Robin, Marie

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.

Objective Vacuoles E1 enzyme X‐linked autoinflammatory somatic syndrome (VEXAS) is a recently identified rare genetic disorder associated with somatic mutations in the UBA1 gene. VEXAS presents with a combination of inflammatory and hematologic manifestations, leading to increased morbidity and mortality. Methods Given the variability in disease presentation and the limited number of studies to date, no clinical documents currently exist to provide guidance to health care providers about the management of VEXAS. To address this gap, we formed an international multidisciplinary panel of VEXAS experts. Results Through formalized meetings and a voting process, the group developed consensus clinical guidance considerations for the management of VEXAS. These considerations offer practical advice on several key topics: (1) clinical features of VEXAS, (2) UBA1 screening methods, (3) the diagnosis of myelodysplastic syndromes (MDSs) in patients with VEXAS, and (4) prognosis and management. The aim is to provide expert guidance on which patients to test, how to test for VEXAS, how to approach MDS in the context of VEXAS, and considerations for management. Conclusion This work marks the first formal international consensus guidance for VEXAS and is intended to be used as a resource for clinicians seeking to understand the disease and its management.

Abstract “Nonclassical” myeloproliferative neoplasms (MPNs) and myelodysplastic/myeloproliferative neoplasms (MDS/MPNs) represent a heterogeneous group of malignancies characterized by a wide range of clinical manifestations. Unlike classical MPNs, there is no standardized management approach for these conditions, particularly concerning the indications for and management of allogeneic hematopoietic cell transplantation. To address this gap, the European Society for Blood and Marrow Transplantation (EBMT) Practice Harmonization and Guidelines (PH&G) Committee and the Chronic Malignancies Working Party (CMWP) have collaborated to develop shared guidelines aimed at optimizing the selection and management of patients with these rare forms of neoplasms. A comprehensive review of the literature from the publication of the revised fourth edition of the (2016) World Health Organization classification onward was conducted. A multidisciplinary group of experts in the field convened to produce this document, which was developed through multiple rounds of draft circulation. Key recommendations include the early identification of potential transplant candidates, particularly in cases of chronic neutrophilic leukemia, chronic eosinophilic leukemia (CEL)/CEL, not otherwise specified (CEL-NOS), myeloid/lymphoid neoplasm with eosinophilia and tyrosine kinase gene fusions with FGFR1, JAK2, ABL1, and FLT3 rearrangements, MDS/MPN with neutrophilia/atypical chronic myeloid leukemia, and MDS/MPN, NOS. For patients with MPN, NOS/MPN unclassifiable, standard recommendations for myelofibrosis should be applied. Similarly, in MDS/MPN with thrombocytosis, transplantation is recommended on the basis of established MDS guidelines. Given the current lack of robust evidence, this document will serve as a valuable resource to guide future research activities, providing a framework for addressing critical unanswered questions and advancing the field.

Background. Study of myeloid neoplasms (MN) has been rapidly transformed by genome characterization. Gene mutations have been reported to influence disease phenotype and risk of disease progression, and the evaluation of mutational status can provide valuable insights to improve the decision-making process. In this international study, we evaluated the clinical impact of mutational screening in patients with CMML, which is characterized by significant clinical and genomic heterogeneity, including a substantial proportion of patients with poor outcomes and unmet needs. Currently, only limited molecular information has been incorporated into CMML classification and prognostication. Methods. We retrospectively collected 3182 CMML patients. We used MOSAIC, an AI-based framework for multimodal analysis in rare cancers (PMID: 38875514) to develop innovative, molecular-based tools for classification and prognostication. An independent validation of the results on 516 prospectively collected patients was performed. Results. Bayesian Networs and Hierarchical Dirichlet Processes were used to identify genomic associations and define a CMML molecular classification. We identified 11 clusters with distinct clinical and genomic features, including splicing machinery, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures (i.e., AML-like and TP53 mutations). Up to 15% of patients showed clear genomic overlap with other MN. Importantly, extensive multi-color flow cytometry on T lymphocytes, NK and myeloid cells (BD FACSymphony A5 Cell Analyzer) revealed specific immunologic and inflammation signatures associated with molecular subgroups. We then integrated molecular and clinical information to build an international CMML Prognostic Scoring System (iCPSS). We assessed the performance of different statistical and AI-based methods; L1-penalized Cox Model resulted as the best performing method. Selected features included hematological parameters (WBC, Hb, PLT and marrow blasts), cytogenetic abnormalities, and mutations in 10 genes (ASXL1, DNMT3A, EZH2, NRAS, RUNX1, SETBP1, STAG2, TET2, TP53, U2AF1). By Bayesian thresholds optimization, we identified 5 risk classes (i.e., very-low, low, intermediate, high and very-high) with median overall survival (OS) ranging from 99 to 9 months (P&lt;.001), and median leukemia-free survival (LFS) ranging from 210 to 18 months (P&lt;.001). iCPSS provided better patient discrimination across all clinical endpoints compared to currently available prognostic tools, with a Concordance Index (CI) for OS of 0.75 versus 0.62-0.64, respectively. Notably, compared to available scoring systems, up to 40% of patients were reassigned to higher or lower risk classes by the iCPSS. External validation on an independent prospective cohort confirmed that the performance of iCPSS is superior to existing prognostic models (CI for OS 0.71 vs 0.54-0.61, respectively) To demonstrate the clinical utility of iCPSS, we focused on 753 patients who underwent allogeneic stem cell transplantation (HSCT). In multivariable analysis, iCPSS stratified the probability of OS post-HSCT (P&lt;.001) and identified groups of patients with different probabilities of disease relapse, ranging from 9% to 62% (P&lt;.001). We employed a clinical- and genomic-based decision support system (PMID: 38723212) to determine the optimal timing of HSCT. Preliminary analyses indicated that higher-risk patients according to iCPSS (i.e., intermediate, high, and very high) benefit from an immediate HSCT strategy. Lower-risk patients (i.e., very low and low) had life expectancy maximized with delayed HSCT. Modeling decision analysis using iCPSS compared to conventional scores, resulted in a change in transplantation policy for a significant proportion of patients (up to 25%). Conclusion. Molecular information significantly improves the classification of CMML patients, providing a basis for refining diagnostic boundaries with other MN and for a more rational inclusion of patients in clinical trials. The iCPSS demonstrated superior performance over currently available scoring systems and improved HSCT decision making process.

Abstract To determine the survival benefit of allogeneic hematopoietic cell transplantation (allo-HCT) in chronic myelomonocytic leukemias (CMML), we assembled a retrospective cohort of CMML patients 18-70 years old diagnosed between 2000 and 2014 from an international CMML dataset (n = 730) and the EBMT registry (n = 384). The prognostic impact of allo-HCT was analyzed through univariable and multivariable time-dependent models and with a multistate model, accounting for age, sex, CMML prognostic scoring system (low or intermediate-1 grouped as lower-risk, intermediate-2 or high as higher-risk) at diagnosis, and AML transformation. In univariable analysis, lower-risk CMMLs had a 5-year overall survival (OS) of 20% with allo-HCT vs 42% without allo-HCT (P &lt; .001). In higher-risk patients, 5-year OS was 27% with allo-HCT vs 15% without allo-HCT (P = .13). With multistate models, performing allo-HCT before AML transformation reduced OS in patients with lower-risk CMML, and a survival benefit was predicted for men with higher-risk CMML. In a multivariable analysis of lower-risk patients, performing allo-HCT before transformation to AML significantly increased the risk of death within 2 years of transplantation (hazard ratio [HR], 3.19; P &lt; .001), with no significant change in long-term survival beyond this time point (HR, 0.98; P = .92). In higher-risk patients, allo-HCT significantly increased the risk of death in the first 2 years after transplant (HR 1.46; P = .01) but not beyond (HR, 0.60; P = .09). Performing allo-HCT before AML transformation decreases life expectancy in lower-risk patients but may be considered in higher-risk patients.

Background: CMML is a heterogeneous disease with overlapping features of MDS and MPN. Several risk scores have been proposed in CMML, including CPSS (Such Blood 2013) that identifies 4 risk groups (low, intermediate-1 [int-1], int-2 and high risk) with median overall survival (OS) ranging from 12 months to > 5 years. HSCT is the only curative treatment in CMML, with an expected 20-40% post-transplantation OS. Current guidelines, common to MDS and CMML recommend rapidly transplanting higher-risk CMML and delaying transplant in lower-risk disease (de Witte Blood 2017). Retrospective transplant studies have shown better outcome in lower-risk CMML (Liu et al BBMT 2017). Whether this translates into a survival benefit compared to a delayed transplant strategy requires prospective studies. Multistate models based on retrospective data from transplant and non-transplant patients (pts) have addressed similar issues in MDS (Koreth JCO 2013, Della Porta Leukemia 2017). Through a large collaborative study, we address the question of optimal timing for HSCT in CMML patients through a similar large international collaborative study. Method: We retrospectively selected pts from 2 registries: International MDS/MPN Working Group (IWG cohort, Padron Blood Cancer J 2015) and EBMT with the following criteria: WHO-defined CMML, age ≤ 70y, ECOG 0-2, diagnosis after 2000, available CPSS at the time of diagnosis. Different states were considered in higher- (CPSS int-2 and high) and lower- risk (CPSS low/int-1) pts: diagnosis, AML transformation, transplantation and death. IWG data was used to estimate transition probabilities from diagnosis to AML, transplantation and death and from AML to transplantation and death. EBMT data was used for transplantation to death transitions (Figure 1). Results: 719 and 403 pts were identified in the IWG and EMBT registry, respectively (resp). Median age was 64 (range 16-70) in IWG and 58 (19-70) years in EBMT cohort. Patients were male in 69% and 67% of IWG and EBMT cohorts, respectively (resp). CPSS was low in 22% and 13%, int-1 in 31% and 31%, int-2 in 40% and 45% and high in 8% and 11% of the IWG and EBMT pts, resp. In the IWG cohort, the 1 year cumulative incidence of transformation into AML were 7.3% and 18.2% in lower and higher risk patients, resp. Among the 719 pts from IWG, 102 received HSCT. At the time of diagnosis the expected life time of higher risk (int-2 and high) patients was 25.2 months while it was 44.1 months in lower risk (int-1 and low) patients. Table 1 reports gain or loss in expected life time (until 60 months after diagnosis) for transplantation at different intervals from diagnosis (within 6, 12, 18 and 24 months) for patients who have survived and not transformed to AML until the prediction time point, taking into account CPSS at diagnosis. Expected life time is also given separately for higher risk pts after transformation into AML. There was a modest gain of life expectancy with transplantation in higher risk patients (CPSS int-2 and high) while it was not the case in lower risk patients. The survival gain in higher risk pts with HSCT rose from 1.11 at 6 months to 3.4 months at 24 months. There was also a survival benefit of HSCT in higher risk pts who were transformed to AML during their follow-up which was even higher in terms of gain of months: from 9.89 month if HSCT performed within 6 months to 14.25 months if performed within 18 months. Of note, the loss of survival in lower risk patients who underwent HSCT decreased over time: 11.1 months if HSCT is performed within 6 months and 3.7 months if HSCT is performed within 24 months, probably owing to transition to higher-risk CMML at this stage in some pts, a transition that could not be captured in the present dataset. Conclusion: For the first time, using a multistate model, we could provide evidence that the transplant benefit in CMML is restricted to higher-risk pts, in line with findings in MDS and current guidelines. More analyses will be performed to analyze other subgroups of patients, especially regarding their risk (other classification than CPSS, the role of somatic mutation…). More studies are needed to analyze the role of pre HSCT treatment and its potential impact on post-transplant outcome. Disclosures Robin: Novartis Neovii: Research Funding. Beelen:Medac GmbH Wedel Germany: Consultancy, Honoraria. Fenaux:Celgene Corporation: Honoraria, Research Funding; Astex: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; Aprea: Research Funding. Kroeger:Riemser: Research Funding; Novartis: Honoraria, Research Funding; Medac: Honoraria; DKMS: Research Funding; Neovii: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; JAZZ: Honoraria; Sanofi-Aventis: Honoraria. Nazha:Tolero, Karyopharma: Honoraria; MEI: Other: Data monitoring Committee; Novartis: Speakers Bureau; Jazz Pharmacutical: Research Funding; Incyte: Speakers Bureau; Daiichi Sankyo: Consultancy; Abbvie: Consultancy. Rampal:Agios, Apexx, Blueprint Medicines, Celgene, Constellation, and Jazz: Consultancy; Constellation, Incyte, and Stemline Therapeutics: Research Funding. Finke:Riemser: Honoraria, Other: research support, Speakers Bureau; Neovii: Honoraria, Other: research support, Speakers Bureau; Medac: Honoraria, Other: research support, Speakers Bureau. Komrokji:Agios: Consultancy; DSI: Consultancy; pfizer: Consultancy; celgene: Consultancy; JAZZ: Consultancy; Novartis: Speakers Bureau; JAZZ: Speakers Bureau; Incyte: Consultancy. Killick:JAZZ: Honoraria; Celgene: Honoraria; NOVARTIS: Honoraria, Membership on an entity's Board of Directors or advisory committees; ALEXION: Honoraria. Blaise:Molmed: Consultancy, Honoraria; Sanofi: Honoraria; Pierre Fabre medicaments: Honoraria; Jazz Pharmaceuticals: Honoraria. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Patnaik:Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.