Magrolimab Therapy in Conjunction with Conventional Chemotherapeutics Slows Disease Progression in Pediatric Acute
Julia G Kim1, Sohani K Sandhu1, Ritesh V Dontula1
1Department of Pediatric Hematology/Oncology, Texas Children's Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.
Abstract:
Background/Objectives: Magrolimab (Magro) is a humanized naked anti-CD47 monoclonal antibody that blocks the SIRPα CD47 interaction, allowing macrophages to target and destroy cancer cells. To evaluate its preclinical efficacy in vivo, Magro was tested as a single agent and in combination with conventional chemotherapy drugs, Cytarabine (Ara-C) or Azacitidine (Aza), in three pediatric AML (pAML) patient-derived xenograft (PDX) models-AML006 (KMT2A::MLLT1), AML010 (+10, WT1), and AML013 (KMT2A::MLLT4). Methods: After PDX model establishment, mice were assigned to treatment groups hulgG4 (VC, vehicle control for Magro), Magro, Ara-C + VC, Aza + VC, Ara-C + Magro, and Aza + Magro, and then followed for survival. Mice that met humane euthanasia endpoints and at the culmination of experimental timelines had tissues harvested to measure disease burden. Results: Magro alone significantly improved survival in AML006 (p < 0.0001) and AML013 (p = 0.003) and decreased bone marrow (BM) disease burden in AML006 (p = 0.009) and AML013 (p = 0.002). Ara-C + Magro therapy led to significantly improved survival in all three models and significantly decreased BM disease burden in AML006 (p < 0.0001) and AML013 (p = 0.048). Aza + Magro therapy led to significantly improved survival in AML013 (p = 0.047) and AML010 (p = 0.017) and significantly lower BM disease burden in AML010 (p = 0.001). Conclusions: Interestingly, the two models that demonstrated improvement in survival with Magro harbored KMT2A rearrangements, suggesting a subset of patients that may be more responsive to the effects of CD47 blockade. As this drug is being evaluated for use in other malignancies, future studies may focus on investigating the importance of biomarker-based patient selection.
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