Abstract
Abstract Background: Immune checkpoint inhibitors currently represent the most promising cancer therapeutics to produce durable responses. Many studies have highlighted checkpoint inhibitors' targets for future monotherapies or combination therapies. However, due to the complexity of tumor microenvironment, different types of cells exhibit different reaction time and order. To understand the MoA of immune checkpoint inhibitors in cell or animal models, time-series analysis will help select proper PD sampling time, as well as administration time & order in combination therapy. However, such analysis has limited application in syngeneic tumor models in the early stage of drug treatment due to the small tumor volumes. Methods and Results: In this study, we combined NanoString technology and flow cytometry in an in-vivo efficacy study to explore the therapeutic response mechanism in mouse breast cancer EMT-6 model by the combinational treatment with anti-PD1 and an undisclosed compound A. Through time-course sampling of tumor tissues of EMT-6 xenograft tumors in the early stage of treatment, we found that anti-PD1 could enhance antigen-presentation and T cell priming as a single agent, and this effect could be enhanced by combination with compound A. In addition, we found the change of antigen-presentation induced by anti-PD1 occurs at RNA level, but not at protein level by flow cytometry analysis, which might imply to employ different time points to combine with RNA-targeted or protein-targeted drugs on T cell priming. Summary: We have developed a time-series analysis combining in vivo efficacy study and NanoString technology with flow cytometry, to evaluate the dynamic changes of TME after immune checkpoint blocker treatment. This can be a powerful method to reveal time-dependent drug-induced pharmacodynamic changes, and help us to select the best time course for combination therapy. Citation Format: Jingjing Wang, Panpan Wang, Wenli Zhang, Qiyao Zhang, Qingyang Gu, Qunsheng Ji. Multi-dimensional time-series analysis to reveal pharmacodynamic changes induced by immunotherapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6674.
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