Vučinić, Vladan

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.

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.

Introduction: Patients (pts) with relapsed or refractory (R/R) chronic lymphocytic leukemia (CLL) who failed treatment with the Bruton's tyrosine kinase inhibitor (BTKi) ibrutinib have a poor outcome and are difficult to treat. This ongoing, two-cohort, Phase II trial evaluates the safety and preliminary efficacy of tafasitamab (MOR208), an Fc-enhanced anti-CD19 monoclonal antibody in combination with idelalisib (IDE) (Cohort A) or venetoclax (VEN) (Cohort B) in R/R CLL pts previously treated with a BTKi. Preliminary results were published at EHA 2018 for Cohort A and at ASH 2018 for Cohort B. Here, we report the results of the primary analysis for both cohorts. Methods and Patients: Pts who either progressed or were intolerant to BTKi were enrolled at 12 sites in six countries in Europe and the US from Nov 2016 to Apr 2018. The primary endpoint is the incidence and severity of adverse events (AEs); secondary endpoints include overall response rate (ORR) as per investigator assessment according to International Workshop on CLL (IWCLL) 2008 guidelines. Complete response (CR) was confirmed by computed tomography assessment and by bone marrow (BM) biopsy. The exploratory endpoint minimal residual disease (MRD) was assessed centrally by quantitative allele-specific oligonucleotide-polymerase chain reaction (ASO-PCR) in peripheral blood (PB) and BM. Each treatment cycle (C) lasts 28 days (D). Dose and administration: tafasitamab intravenous infusion, 12 mg/kg weekly in C1-C3, every other week in C4-C6 and monthly from C7D1; IDE orally, 150 mg twice daily; VEN orally, weekly ramp up starting on C1D8 at 20 mg to full daily dose of 400 mg. Patients: mean time since first CLL diagnosis was 135 months (mos) for pts in Cohort A and 105 mos in Cohort B. Median number of prior therapy lines was five (2-9) and three (1-5), respectively. All pts had received ibrutinib; one pt had subsequent acalabrutinib treatment as last prior therapy line. Mutations of BTK and PLCγ2 were assessed in nine pts in Cohort A and 13 pts in Cohort B. BTK/PLCγ2 mutations were centrally detected in 4/3 pts in Cohort A and in 2/3 pts in Cohort B, respectively. Complex karyotype was observed in six (54.5%) pts in Cohort A and 12 (92.3%) pts in Cohort B. Results with a data cut-off date of 9 Nov 2018 are presented. Results: Cohort A: Median time on study was 9.9 mos (95% confidence interval [CI]: 5.7-not reached). Eleven pts were enrolled and received tafasitamab and IDE. Two pts discontinued treatment due to AEs (aspartate-aminotransferase increased; acute pancreatitis), two due to progressive disease (PD) and one pt by physician's decision. One pt died due to PD and one pt due to cardiac failure. At the cut-off date, treatment was ongoing in four pts. Table 1 summarizes treatment-emergent adverse events (TEAEs) with neutropenia Grade ≥3 being most common (5 [46%]). Fourteen treatment-emergent serious AEs (SAEs) were reported in eight (72.7%) pts. ORR was 90.9% (CR=9.1%, partial response [PR]=81.8%), disease control was achieved in all 11 pts. One of eight pts (12.5%) assessed for MRD status reached MRD-negativity in PB at C14. Cohort B: Median time on study was 12 mos (95% CI: 2.8-not reached). Eleven of 13 enrolled pts received tafasitamab and VEN while two pts received tafasitamab only. Three pts discontinued treatment due to AEs (infusion-related reactions [two pts], diarrhea [one pt], one due to PD and one withdrew consent. At the cut-off date, treatment was ongoing in eight patients. Table 2 summarizes TEAEs, neutropenia Grade ≥3 was most commonly observed (six [46%] pts). Fourteen SAEs were reported in nine (69.2%) pts. The ORR in all 13 pts was 76.9% (CR=23.1%, PR=53.8%, not evaluable=23.1%). Six of seven pts assessed for MRD in PB (46.2% of 13 [100%] pts) reached negative status in PB by C7 at the latest. One of three pts assessed for MRD in BM (7.7% of 13 [100%] pts) reached MRD negative status in BM at C15. Conclusions: This trial demonstrates that in heavily pretreated pts with R/R CLL who failed prior BTKi, tafasitamab in combination with IDE or VEN is a potential therapeutic option. The safety profiles of the combinations are influenced by the combination partner, but both combinations are manageable. The response rates and MRD-negativity rates indicate that combinations of targeted agents with anti-CD19 tafasitamab have valuable antitumor activity and warrant further investigation of tafasitamab-based combinations in CLL. Disclosures Staber: AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; MSD: Honoraria, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda-Millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Jurczak:Celtrion: Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees, Research Funding; Morphosys: Research Funding; Celgene Corporation: Research Funding; Incyte: Research Funding; Servier: Research Funding; Roche: Research Funding; Novo Nordisk: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Research Funding; Gilead: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Loxo: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; TG Therapeutics: Research Funding. Brugger:AstraZeneca: Equity Ownership; MorphoSys: Employment. Chanan-Khan:Pharmacyclics: Research Funding; Merck: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding; Xencor: Research Funding; AbbVie: Research Funding. Greil:Mundipharma: Honoraria, Research Funding; Bristol-Myers-Squibb: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; Daiichi Sankyo: Consultancy, Honoraria; Sanofi Aventis: Honoraria; Sandoz: Honoraria; AstraZeneca: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; Celgene: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; Eisai: Honoraria; Janssen-Cilag: Honoraria; Cephalon: Consultancy, Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Merck: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; Boehringer Ingelheim: Honoraria; Amgen: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; Ratiopharm: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; MSD: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; Pfizer: Honoraria, Research Funding; Gilead: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; Roche: Consultancy, Honoraria, Other: Travel/accomodation expenses, Research Funding; GSK: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding. Dirnberger-Hertweck:MorphoSys: Employment. Kelemen:MorphoSys: Employment. Middeke:Janssen: Consultancy, Speakers Bureau; MSD: Consultancy; AbbVie: Consultancy, Speakers Bureau; Gilead: Consultancy; Roche: Speakers Bureau; Sanofi: Research Funding, Speakers Bureau. Montillo:Roche: Consultancy, Honoraria, Research Funding; Acerta: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; AstraZeneca: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau; Versatem: Membership on an entity's Board of Directors or advisory committees. Munir:Acerta: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Other: TBC; AbbVie: Honoraria; Alexion: Honoraria; Gilead: Honoraria; Janssen: Honoraria; Novartis: Honoraria; Roche: Honoraria; Morphosys: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sunesis: Consultancy. Parikh:Pharmacyclics: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; MorphoSys: Research Funding; Acerta Pharma: Research Funding; AbbVie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Research Funding. Stilgenbauer:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; Hoffmann La-Roche: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Weirather:MorphoSys: Employment. Woyach:Janssen: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Loxo: Research Funding; Morphosys: Research Funding; Verastem: Research Funding. Wendtner:AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Hoffman-La Roche: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Research Funding, Speakers Bureau; Gilead Sciences, Inc.: Consultancy, Honoraria, Research Funding, Speakers Bureau; MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.