Dual PI3Kδγ inhibition demonstrates potent anticancer effects in diffuse large B-cell lymphoma models: Discovery and preclinical characterization of LL-00084282
Phosphoinositide 3-kinase (PI3K) pathway mediates key signaling events downstream to B-cell receptor (BCR) for survival of mature B-cells, and overexpression or overactivation of PI3Kδ is crucial for B-cell malignancies such as diffuse large B-cell lymphoma (DLBCL). Small molecule PI3Kδγ inhibitors, with a known potential to reduce activated B-cell (ABC)-DLBCL transformation, form an important class of therapeutics approved for follicular lymphoma (FL), chronic lymphocytic leukemia (CLL), small lymphocytic lymphoma (SLL). In this study, we describe discovery of a potent, selective and efficacious dual PI3Kδγ inhibitor, LL-00084282, having a differentiated efficacy profile in human ABC- and germinal center B-cell (GCB)-DLBCL cell lines. LL-00084282 displayed high potency and superior PI3Kδγ engagement with excellent selectivity over other PI3K isoforms at both IC50/90 concentrations in biochemical and cell-based assays. In contrast to selective PI3Kδ inhibitors, LL-00084282 showed superior and potent anticancer activity in both ABC- and GCB-DLBCL cell lines. LL-00084282 demonstrated in-vivo efficacy in OCI-Ly10 and SU-DHL-6 xenografts with good tolerability. Furthermore, LL-00084282 inhibited pro-inflammatory cytokine secretion and reduced basophil activation in human PBMCs, showing potential implications in immunoinflammatory conditions. Good pharmacokinetic properties in higher species and desirable efficacy profile highlights potential of this novel PI3Kδγ inhibitor for further clinical evaluation in DLBCL patients.Keywords: Basophil activation; Diffuse large B-cell lymphoma; Indolent non-Hodgkin's lymphoma; Phosphoinositide 3-kinase; Tumor growth inhibition; Xenograft.
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组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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