Core 1: Mouse Model and Tissue Biobank Core

小鼠和临床肿瘤(MCT)核心服务。项目摘要 抗PD-L1与BRAFV600MUT和MEK抑制剂同时联合(所谓的三联疗法)， 在早期临床数据中，这种药物似乎是有益的，最近已被批准用于BRAFV600-MUT黑色素瘤患者 (13)。这是第一个被批准的突变免疫联合靶向治疗，但关于这个三胞胎的数据似乎喜忧参半， 其他试验没有达到关键终点(14)，这表明同时联合并不是最佳的。 重要的是，回顾临床数据分析和使用同基因模型的体内治疗建模 小鼠黑色素瘤显示在MAPKi结合前引入抗PD-1/L1(±抗CTLA-4)方案 通过增强MAPKi的持久性(并克服天生的抵抗力)来增强三联疗法的疗效 免疫检查站封锁)(12)。因此，认识到免疫因素导致了对MAPKi治疗的抵抗 为基于免疫的策略打开大门，例如过继细胞疗法(ACT)(项目1，目标3)，如 预防MAPKi耐药的组合药物。 在这一最新进展的基础上，这个小鼠和临床肿瘤(MCT)核心将提供项目1和2模型 和临床肿瘤，以获得肿瘤免疫微环境的多尺度(时空)概况(时间) 早期和晚期单剂(MAPKi或抗PD-1/L1)治疗(项目1，目标1)。这些“早期”数据将提供 对项目1、目标2中正在开发的基于代理的模型(ABM)的输入和“后期”数据将有助于验证 预测。我们将比较成功的组合策略和不成功的组合策略 组合策略，教授ABM关于优化的TME。该核心还将提供临床组织用于 翻译验证(项目1，目标4)和肿瘤模型以测试预测的新联合疗法 (项目2，目标3)。

Murine and Clinical Tumors (MCT) Core services. Project Summary The simultaneous combination of anti-PD-L1 with BRAFV600MUT and MEK inhibitors (so-called “triplet” therapy), in early clinical data, appears beneficial and has recently been approved for patients with BRAFV600MUT melanoma (13). This is first mutation-immune co-targeted therapy to be approved, but the data on this triplet appear mixed, with other trials not meeting key endpoints (14), suggesting that simultaneous combination is not optimal. Importantly, retrospective clinical data analysis and in vivo therapeutic modeling using syngeneic models of murine melanoma showed that a regimen of anti-PD-1/L1 (± anti-CTLA-4) lead-in before MAPKi combination augments the efficacy of triplet therapy by enhancing MAPKi durability (and overcoming innate resistance to immune checkpoint blockade) (12). Thus, the realization that immune factors drive resistance to MAPKi therapy opens the door to immune-based strategies, such as adoptive cell therapy (ACT) (Project 1, Aim 3), as combinatorial agents to prevent MAPKi resistance. Building on this recent progress, this Murine and Clinical Tumors (MCT) Core will offer Projects 1 and 2 model and clinical tumors to obtain multi-scale (spatiotemporal) profiles of the tumor immune microenvironment (TIME) early and late on single-agent (MAPKi or anti-PD-1/L1) therapy (Project 1, Aim 1). These “early” data will provide inputs to the agent-based models (ABMs) being developed in Project 1, Aim 2, and “late” data will help validate predictions. Profiles from more successful combination strategies will be compared against less successful combination strategies to teach the ABM on optimized TMEs. This core will also offer clinical tissues for translational validation (Project 1, Aim 4) and tumor models to test predicted novel combination therapies (Project 2, Aim 3).