2024
Landscape of Immune Cell States and Ecosystems in Patients with Myelodysplastic Syndrome to Refine Prognostic Assessment and Predict Treatment Response. a Study By i4MDS Consortium
Riva E, Calvi M, Zampini M, Dall'Olio L, Merlotti A, Russo A, Maggioni G, Orlandi L, Frigo A, Ficara F, Crisafulli L, Sauta E, D'Amico S, Lugli E, Campagna A, Ubezio M, Tentori C, Todisco G, Lanino L, Buizza A, Ventura D, Pinocchio N, Saba E, Santoro A, Santini V, van de Loosdrecht A, Komrokji R, Garcia-Manero G, Fenaux P, Ades L, Platzbecker U, Haferlach T, Almeida A, Zeidan A, Kordasti S, Remondini D, Castellani G, Di Vito C, Mavilio D, Della Porta M. Landscape of Immune Cell States and Ecosystems in Patients with Myelodysplastic Syndrome to Refine Prognostic Assessment and Predict Treatment Response. a Study By i4MDS Consortium. Blood 2024, 144: 665-665. DOI: 10.1182/blood-2024-200184.Peer-Reviewed Original ResearchMyelodysplastic syndromeImmune dysfunctionClinical work-upIPSS-MHypomethylating agentsBone marrowImmune ecosystemNatural killerNK cellsImmune monitoringPeripheral bloodT cellsAntibody panelClinical heterogeneity of myelodysplastic syndromesPatients treated with hypomethylating agentsCohort of MDS patientsLevel of immune dysfunctionRisk of leukemic transformationResponse to hypomethylating agentsHeterogeneity of myelodysplastic syndromesMulti-color flow cytometryWork-up of patientsClinical work-up of patientsImmune monitoring approachesMDS microenvironmentEnhancing Personalized Prognostic Assessment of Myelodysplastic Syndromes through a Multimodal and Explainable Deep Data Fusion Approach (MAGAERA)
Sauta E, Sartori F, Lanino L, Asti G, D'Amico S, Delleani M, Riva E, Zampini M, Zazzetti E, Bicchieri M, Maggioni G, Campagna A, Todisco G, Tentori C, Ubezio M, Russo A, Buizza A, Ficara F, Crisafulli L, Brindisi M, Ventura D, Pinocchio N, Rahal D, Lancellotti C, Bonometti A, Di Tommaso L, Savevski V, Santoro A, Derus N, Dall'Olio D, Santini V, Sole F, Platzbecker U, Fenaux P, Diez-Campelo M, Komrokji R, Garcia-Manero G, Haferlach T, Kordasti S, Zeidan A, Castellani G, Sanavia T, Fariselli P, Della Porta M. Enhancing Personalized Prognostic Assessment of Myelodysplastic Syndromes through a Multimodal and Explainable Deep Data Fusion Approach (MAGAERA). Blood 2024, 144: 105-105. DOI: 10.1182/blood-2024-205413.Peer-Reviewed Original ResearchPersonalized medicine programsMyelodysplastic syndrome patientsMyelodysplastic syndromeOverall survivalConcordance indexClinical outcomesMay-Grunwald-GiemsaHypomethylating agentsBone marrowAnalysis of hematological malignanciesSomatic mutation screeningEvaluation of T lymphocytesResponse to hypomethylating agentsCD34+ bone marrowStudies of myelodysplastic syndromesGenomic featuresMDS populationRNA-seqPrediction of patient outcomeGenomic characterizationHarrell's concordance indexPredicting clinical outcomesHematoxylin and eosin (H&EMorphological dataMulti-omicsThe Implication of TP53 Allelic Status for Outcome and Erythropoiesis in MDS
Li B, Zeng Y, Li C, Liu J, Song G, Yao Y, Zeidan A, Xiao Z. The Implication of TP53 Allelic Status for Outcome and Erythropoiesis in MDS. Blood 2024, 144: 6707-6707. DOI: 10.1182/blood-2024-205429.Peer-Reviewed Original ResearchNext-generation sequencingMultiplex ligation-dependent probe amplificationComplex karyotypeMyelodysplastic syndromeCD34+ cellsPrognostic impactClinical characteristicsBone marrowPercentage of erythroid progenitorsCD34+ BM cellsAllele statusSubtype of myelodysplastic syndromeLigation-dependent probe amplificationTP53-mutant patientsPercentage of blastsSingle-cell mutational analysisCopy number assayCopy number alterationsClone sizeLineage dysplasiaMutant patientsTP53 mutationsBM cellsMDS-UWHO classificationArtificial Intelligence-Powered Digital Pathology to Improve Diagnosis and Personalized Prognostic Assessment in Patient with Myeloid Neoplasms
Asti G, Curti N, Maggioni G, Carlini G, Lanino L, Campagna A, D'Amico S, Sauta E, Delleani M, Bonometti A, Lancellotti C, Rahal D, Ubezio M, Todisco G, Tentori C, Russo A, Crespi A, Figini G, Buizza A, Riva E, Zampini M, Brindisi M, Ficara F, Crisafulli L, Ventura D, Pinocchio N, Zazzetti E, Bicchieri M, Grondelli M, Forcina Barrero A, Savevski V, Santoro A, Santini V, Sole F, Platzbecker U, Fenaux P, Diez-Campelo M, Komrokji R, Haferlach T, Kordasti S, Di Tommaso L, Zeidan A, Loghavi S, Garcia-Manero G, Castellani G, Della Porta M. Artificial Intelligence-Powered Digital Pathology to Improve Diagnosis and Personalized Prognostic Assessment in Patient with Myeloid Neoplasms. Blood 2024, 144: 3598-3598. DOI: 10.1182/blood-2024-206248.Peer-Reviewed Original ResearchLeukemia-free survivalMyeloid neoplasmsOverall survivalConcordance indexGenomic informationBone marrowPredictive of overall survivalMD Anderson Cancer CenterCell typesProportion of patientsHarrell's concordance indexSomatic gene mutationsMorphological featuresHumanitas Research HospitalGenomic dataMGG smearsPersonalized risk assessmentRUNX1 mutationsBM aspiratesClinically relevant informationClinical entityBiopsy dataMN patientsPrognostic assessmentWhole slide imagesEncouraging Efficacy of Bexmarilimab with Azacitidine in Relapsed or Refractory MDS in Bexmab Ph1/2 Study
Kontro M, Stein A, Pyörälä M, Rimpiläinen J, Siitonen T, Rannikko J, Mickos J, Turpin R, Hakoniemi M, Berns B, Aakko S, Pawlitzky I, Hollmén M, Zeidan A, Daver N. Encouraging Efficacy of Bexmarilimab with Azacitidine in Relapsed or Refractory MDS in Bexmab Ph1/2 Study. Blood 2024, 144: 4265. DOI: 10.1182/blood-2024-206804.Peer-Reviewed Original ResearchMedian overall survival estimatesMyelodysplastic syndrome patientsTreatment-emergent adverse eventsMyelodysplastic syndromeBone marrowMarrow CRStable diseaseHematologic improvementPartial responseClever-1HLA-DROutcome of high-risk myelodysplastic syndromeHuman leukocyte antigen-DR isotypePhase 1 dose-escalationResponse of stable diseaseAllogeneic stem cell transplantationHigh-risk myelodysplastic syndromeHigher-risk myelodysplastic syndromesSimon 2-stage designTreatment of myelodysplastic syndromesResponse rateBayesian optimal intervalMedian overall survivalPrimary refractory diseaseRefractory myelodysplastic syndromeImmune Landscape and Outcomes of Patients with RNA Splicing Factor-Mutant Acute Myeloid Leukemia and Myelodysplastic Syndromes Treated with Azacitidine +/- the Anti-PD-L1 Antibody Durvalumab
Bewersdorf J, Hasle V, Shallis R, Thompson E, De Menezes D, Rose S, Boss I, Mendez L, Podoltsev N, Stahl M, Kewan T, Halene S, Haferlach T, Fox B, Zeidan A. Immune Landscape and Outcomes of Patients with RNA Splicing Factor-Mutant Acute Myeloid Leukemia and Myelodysplastic Syndromes Treated with Azacitidine +/- the Anti-PD-L1 Antibody Durvalumab. Blood 2024, 144: 4585. DOI: 10.1182/blood-2024-194929.Peer-Reviewed Original ResearchAcute myeloid leukemiaAnti-PD-L1 antibody durvalumabOverall response rateMyelodysplastic syndromeComplete responseBM aspiratesMyeloid leukemiaInternational Working GroupBone marrowMyelodysplastic syndromes treated with azacitidineAcute myeloid leukemia ptsWild-type acute myeloid leukemiaSecondary acute myeloid leukemiaResponse criteriaAnti-PD-L1Immune checkpoint inhibitorsTreated with azacitidineOutcomes of patientsAny-cause deathGeneration of neoantigensVariant allele frequencySusceptible to treatmentMarrow CRAdverse cytogeneticsCheckpoint inhibitorsIntegrated genetic, epigenetic, and immune landscape of TP53 mutant AML and higher risk MDS treated with azacitidine
Zeidan A, Bewersdorf J, Hasle V, Shallis R, Thompson E, de Menezes D, Rose S, Boss I, Halene S, Haferlach T, Fox B. Integrated genetic, epigenetic, and immune landscape of TP53 mutant AML and higher risk MDS treated with azacitidine. Therapeutic Advances In Hematology 2024, 15: 20406207241257904. PMID: 38883163, PMCID: PMC11180421, DOI: 10.1177/20406207241257904.Peer-Reviewed Original ResearchHigher-risk myelodysplastic syndromesAcute myeloid leukemiaBone marrowMutation statusImmune landscapeImmunological landscapeAnti-PD-L1 antibody durvalumabHR-MDS patientsWild-type acute myeloid leukemiaTP53-mutant acute myeloid leukemiaMutant acute myeloid leukemiaAzacitidine-based therapyWild-type patientsImmune checkpoint proteinsImmune checkpoint expressionT cell populationsWild-typeStatistically significant decreaseAZA therapyImmunosuppressive microenvironmentPD-L1Mutant patientsDNA methylation arraysCheckpoint expressionMyelodysplastic syndrome
2023
Safety, Pharmacodynamic, and Anti-Tumor Activity of SL-172154 As Monotherapy and in Combination with Azacitidine (AZA) in Relapsed/Refractory (R/R) Acute Myeloid Leukemia (AML) and Higher-Risk Myelodysplastic Syndromes/Neoplasms (HR-MDS) Patients (pts)
Daver N, Stein A, Bixby D, Chai-Ho W, Zeidner J, Maher K, Stevens D, Stahl M, Yee K, Curran E, Ito S, Sochacki A, Sallman D, Hernandez R, Metenou S, Ma B, Kato K, Zeidan A. Safety, Pharmacodynamic, and Anti-Tumor Activity of SL-172154 As Monotherapy and in Combination with Azacitidine (AZA) in Relapsed/Refractory (R/R) Acute Myeloid Leukemia (AML) and Higher-Risk Myelodysplastic Syndromes/Neoplasms (HR-MDS) Patients (pts). Blood 2023, 142: 4278. DOI: 10.1182/blood-2023-173991.Peer-Reviewed Original ResearchR AMLAcute myeloid leukemiaTreatment-emergent AEsInfusion-related reactionsDose-limiting toxicityDose-escalation cohortsHR-MDSDose-dependent increaseComplete remissionObjective responseAnti-tumor activityBone marrowHypomethylating agentAllo-HCTAML ptsEvaluable ptsEscalation cohortsDose escalationRelapsed/Refractory Acute Myeloid LeukemiaMedian age 70 yearsMorphologic leukemia-free statePhase 1 dose escalationSIRPα-Fc fusion proteinRefractory acute myeloid leukemiaMarrow complete remissionLuspatercept Modulates Inflammation in the Bone Marrow, Restores Effective Erythropoiesis/Hematopoiesis, and Provides Sustained Clinical Benefit Versus Epoetin Alfa (EA): Biomarker Analysis from the Phase 3 COMMANDS Study
Hayati S, Zeidan A, Garcia-Manero G, Platzbecker U, Ahsan A, Verma A, Aluri S, Guerrero M, Gandhi A, Suragani R, Vodala S. Luspatercept Modulates Inflammation in the Bone Marrow, Restores Effective Erythropoiesis/Hematopoiesis, and Provides Sustained Clinical Benefit Versus Epoetin Alfa (EA): Biomarker Analysis from the Phase 3 COMMANDS Study. Blood 2023, 142: 1845. DOI: 10.1182/blood-2023-178674.Peer-Reviewed Original ResearchBM mononuclear cellsLow-risk MDSEpoetin alfaWk 48Myelodysplastic syndromeWk 24Clinical benefitPg/Bone marrowErythroid precursorsITT populationIL-1Ring sideroblastsN-terminal pro-brain natriuretic peptideLower-risk myelodysplastic syndromesPro-brain natriuretic peptideHematopoietic stem cellsDysplastic erythroid precursorsRBC transfusion independencePhase 3 trialSuperior clinical benefitSerum cytokine analysisAnti-inflammatory signalingIL-10 signalingComplete blood countImpact of Type of Hypomethylating Agent (HMA) Used on Outcomes of Patients (Pts) with Higher-Risk Myelodysplastic Syndromes/Neoplasms (HR-MDS) - a Large, Multicenter, Retrospective Analysis
Bewersdorf J, Kewan T, Blaha O, Stahl M, Al Ali N, DeZern A, Sekeres M, Uy G, Carraway H, Desai P, Griffiths E, Stein E, Brunner A, McMahon C, Zeidner J, Savona M, Stempel J, Chandhok N, Ramaswamy R, Roboz G, Rolles B, Wang E, Harris A, Amaya M, Hawkins H, Grenet J, Gurnari C, Shallis R, Xie Z, Maciejewski J, Sallman D, Della Porta M, Komrokji R, Zeidan A. Impact of Type of Hypomethylating Agent (HMA) Used on Outcomes of Patients (Pts) with Higher-Risk Myelodysplastic Syndromes/Neoplasms (HR-MDS) - a Large, Multicenter, Retrospective Analysis. Blood 2023, 142: 4613. DOI: 10.1182/blood-2023-178728.Peer-Reviewed Original ResearchCox multivariable regression modelOverall survivalHMA initiationHypomethylating agentMultivariable regression modelsTP53 mutationsAllo-HCTComplete remissionComplex karyotypePartner drugsBone marrowSurvival analysisAllogeneic hematopoietic cell transplantMultivariable Cox regression modelsTreatment typeOverall responseAdverse genetic featuresMedian overall survivalOutcomes of patientsHematopoietic cell transplantAdverse overall survivalKaplan-Meier methodCox regression modelLog-rank testPredictors of response
2021
Immune and Epigenetic Landscape of TP53-mutated Acute Myeloid Leukemia (AML) and Higher-Risk Myelodysplastic Syndromes (HR-MDS)
Zeidan A, Bewersdorf J, Hasle V, Thompson E, de Menezes D, Rose S, Boss I, Fox B. Immune and Epigenetic Landscape of TP53-mutated Acute Myeloid Leukemia (AML) and Higher-Risk Myelodysplastic Syndromes (HR-MDS). Blood 2021, 138: 3371. DOI: 10.1182/blood-2021-146329.Peer-Reviewed Original ResearchHigh-risk myelodysplastic syndromeClinical Trials CommitteeAcute myeloid leukemiaBristol-Myers SquibbCurrent equity holderPoor-risk cytogeneticsVariant allele frequencyAML ptsOverall response rateTrials CommitteeMedian OSTP53 mutationsMyeloid neoplasmsFlow cytometryPeripheral bloodT cell genesHigh expressionBone marrowAverage variant allele frequencyRandomized phase 2 studyBone marrow flow cytometryT-cell gene signatureTumor cellsBM blast percentageIPSS-R score
2019
Will deeper characterization of the landscape of immune checkpoint molecules in acute myeloid leukemia bone marrow lead to improved therapeutic targeting?
Vandsemb EN, Kim TK, Zeidan AM. Will deeper characterization of the landscape of immune checkpoint molecules in acute myeloid leukemia bone marrow lead to improved therapeutic targeting? Cancer 2019, 125: 1410-1413. PMID: 30861094, PMCID: PMC6467744, DOI: 10.1002/cncr.32042.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2018
The use of immunosuppressive therapy in MDS: clinical outcomes and their predictors in a large international patient cohort
Stahl M, DeVeaux M, de Witte T, Neukirchen J, Sekeres MA, Brunner AM, Roboz GJ, Steensma DP, Bhatt VR, Platzbecker U, Cluzeau T, Prata PH, Itzykson R, Fenaux P, Fathi AT, Smith A, Germing U, Ritchie EK, Verma V, Nazha A, Maciejewski JP, Podoltsev NA, Prebet T, Santini V, Gore SD, Komrokji RS, Zeidan AM. The use of immunosuppressive therapy in MDS: clinical outcomes and their predictors in a large international patient cohort. Blood Advances 2018, 2: 1765-1772. PMID: 30037803, PMCID: PMC6058241, DOI: 10.1182/bloodadvances.2018019414.Peer-Reviewed Original ResearchConceptsAnti-thymocyte globulinRBC transfusion independenceImmunosuppressive therapyTransfusion independenceOverall response rateHypocellular bone marrowMyelodysplastic syndromeOverall survivalBone marrowRed blood cell transfusion independenceHorse anti-thymocyte globulinRabbit anti-thymocyte globulinInternational Working Group criteriaCox proportional hazards modelSingle-center natureMedian overall survivalKaplan-Meier methodLarge international cohortLarge international patient cohortProportional hazards modelInternational patient cohortPredictors of benefitParoxysmal nocturnal hemoglobinuriaLogistic regression modelsSteroid monotherapy