloid progenitor count: A reproducible parameter for diagnosis and prognosis of myelodysplastic syndromes.

BACKGROUND: The bone marrow blast count is central to the diagnosis and monitoring of myelodysplastic syndromes (MDS). It is an independent risk factor for worse prognosis whether based on the morphology blast count or the flow cytometry (FC) myeloid progenitor (MyP) count. It is a principal population in FC MDS analysis also because once defined; it provides significant contributions to the overall FC MDS score. METHODS: We elected to investigate inter-analyst agreement for the most fundamental parameter of the FC MDS diagnostic score: the MyP count. A common gating strategy was agreed and used by seven cytometrists for blind analysis of 34 routine bone marrows sent for MDS work-up. Additionally, we compared the results with a computational approach. RESULTS: Concordance was excellent: Intraclass correlation was 0.993 whether measuring %MyP of total cells or CD45+ cells, and no significant difference was observed between files from different centers or for samples with abnormal MyP phenotypes. Computational and manual results were similar. Applying the common strategy to individual laboratories' control cohorts produced similar MyP reference ranges across centers. CONCLUSION: The FC MyP count offers a reliable diagnostic and prognostic measurement in MDS. The use of manual and computational approaches side by side may allow for optimizing both strategies. Considering its known prognostic power, the MyP count could be considered a useful and reliable addition to existing prognostic scoring systems.

Characterization of myelodysplastic syndromes hematopoietic stem and progenitor cells using mass cytometry.

BACKGROUND: Myelodysplastic syndromes (MDS) at risk of transformation to acute myeloid leukemia (AML) are difficult to identify. The bone marrows of MDS patients harbor specific hematopoietic stem and progenitor cell (HSPC) abnormalities that may be associated with sub-types and risk-groups. Leukemia-associated characteristics of such cells may identify MDS patients at risk of progression to AML and provide insight in the pathobiology of MDS. METHODS: Bone marrow samples from healthy donors (n = 10), low risk (n = 12) and high risk (n = 13) MDS patients were collected, in addition, AML samples for 5 out of 6 MDS patients that progressed. Mass cytometry was applied to assess expression of stem cell subset and leukemia-associated immunophenotype markers. RESULTS: We analyzed the data using FlowSOM to cluster cells with similar expression of 10 commonly used stem cell markers. Metaclusters (n = 20) of these clusters represented populations of cells with a related phenotype, largely resembling known stem cell subsets. Within specific subsets, intra-cellular expression levels of pCREB, IkBα, or pS6 differed significantly between healthy bone marrow (HBM) and MDS or consecutive secondary AML samples. CD34, CD44, and CD49f expression was significantly increased in high risk MDS and AML-associated metaclusters. We identified MDS/sAML cells with aberrant phenotypes when compared to HBM. Such cells were observed in clusters of both primary MDS and secondary AML samples. CONCLUSIONS: High-dimensional mass cytometry and computational data analyses enabled characterization of HSPC subsets in MDS and identification of leukemia stem cell populations based on their immunophenotype. Stem cells in MDS that display leukemia-associated features may predict the risk of developing AML.

Multiparameter flow cytometry in the evaluation of myelodysplasia: Analytical issues: Recommendations from the European LeukemiaNet/International Myelodysplastic Syndrome Flow Cytometry Working Group.

Multiparameter flow cytometry (MFC) is one of the essential ancillary methods in bone marrow (BM) investigation of patients with cytopenia and suspected myelodysplastic syndrome (MDS). MFC can also be applied in the follow-up of MDS patients undergoing treatment. This document summarizes recommendations from the International/European Leukemia Net Working Group for Flow Cytometry in Myelodysplastic Syndromes (ELN iMDS Flow) on the analytical issues in MFC for the diagnostic work-up of MDS. Recommendations for the analysis of several BM cell subsets such as myeloid precursors, maturing granulocytic and monocytic components and erythropoiesis are given. A core set of 17 markers identified as independently related to a cytomorphologic diagnosis of myelodysplasia is suggested as mandatory for MFC evaluation of BM in a patient with cytopenia. A myeloid precursor cell (CD34+ CD19- ) count >3% should be considered immunophenotypically indicative of myelodysplasia. However, MFC results should always be evaluated as part of an integrated hematopathology work-up. Looking forward, several machine-learning-based analytical tools of interest should be applied in parallel to conventional analytical methods to investigate their usefulness in integrated diagnostics, risk stratification, and potentially even in the evaluation of response to therapy, based on MFC data. In addition, compiling large uniform datasets is desirable, as most of the machine-learning-based methods tend to perform better with larger numbers of investigated samples, especially in such a heterogeneous disease as MDS.

The wider perspective: twenty years of clinical trials in myelodysplastic syndromes.

Most patients with myelodysplastic syndromes (MDS) require therapeutic intervention. However, there are few approved treatments for MDS. To explore reasons, we searched clinicaltrials.gov and clinicaltrialsregister.eu for MDS trials from 2000 to 2020. We assessed which agents were under investigation and analysed clinical trial characteristics and continuation rates from phase I to II to III to approval. As such, we identified 384 unique agents in 426 phase I, 430 phase II and 48 phase III trials. Success rates for phase III trials and agents were low, and MDS trials took markedly longer to complete than the average clinical trial. Although success rates were higher when MDS-specific phase I trials were conducted, 52% of the agents had not been evaluated in a phase I trial for MDS. MDS trials often failed to include quality of life, an especially important outcome for older MDS patients. Our work identifies factors potentially contributing to the paucity of available agents for MDS. We suggest a framework to improve clinical research in MDS that might ultimately augment the number of available agents.

Computational flow cytometry as a diagnostic tool in suspected-myelodysplastic syndromes.

The diagnostic work-up of patients suspected for myelodysplastic syndromes is challenging and mainly relies on bone marrow morphology and cytogenetics. In this study, we developed and prospectively validated a fully computational tool for flow cytometry diagnostics in suspected-MDS. The computational diagnostic workflow consists of methods for pre-processing flow cytometry data, followed by a cell population detection method (FlowSOM) and a machine learning classifier (Random Forest). Based on a six tubes FC panel, the workflow obtained a 90% sensitivity and 93% specificity in an independent validation cohort. For practical advantages (e.g., reduced processing time and costs), a second computational diagnostic workflow was trained, solely based on the best performing single tube of the training cohort. This workflow obtained 97% sensitivity and 95% specificity in the prospective validation cohort. Both workflows outperformed the conventional, expert analyzed flow cytometry scores for diagnosis with respect to accuracy, objectivity and time investment (less than 2 min per patient).

Distinct bone marrow immunophenotypic features define the splicing factor 3B subunit 1 (SF3B1)-mutant myelodysplastic syndromes subtype.

Splicing factor 3B subunit 1 (SF3B1) mutations define a distinct myelodysplastic syndromes (MDS) patient group with a relatively favourable disease course and high response rates to luspatercept. Few data are available on bone marrow phenotype beyond ring sideroblasts in this subgroup of patients with MDS. In the present study, we identified immunophenotypic erythroid, myelomonocyte and progenitor features associated with SF3B1 mutations. In addition, we illustrate that SF3B1-mutation type is associated with distinct immunophenotypic features, and show the impact of co-occurrence of a SF3B1 mutation and a deletion of chromosome 5q on bone marrow immunophenotype. These genotype-phenotype associations and phenotypic subtypes within SF3B1-MDS provide leads that may further refine prognostication and therapeutic strategies for this particular MDS subgroup.

Computational analysis of flow cytometry data in hematological malignancies: future clinical practice?

PURPOSE OF REVIEW: This review outlines the advancements that have been made in computational analysis for clinical flow cytometry data in hematological malignancies. RECENT FINDINGS: In recent years, computational analysis methods have been applied to clinical flow cytometry data of hematological malignancies with promising results. Most studies combined dimension reduction (principle component analysis) or clustering methods (FlowSOM, generalized mixture models) with machine learning classifiers (support vector machines, random forest). For diagnosis and classification of hematological malignancies, many studies have reported results concordant with manual expert analysis, including B-cell chronic lymphoid leukemia detection and acute leukemia classification. Other studies, e.g. concerning diagnosis of myelodysplastic syndromes and classification of lymphoma, have shown to be able to increase diagnostic accuracy. With respect to treatment response monitoring, studies have focused on, for example, computational minimal residual disease detection in multiple myeloma and posttreatment classification of healthy or diseased in acute myeloid leukemia. The results of these studies are encouraging, although accurate relapse prediction remains challenging. To facilitate clinical implementation, collaboration and (prospective) validation in multicenter setting are necessary. SUMMARY: Computational analysis methods for clinical flow cytometry data hold the potential to increase ease of use, objectivity and accuracy in the clinical work-up of hematological malignancies.

Clinical Implication of Multi-Parameter Flow Cytometry in Myelodysplastic Syndromes.

Myelodysplastic syndromes (MDS) are a challenging group of diseases for clinicians and researchers, as both disease course and pathobiology are highly heterogeneous. In (suspected) MDS patients, multi-parameter flow cytometry can aid in establishing diagnosis, risk stratification and choice of therapy. This review addresses the developments and future directions of multi-parameter flow cytometry scores in MDS. Additionally, we propose an integrated diagnostic algorithm for suspected MDS.