This Data in Brief article presents a novel flow cytometric assay used to acquire and process the data presented and discussed in the research paper by Mestrum et al., co-submitted to Leukemia ...Research, entitled: “Integration of the Ki-67 proliferation index into the Ogata score improves its diagnostic sensitivity for low-grade myelodysplastic syndromes.” 1. The dataset includes the gated fractions of the different myeloid populations in bone marrow (BM) aspirates (total BM cells, CD34 positive blast cells, erythroid cells, granulocytes and monocytes. The raw data is hosted in FlowRepository, while the analyzed data of 1) the fractions of the different myeloid cell populations and 2) the Ki-67 proliferation indices of these myeloid cell populations are provided in tabular form to allow comparison and reproduction of the data when such analyses are performed in a different setting. BM cells from aspirates of 50 myelodysplastic syndrome (MDS) patients and 20 non-clonal cytopenic controls were stained using specific antibody panels and proper fixation and permeabilization to determine the Ki-67 proliferation indices of the different myeloid cell populations. Data was acquired with the three laser, 10-color Navios™ Flow cytometer (Beckman Coulter, Marseille, France) with a blue diode Argon laser (488 nm, 22 mW), red diode Helium/Neon laser (638 nm, 25 mW) and violet air-cooled solid-state diode laser laser (405 nm, 50 mW). A minimum of 100,000 relevant events were acquired per sample, while we aimed at acquiring 500,000 events per sample. Gating was performed with the Infinicyt v2.0 software package (Cytognos SL, Salamanca, Spain). These data may guide the development and standardization of the flow cytometric analysis of the Ki-67 proliferation index (and other markers for cell behavior) for differentiation between non-clonal cytopenic patients and MDS patients. In addition, this assay may be used in myeloid malignancies for research and clinical purposes in other laboratories. This data can be used to encourage future research regarding stem-/progenitor cell resistance against anti-cancer therapies for myeloid malignancies, diagnostics of myeloid malignancies and prognosis of myeloid malignancies. Therefore, these data are of relevance to internist-hematologists, clinical chemists with sub-specialization of hematology and hemato-oncology oriented researchers.
Most myelodysplastic syndromes (MDS)-patients receive multiple red blood cell transfusions (RBCT). Transfusions may cause iron-related toxicity and mortality, influencing outcome after allogeneic ...HSCT. This prospective non-interventional study evaluated 222 MDS and CMML patients undergoing HSCT. Overall survival (OS), relapse-free survival (RFS), non-relapse mortality (NRM), and relapse incidence (RI) at 36 months were 52%, 44%, 25%, and 31%, respectively. Age, percentage of marrow blasts and severe comorbidities impacted OS. RFS was significantly associated with RBCT burden prior to HSCT (HR: 1.7; p = .02). High ferritin levels had a significant negative impact on OS and RI, but no impact on NRM. Administration of iron chelation therapy prior to HSCT did not influence the outcome, but early iron reduction after HSCT (started before 6 months) improved RFS significantly after transplantation (56% in the control group vs. 90% in the treated group, respectively; p = .04). This study illustrates the impact of RBCT and related parameters on HSCT-outcome. Patients with an expected prolonged survival after transplantation may benefit from early iron reduction therapy after transplantation.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Karyotyping is considered as the gold standard in the genetic subclassification of myelodysplastic syndrome (MDS). Oligo/SNP‐based genomic array profiling is a high‐resolution tool that also enables ...genome wide analysis. We compared karyotyping with oligo/SNP‐based array profiling in 104 MDS patients from the HOVON‐89 study. Oligo/SNP‐array identified all cytogenetically defined genomic lesions, except for subclones in two cases and balanced translocations in three cases. Conversely, oligo/SNP‐based genomic array profiling had a higher success rate, showing 55 abnormal cases, while an abnormal karyotype was found in only 35 patients. In nine patients whose karyotyping was unsuccessful because of insufficient metaphases or failure, oligo/SNP‐based array analysis was successful. Based on cytogenetic visible abnormalities as identified by oligo/SNP‐based genomic array prognostic scores based on IPSS/‐R were assigned. These prognostic scores were identical to the IPSS/‐R scores as obtained with karyotyping in 95%‐96% of the patients. In addition to the detection of cytogenetically defined lesions, oligo/SNP‐based genomic profiling identified focal copy number abnormalities or regions of copy neutral loss of heterozygosity that were out of the scope of karyotyping and fluorescence in situ hybridization. Of interest, in 26 patients we demonstrated such cytogenetic invisible abnormalities. These abnormalities often involved regions that are recurrently affected in hematological malignancies, and may therefore be of clinical relevance. Our findings indicate that oligo/SNP‐based genomic array can be used to identify the vast majority of recurrent cytogenetic abnormalities in MDS. Furthermore, oligo/SNP‐based array profiling yields additional genetic abnormalities that may be of clinical importance.
Myelodysplastic syndromes is a heterogeneous group of bone marrow diseases ranging from low risk to high risk subtypes that may rapidly evolve to acute myeloid leukemia. Flow cytometry (FCM) is added ...as a recommended tool for diagnostic purposes in MDS. In recent studies FCM has also shown applicable to predict prognosis and treatment response. This review summarizes current data about the diagnostic, prognostic and therapeutic value of FCM in MDS. The high sensitivity of FCM in the detection of dysplasia in myelo-/monocytic and erythroid cell lineages makes it a valuable tool to distinguish possible clonal causes of cytopenia(s) from non-clonal causes, and to detect multi-lineage dysplasia in addition to cytomorphology. The utility of FCM in prediction of treatment response is promising. Therefore, FCM is an essential tool in standard diagnostic strategies in case of suspected MDS, and ready for general application.
Introduction
Flow cytometry is a recommended tool in the diagnostic work-up of cytopenic patients suspected for myelodysplastic syndromes. Currently used flow cytometry scores rely on human ...assessment of dysplastic features in the bone marrow. Although proven useful, these methods are labor intensive and require a high level of expertise. Therefore, we previously developed a machine learning-based workflow for flow cytometry diagnostics in MDS by combining computational cell detection and a machine learning-classifier. This workflow outperformed traditional diagnostic scores with respect to accuracy (sensitivity 85-97%, specificity 93-97%), time investment (<30 seconds) and required materials (manuscript submitted). In the present study, we validated sensitivity of the workflow in a well-characterized clinical trial cohort (HOVON89 EudraCT 2008-002195-10) of lower risk MDS patients.
Method
Patient inclusion and characteristics
Very low to intermediate risk MDS patients enrolled in the HOVON89 clinical trial (EudraCT 2008-002195-10) were included. 53 patients met the additional inclusion criteria, concerning written consent for add-on studies and availability of required flow cytometry data.
Sample preparation
Bone marrow samples were processed for flow cytometry analysis according to the European Leukemia Net guidelines. This study focused on the antibody combination optimized for assessment of myeloid progenitors and erythroid dysplasia (CD45, CD34, CD117, HLA-DR, CD71, CD36, CD105, CD33, sideward light scatter (SSC) and forward light scatter (FSC)).
Machine learning-based workflow
The machine learning-based workflow was developed in a prior study based on a reference cohort consisting of MDS patients without excess of blasts(n=67) and non-MDS cases (n=81) (Figure 1). MDS patients were diagnosed based on (cyto)morphology, cytogenetics and clinical follow-up. Non-MDS cases were patients with confirmed non-neoplastic cytopenias (n=69) and age-matched healthy individuals (n=12).
Results
In the validation cohort, the machine learning-based diagnostic workflow classified 49 out of 53 patients correctly, reaching a sensitivity of 92%. The workflow outperformed two currently used diagnostic tools for MDS flow cytometry, the Ogata score and integrated flow cytometry score (iFS). The former obtained 72% sensitivity (McNemar: p = 0.001) and the latter 83% sensitivity (McNemar: p = 0.06) in the validation cohort. Per patient, time required for automated analysis was less than 30 seconds.
All four MDS patients that classified false negatively had a normal karyotype and (very) low risk disease according to the IPSS-r. In three out of four patients, no mutations or MDS-associated immunophenotypic features were detected. One patients was diagnosed as MDS-MLD and three patients as MDS-RS-SLD according to the WHO 2016 classification.
The ten most relevant cellular features that discriminated between MDS and non-MDS patients in the reference data were confirmed in the current validation cohort. All ten features of MDS patients in the validation cohort were significantly different from non-MDS patients of the reference cohort (all features, p < 0.00001) (Figure 2). Seven out of ten features were similar in MDS patients of the validation cohort compared to those of the MDS patients of the reference cohort (p>0.05) (Figure 2).
Conclusion
In this validation study, we confirmed accuracy of machine learning-based flow cytometry diagnostics in lower risk MDS. The workflow obtained 92% sensitivity, which is in accordance with results from our previous study (85-97%), and outperformed currently used diagnostic flow cytometry scores for MDS (i.e. Ogata score and iFS). In our previous study specificity was 95% in both reference and test cohorts. Cellular features, most discriminative for diagnosis, were confirmed in the validation cohort, emphasizing robustness of the method. Additional benefits of this approach are the reduction in analysis time to less than thirty seconds per patient, reduction of required antibodies and increased reproducibility.
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van de Loosdrecht:celgene: Honoraria; novartis: Honoraria.
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.
Discriminating between cytopenia(s) due to myelodysplastic syndromes (MDS) and due to other (non-clonal) causes can be challenging, especially when dysplasia as assessed by cytomorphology is minimal, ...and when other MDS-specific features (such as ring sideroblasts or cytogenetic aberrations) are absent. Current recommendations for diagnosing MDS endorse flow cytometry (FC) as a valuable and informative diagnostic tool. Most FC protocols focus on analyzing the progenitor cells and the maturing myelomonocytic lineage. However, one of the most frequently observed symptoms in MDS is anemia, which is often associated with erythrodysplasia. Therefore, flow cytometric features of nucleated erythroid cells may complement current validated FC tools. The international, multicenter study within the European LeukemiaNet MDS-FC working group (ELNet-IMDS-Flow) reported herein focused on defining those erythroid parameters that enable discrimination of dyserythropoiesis associated with MDS from erythropoiesis in non-clonal cytopenias. This analysis was based on ELNet iMDS-flow guidelines for studying nucleated erythroid cells and their expression of CD117, CD71, CD36, CD235a and CD105. Westers et al., Leukemia 2012 Nineteen centers (members of the ELNet-iMDS-flow) collected FC data on the erythroid lineage in mainly low grade MDS cases and pathological and normal controls. Bone marrow aspirates were taken after informed consent in accordance with the Declaration of Helsinki and local ethics committee approval. Data from a learning cohort were compared among MDS patients and controls; the results were validated in a separate cohort. The learning cohort comprised 685 cases and the validation cohort 352 cases; in total 191 normal controls, 443 pathological controls, and 403 MDS cases were included. The data revealed that the analysis of the expression pattern of CD71 and that of CD36 on erythroid cells in combination with the percentage of CD117+ erythroid progenitors provides the best discrimination between MDS and non-clonal cytopenia. The selected markers were used to build an FC erythroid dysplasia score which displayed a sensitivity of 59% (95% CI: 49-68%) and a specificity of 84% (95% CI: 77-89%). Of note, not every MDS case shows signs of erythrodysplasia by cytomorphology whereas some non-clonal conditions do. Evaluation of the results in the validation cohort displayed a specificity of 77% (95% CI: 29-50%) and a sensitivity of 39% (95% CI: 66-85%) for separating pathologic controls and MDS cases based on FC erythroid dysplasia. Most “FC-dysplastic” cases in the pathological control group involved reactive conditions and cytopenia associated with infections. The majority of the “FC-dysplastic” controls demonstrated abnormal CD71 expression, which argues against the application of single aberrancies to indicate dysplasia. Considering only the presence of multiple erythroid aberrancies as erythroid dysplasia by FC increased the specificity to 96% and 95% in the learning and validation cohorts, respectively; however, at the cost of a markedly reduced sensitivity (37% and 21%, respectively). Ultimately, analysis of the erythroid and myeloid lineages should be combined to increase both sensitivity and specificity. In summary, the defined erythroid marker combination may aid the diagnostic work-up of cytopenic cases with suspected MDS, particularly in combination with flow cytometric evaluation of the progenitor cells and maturing myelomonocytic lineage. This will be implemented in an upcoming multicenter data collection exercise within ELNet iMDS-flow.
Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Loosdrecht:Celgene: Consultancy.
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Purpose: This randomized phase II study (HOVON89) in patients with low/int-1 risk MDS refractory or unlikely to respond to erythropoietin and granulocyte-colony stimulating factor (EPO/G-CSF) ...assessed efficacy and safety of lenalidomide without (Arm A) or with EPO+/-G-CSF (Arm B) in case of no erythroid response after 4 cycles.
Patients and methods: In total 200 patients were randomly 1:1 assigned to either Arm A or Arm B. All patients were treated with lenalidomide (10 mg/day/day 1-21) for a minimum of 6 months in arm A and 12 months in arm B or until loss of response or disease progression. Patients in arm B without hematological improvement-erythroid (HI-E) after 4 cycles received EPO (30,000 IU/wk). In those patients who did not show HI-E after 6 months, EPO was increased to 60,000 IE/wk. G-CSF (3x 300-480 µg/wk) was added if no HI-E was reached at 8 month. The current pre-final evaluation was based on the first180 patients and included 85% non-del5q MDS and15% patients with isolated del5q. The median age was 71years (range 38-89). No differences were observed between both arms regarding sex (55% male), WHO PS, WHO diagnostic subgroup and IPSS, baseline Hb, WBC, platelets, endogenous erythropoietin level, pretreatment with EPO+/-G-CSF (67% of the patients were pretreated) and pre-study transfusions. Patients had received a median of 13 (range 0-72) units of RBC and 4 (range 0-13) within 8 weeks for prior study entry.
Results: Adverse events were consistent with the known safety profile of lenalidomide/EPO/G-CSF. HI-E according to IWG criteria was achieved in 38% and 41% of the patients for arm A and B, respectively (p = 0.46). HI-E was significantly lower in non-del5q versus del5q patients (33% vs 78%, respectively). Time-to-HI-E was 3.1 months (median; range 1.6-12.3) for both arms with a median duration of 10 months (range 1 - 76). The median PFS was 14.4 vs 15.4 months in arms A and B (p=0.43). OS was 51.1 and 37.7 months for arm A and B (p=0.09). At 2 years 17% of patients had progressed to AML (no differences between arms). The median FU of patients still alive is 31 months. PFS and OS was significantly longer in those who achieved HI-E, (median 13 vs 19 months, p=0.02 for PFS and median 31 vs 63 months for OS, p<0.001); non-responders vs responders). A Landmark analysis at 12 month confirms a significant prolonged OS in patients who achieved HI-E (28 and 51 months, p<0.002, non-responders vs responders). Endogenous erythropoietin level, pretreatment with EPO/G-CSF, and WHO subgroup did not predict for HI-E, PFS and OS. However, an IPSS of 0 was favorable in comparison to a score of 0.5-1.0 (p=0.02). To better predict response we are currently analyzing baseline flowcytometry and NGS data.
Conclusion: Lenalidomide yields sustained HI-E in 33% of patients with non-del5q low/int-1 risk MDS refractory or unlikely to respond on EPO/G-CSF. The addition of EPO/G-CSF did not improve HI-E. Achievement of HI-E significantly improves PFS and OS.
Ossenkoppele:J&J: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Roche: Honoraria; Karyopharm: Consultancy, Research Funding; Novartis: Research Funding.
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