Quantifying ADC bystander payload penetration with cellular resolution using pharmacodynamic mapping.
Quantifying ADC bystander payload penetration with cellular resolution using pharmacodynamic mapping.
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使用药效学映射通过细胞分辨率定量ADC旁观者有效载荷穿透。
DOI:
10.1016/j.neo.2020.12.001
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发表时间:
2021-03
期刊:
影响因子:
--
通讯作者:
Thurber GM
中科院分区:
文献类型:
--
作者:
Khera E;Cilliers C;Smith MD;Ganno ML;Lai KC;Keating TA;Kopp A;Nessler I;Abu-Yousif AO;Thurber GM
With the recent approval of 3 new antibody drug conjugates (ADCs) for solid tumors, this class of drugs is gaining momentum for the targeted treatment of cancer. Despite significant investment, there are still fundamental issues that are incompletely understood. Three of the recently approved ADCs contain payloads exhibiting bystander effects, where the payload can diffuse out of a targeted cell into adjacent cells. These effects are often studied using a mosaic of antigen positive and negative cells. However, the distance these payloads can diffuse in tumor tissue while maintaining a lethal concentration is unclear. Computational studies suggest bystander effects partially compensate for ADC heterogeneity in tumors in addition to targeting antigen negative cells. However, this type of study is challenging to conduct experimentally due to the low concentrations of extremely potent payloads. In this work, we use a series of 3-dimensional cell culture and primary human tumor xenograft studies to directly track fluorescently labeled ADCs and indirectly follow the payload via an established pharmacodynamic marker (γH2A. X). Using TAK-164, an anti-GCC ADC undergoing clinical evaluation, we show that the lipophilic DNA-alkylating payload, DGN549, penetrates beyond the cell targeted layer in GCC-positive tumor spheroids and primary human tumor xenograft models. The penetration distance is similar to model predictions, where the lipophilicity results in moderate tissue penetration, thereby balancing improved tissue penetration with sufficient cellular uptake to avoid significant washout. These results aid in mechanistic understanding of the interplay between antigen heterogeneity, bystander effects, and heterogeneous delivery of ADCs in the tumor microenvironment to design clinically effective therapeutics.
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