MYC protein is a high-risk factor in mantle cell lymphoma and identifies cases beyond morphology, proliferation and TP53/p53 - a Nordic Lymphoma Group study.

The transcription factor MYC is a well-described oncogene with an important role in lymphomagenesis, but its significance for clinical outcome in mantle cell lymphoma (MCL) remains to be determined. We performed an investigation of the expression of MYC protein in a cohort of 251 MCL patients complemented by analyses of structural aberrations and mRNA, in a sub-cohort of patients. Fourteen percent (n=35) of patients showed high MYC protein expression with >20% positive cells (MYChigh), among whom only one translocation was identified, and 86% (n=216) of patients showed low MYC protein expression. Low copy number gains of MYC were detected in ten patients, but with no correlation to MYC protein levels. However, MYC mRNA levels correlated significantly to MYC protein levels with a R2 value of 0.76. Patients with a MYChigh tumor had both an independent inferior overall survival and an inferior progression-free survival (hazard ratio [HR]=2.03, 95% confidence interval [95% CI]: 1.2-3.4 and HR=2.2, 95% CI: 1.04-4.6, respectively) when adjusted for additional high-risk features. Patients with MYChigh tumors also tended to have additional high-risk features and to be older at diagnosis. A subgroup of 13 patients had concomitant MYChigh expression and TP53/p53 alterations and a substantially increased risk of progression (HR=16.9, 95% CI: 7.4-38.3) and death (HR=7.8, 95% CI: 4.4-14.1) with an average overall survival of only 0.9 years. In summary, we found that at diagnosis a subset of MCL patients (14%) overexpressed MYC protein, and had a poor prognosis but that MYC rearrangements were rare. Tumors with concurrent MYC overexpression and TP53/p53 alterations pinpointed MCL patients with a dismal prognosis with a median overall survival of less than 3 years. We propose that MYC needs to be assessed beyond the current high-risk factors in MCL in order to identify cases in need of alternative treatment.

Soluble CD163 predicts outcome in both chemoimmunotherapy and targeted therapy-treated mantle cell lymphoma.

The outcome for patients with mantle cell lymphoma (MCL) has drastically improved with new treatments directed toward the tumor immune microenvironment, where macrophages play an important role. In MCL, the presence of M2 macrophages defined by CD163 expression in diagnostic biopsies has been associated with a worse prognosis. An alternative way to assess the abundance of M2 macrophages is by measuring the level of soluble CD163 in serum (sCD163). We aimed to investigate the prognostic value of sCD163 in 131 patients with MCL. We found that high sCD163 at diagnosis was associated with shorter progression-free survival (PFS) and shorter overall survival (OS) in 81 patients who were newly diagnosed and subsequently treated with chemoimmunotherapy. The same was seen in a cohort of 50 patients with relapsed MCL that were mainly treated within the phase 2 Philemon-trial with rituximab, ibrutinib, and lenalidomide. In patients who were newly diagnosed and had low levels of sCD163, 5-year survival was 97%. There was a moderate correlation between sCD163 and tissue CD163. The association with a poor prognosis was independent of MCL international prognostic index, Ki67, p53 status, and blastoid morphology, as assessed in a multivariable Cox proportional hazards model. In this study, high sCD163 was associated with both shorter PFS and shorter OS, showing that high levels of the M2 macrophage marker sCD163 is an independent negative prognostic factor in MCL, both in the chemoimmunotherapy and ibrutinib/lenalidomide era. In addition, low sCD163 levels identify patients with MCL with a very good prognosis.

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.

Overexpression of the key metabolic protein CPT1A defines mantle cell lymphoma patients with poor response to standard high-dose chemotherapy independent of MIPI and complement established highrisk factors.

The variable outcome to standard immunochemotherapy for mantle cell lymphoma (MCL) patients is a clinical challenge. Established risk factors, including high MCL International Prognostic Index (MIPI), high proliferation (Ki-67), non-classic (blastoid/pleomorphic) morphology, and mutated TP53, only partly identify patients in need of alternative treatment. Deepened understanding of biological factors that influence time to progression and relapse would allow for an improved stratification, and identification of novel targets for high-risk patients. We performed gene expression analyses to identify pathways and genes associated with outcome in a cohort of homogeneously treated patients. In addition to deregulated proliferation, we show that thermogenesis, fatty acid degradation and oxidative phosphorylation are altered in patients with poor survival, and that high expression of carnitine palmitoyltransferase 1A (CPT1A), an enzyme involved in fatty acid degradation, can specifically identify high-risk patients independent of the established high-risk factors. We suggest that complementary investigations of metabolism may increase the accuracy of patient stratification and that immunohistochemistry- based assessment of CPT1A can contribute to defining high-risk MCL.

Multicenter prospective evaluation of diagnostic potential of flow cytometric aberrancies in myelodysplastic syndromes by the ELN iMDS flow working group.

BACKGROUND: Myelodysplastic syndromes (MDS) represent a diagnostic challenge. This prospective multicenter study was conducted to evaluate pre-defined flow cytometric markers in the diagnostic work-up of MDS and chronic myelomonocytic leukemia (CMML). METHODS: Thousand six hundred and eighty-two patients with suspected MDS/CMML were analyzed by both cytomorphology according to WHO 2016 criteria and flow cytometry according to ELN recommendations. Flow cytometric readout was categorized 'non-MDS' (i.e. no signs of MDS/CMML and limited signs of MDS/CMML) and 'in agreement with MDS' (i.e., in agreement with MDS/CMML). RESULTS: Flow cytometric readout categorized 60% of patients in agreement with MDS, 28% showed limited signs of MDS and 12% had no signs of MDS. In 81% of cases flow cytometric readouts and cytomorphologic diagnosis correlated. For high-risk MDS, the level of concordance was 92%. A total of 17 immunophenotypic aberrancies were found independently related to MDS/CMML in ≥1 of the subgroups of low-risk MDS, high-risk MDS, CMML. A cut-off of ≥3 of these aberrancies resulted in 80% agreement with cytomorphology (20% cases concordantly negative, 60% positive). Moreover, >3% myeloid progenitor cells were significantly associated with MDS (286/293 such cases, 98%). CONCLUSION: Data from this prospective multicenter study led to recognition of 17 immunophenotypic markers allowing to identify cases 'in agreement with MDS'. Moreover, data emphasizes the clinical utility of immunophenotyping in MDS diagnostics, given the high concordance between cytomorphology and the flow cytometric readout. Results from the current study challenge the application of the cytomorphologically defined cut-off of 5% blasts for flow cytometry and rather suggest a 3% cut-off for the latter.

The International Consensus Classification of acute myeloid leukemia.

Acute myeloid leukemias (AMLs) are overlapping hematological neoplasms associated with rapid onset, progressive, and frequently chemo-resistant disease. At diagnosis, classification and risk stratification are critical for treatment decisions. A group with expertise in the clinical, pathologic, and genetic aspects of these disorders developed the International Consensus Classification (ICC) of acute leukemias. One of the major changes includes elimination of AML with myelodysplasia-related changes group, while creating new categories of AML with myelodysplasia-related cytogenetic abnormalities, AML with myelodysplasia-related gene mutations, and AML with mutated TP53. Most of recurrent genetic abnormalities, including mutations in NPM1, that define specific subtypes of AML have a lower requirement of ≥ 10% blasts in the bone marrow or blood, and a new category of MDS/AML is created for other case types with 10-19% blasts. Prior therapy, antecedent myeloid neoplasms or underlying germline genetic disorders predisposing to the development of AML are now recommended as qualifiers to the initial diagnosis of AML. With these changes, classification of AML is updated to include evolving genetic, clinical, and morphologic findings.

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.

A series of case studies illustrating the role of flow cytometry in the diagnostic work-up of myelodysplastic syndromes.

Current guidelines recommend flow cytometric analysis as part of the diagnostic assessment of patients with cytopenia suspected for myelodysplastic syndrome. Herein we describe the complete work-up of six cases using multimodal integrated diagnostics. Flow cytometry assessments are illustrated by plots from conventional and more recent analysis tools. The cases demonstrate the added value of flow cytometry in case of hypocellular, poor quality, or ambiguous bone marrow cytomorphology. Moreover, they demonstrate how immunophenotyping results support clinical decision-making in inconclusive and clinically 'difficult' cases.

Mixed Phenotype/Lineage Leukemia: Has Anything Changed for 2021 on Diagnosis, Classification, and Treatment?

PURPOSE OF REVIEW: Recent advances in the small field of the rare mixed phenotype acute leukemias (MPAL) are presented focusing on a better understanding of their pathophysiology and search for better therapeutic approaches. RECENT FINDINGS: Three aspects of respective classification, therapy, and immunophenotype of MPAL are reviewed. New proposals have been made to segregate MPAL subtypes based on their genomic landscape. In parallel, it was found that a large array of therapeutic approaches has been tested in the past few years with increasingly good results. Finally, we explored the use of unsupervised flow cytometry analysis to dissect subtle variations in markers expression to better characterize the variegating aspect of MPALs. Genomic and immunophenotypic aspects more clearly link MPAL subtypes with bona fide acute myeloblastic of lymphoblastic leukemias. This is likely to impact therapeutic strategies, towards a better management and outcome.

Unsupervised cluster analysis and subset characterization of abnormal erythropoiesis using the bioinformatic Flow-Self Organizing Maps algorithm.

BACKGROUND: The Flow-Self Organizing Maps (FlowSOM) artificial intelligence (AI) program, available within the Bioconductor open-source R-project, allows for an unsupervised visualization and interpretation of multiparameter flow cytometry (MFC) data. METHODS: Applied to a reference merged file from 11 normal bone marrows (BM) analyzed with an MFC panel targeting erythropoiesis, FlowSOM allowed to identify six subpopulations of erythropoietic precursors (EPs). In order to find out how this program would help in the characterization of abnormalities in erythropoiesis, MFC data from list-mode files of 16 patients (5 with non-clonal anemia and 11 with myelodysplastic syndrome [MDS] at diagnosis) were analyzed. RESULTS: Unsupervised FlowSOM analysis identified 18 additional subsets of EPs not present in the merged normal BM samples. Most of them involved subtle unexpected and previously unreported modifications in CD36 and/or CD71 antigen expression and in side scatter characteristics. Three patterns were observed in MDS patient samples: i) EPs with decreased proliferation and abnormal proliferating precursors, ii) EPs with a normal proliferating fraction and maturation defects in late precursors, and iii) EPs with a reduced erythropoietic fraction but mostly normal patterns suggesting that erythropoiesis was less affected. Additionally, analysis of sequential samples from an MDS patient under treatment showed a decrease of abnormal subsets after azacytidine treatment and near normalization after allogeneic hematopoietic stem-cell transplantation. CONCLUSION: Unsupervised clustering analysis of MFC data discloses subtle alterations in erythropoiesis not detectable by cytology nor FCM supervised analysis. This novel AI analytical approach sheds some new light on the pathophysiology of these conditions.

Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm.

Ever since hematopoietic cells became "events" enumerated and characterized in suspension by cell counters or flow cytometers, researchers and engineers have strived to refine the acquisition and display of the electronic signals generated. A large array of solutions was then developed to identify at best the numerous cell subsets that can be delineated, notably among hematopoietic cells. As instruments became more and more stable and robust, the focus moved to analytic software. Almost concomitantly, the capacity increased to use large panels (both with mass and classical cytometry) and to apply artificial intelligence/machine learning for their analysis. The combination of these concepts raised new analytical possibilities, opening an unprecedented field of subtle exploration for many conditions, including hematopoiesis and hematological disorders. In this review, the general concepts and progress achieved in the development of new analytical approaches for exploring high-dimensional data sets at the single-cell level will be described as they appeared over the past few years. A larger and more practical part will detail the various steps that need to be mastered, both in data acquisition and in the preanalytical check of data files. Finally, a step-by-step explanation of the solution in development to combine the Bioconductor clustering algorithm FlowSOM and the popular and widely used software Kaluza® (Beckman Coulter) will be presented. The aim of this review was to point out that the day when these progresses will reach routine hematology laboratories does not seem so far away.

Targeted genomic investigations in a population-based cohort of mantle cell lymphoma reveal novel clinically relevant targets.

Mantle cell lymphoma (MCL) is an aggressive B-cell neoplasm that follows a heterogeneous clinical course. Recurrent mutations have been described, but their applicability in the clinical setting is currently limited. The main reasons are challenges in the sequencing of DNA retrieved from formalin-fixed tissue commonly used for tissue collection in clinical biobanks. In this study, we sequenced 77 samples from a population-based de novo MCL cohort to investigate the utility of targeted sequencing in guiding personalized treatment approaches. Tumors were genetically variable, and a similar genetic landscape as previous studies using non-formalin fixed samples was identified, with recurrent mutations including ATM, KMT2D, and TP53. Novel alterations that can be considered actionable and/or indicative of treatment response were also identified. Our approach shows the potential benefits of using target sequencing of formalin fixed samples to facilitate treatment selection and individualized clinical decisions in MCL.

Cumulative exposure to melphalan chemotherapy and subsequent risk of developing acute myeloid leukemia and myelodysplastic syndromes in patients with multiple myeloma.

OBJECTIVES: The aim of this study was to determine risk factors for development of acute myeloid leukemia/myelodysplastic syndromes (AML/MDS) in patients with multiple myeloma (MM). METHODS: We identified all patients diagnosed with MM in Sweden from January 1st, 1958 to December 31, 2011. A total of 26 627 patients were diagnosed with MM with during the study period. Of these, 124 patients (0.5%) developed subsequent AML/MDS. For each patient with MM and a subsequent AML/MDS diagnosis, we randomly selected a matched (age, sex, and date of MM diagnosis) MM patient without a subsequent second malignancy diagnosis. RESULTS: The cumulative melphalan exposure was significantly higher (OR = 2.8, 95% CI 1.7-5.2; P < .001) among cases (median 988 mg; IQR 644-1640) compared with controls (median 578 mg; IQR 360-967). Median time to AML/MDS development was 3.8 years (IQR 2.8-5.8). Risk of AML/MDS was not statistically altered by M protein isotype, anemia, renal failure, hypercalcemia, lytic bone lesions, or radiation therapy. CONCLUSION: In this nationwide population-based study, we show that increased cumulative doses of alkylating therapy with melphalan increases the subsequent risk of developing AML/MDS in patients with MM. Given improved survival in MM patients over the last decade future studies will be important to better define long-term risks.

Infiltration of CD163-, PD-L1- and FoxP3-positive cells adversely affects outcome in patients with mantle cell lymphoma independent of established risk factors.

We characterised patients with mantle cell lymphoma (MCL) with poor prognosis based on differences in immune infiltration. Different expressions of the tumour cell markers Cyclin D1 and sex-determining region Y-box transcription factor 11 (SOX11), and the immune markers cluster of differentiation 3 (CD3), CD4, CD8, CD25, forkhead box protein P3 (FoxP3), T-box transcription factor TBX21 (T-bet), programmed cell death protein 1 (PD-1), programmed-death ligand 1 (PD-L1) and CD163 were investigated for all-cause mortality in 282 patients with MCL and time-to-progression (TTP) in 106 clinical trial patients. With increasing age, a significantly lower infiltration of CD3+ T lymphocytes was seen. T-cell infiltration was independent of cellular tumour antigen p53 (p53) expression, Ki-67, morphology and frequency of tumour cells. The all-cause mortality was higher in patients with PD-L1-expression above cut-off [hazard ratio (HR) 1·97, 95% confidence interval (CI) 1·18-3·25, adjusted for sex and MCL International Prognostic Index (MIPI)] and a higher frequency of CD163+ cells (continuously, HR 1·51, 95% CI 1·03-2·23, adjusting for age, sex, morphology, Ki-67 and p53). In patients treated within the Nordic Lymphoma Group MCL2/3 trials, TTP was shorter in patients with a higher frequency of FoxP3+ cells (HR 3·22, 95% CI 1·40-7·43) and CD163+ cells (HR 6·09, 95% CI 1·84-20·21), independent of sex and MIPI. When combined a higher frequency of CD163+ macrophages and PD-L1+ cells or high CD163+ macrophages and FoxP3+ regulatory T cells indicated worse outcome independent of established risk factors. The T-cell infiltrate was in turn independent of molecular characteristics of the malignant cells and decreased with age.

Monitoring treatment with 5-Azacitidine by flow cytometry predicts duration of hematological response in patients with myelodysplastic syndrome.

5-Azacitidine (AZA) therapy is used in high-risk myelodysplastic syndrome (MDS) patients who often show abnormalities in their immunophenotype. We explored the potential impact of AZA on these immunophenotypic abnormalities in serial bone marrow studies performed in 81 patients from five centers. We compared the immunophenotypic features before and after therapy with AZA, established definitions consistent with flow cytometry immunophenotyping (FCI) improvement, and explored its clinical significance. After a median of 6 cycles of AZA, 41% of patients showed a FCI improvement and this finding associated with best possible clinical response (P < 0.001). FCI improvement also correlated with hematological improvement (HI) (53/78 patients; 68%), independently of their eligibility for stem cell transplantation. Among patients who achieved a HI after 6 cycles of AZA, the probability of maintaining this response at 12 cycles of AZA was twice as large (67%) for those patients who also achieved a FCI improvement after 6 cycles of AZA as compared to patients who did not (33%, P < 0.01). These findings support that monitoring of the immunophenotypic abnormalities during therapy with AZA may assist in redefining the quality of response in patients with MDS.

Radar plots facilitate differential diagnosis of acute promyelocytic leukemia and NPM1+ acute myeloid leukemia by flow cytometry.

BACKGROUND: Acute promyelocytic leukemia (APL) is one of the most life-threatening hematological emergencies and requires a prompt correct diagnosis by cytomorphology and flow cytometry (FCM) with later confirmation by cytogenetics/molecular genetics. However, nucleophosmin 1 muted acute myeloid leukemia (NPM1+ AML) can mimic APL, especially the hypogranular variant of APL. Our study aimed to develop a novel, Radar plot-based FCM strategy to distinguish APLs and NPM1+ AMLs quickly and accurately. METHOD: Diagnostic samples from 52 APL and 32 NPM1+ AMLs patients were analyzed by a 3-tube panel of 10-color FCM. Radar plots combining all markers were constructed for each tube. Percentages of positive leukemic cells and mean fluorescence intensity were calculated for all the markers. RESULTS: APL showed significantly higher expression of CD64, CD2, and CD13, whereas more leukemic cells were positive for CD11b, CD11c, CD15, CD36, and HLA-DR in NPM1+ AMLs. Radar plots featured CD2 expression, a lack of a monocytic component, lack of expression of HLA-DR and CD15, and a lack of a prominent CD11c+ population as recurring characteristics of APL. The presence of blasts with low SSC, presence of at least some monocytes, some expression of HLA-DR and/or CD15, and a prominent CD11c population were recurrent characteristics of NPM1+ AMLs. Radar plot analysis could confidently separate all hypergranular APL cases from any NPM1+ AML and in 90% of cases between variant APL and blastic NPM1+ AML. CONCLUSION: Radar plots can potentially add to differential diagnostics as they exhibit characteristic patterns distinguishing APL and different types of NPM1+ AMLs.