嵌合抗原受体
抗原
CD33
癌症研究
髓系白血病
髓样
白血病
白细胞介素-3受体
免疫学
生物
T细胞
干细胞
川地34
细胞生物学
免疫系统
作者
Pınar Ataca Atilla,Mary K. McKenna,Norihiro Watanabe,Maksim Mamonkin,Malcolm K. Brenner,Erden Atilla
出处
期刊:Cytotherapy
[Elsevier BV]
日期:2021-12-23
卷期号:24 (3): 282-290
被引量:12
标识
DOI:10.1016/j.jcyt.2021.10.007
摘要
Efforts to safely and effectively treat acute myeloid leukemia (AML) by targeting a single leukemia-associated antigen with chimeric antigen receptor (CAR) T cells have met with limited success, due in part to heterogeneous expression of myeloid antigens. The authors hypothesized that T cells expressing CARs directed toward two different AML-associated antigens would eradicate tumors and prevent relapse.For co-transduction with the authors' previously optimized CLL-1 CAR currently in clinical study (NCT04219163), the authors generated two CARs targeting either CD123 or CD33. The authors then tested the anti-tumor activity of T cells expressing each of the three CARs either alone or after co-transduction. The authors analyzed CAR T-cell phenotype, expansion and transduction efficacy and assessed function by in vitro and in vivo activity against AML cell lines expressing high (MOLM-13: CD123 high, CD33 high, CLL-1 intermediate), intermediate (HL-60: CD123 low, CD33 intermediate, CLL-1 intermediate/high) or low (KG-1a: CD123 low, CD33 low, CLL-1 low) levels of the target antigens.The in vitro benefit of dual expression was most evident when the target cell line expressed low antigen levels (KG-1a). Mechanistically, dual expression was associated with higher pCD3z levels in T cells compared with single CAR T cells on exposure to KG-1a (P < 0.0001). In vivo, combinatorial targeting with CD123 or CD33 and CLL-1 CAR T cells improved tumor control and animal survival for all lines (KG-1a, MOLM-13 and HL-60); no antigen escape was detected in residual tumors.Overall, these findings demonstrate that combinatorial targeting of CD33 or CD123 and CLL-1 with CAR T cells can control growth of heterogeneous AML tumors.
科研通智能强力驱动
Strongly Powered by AbleSci AI