Rewiring the myeloid cell response to adjuvants to improve tumor control

这项提议的关键初步数据是，与公认的教条相反，在暴露于 内源性免疫佐剂MyD88向巨噬细胞传递负面信号，通过以下方式限制肿瘤控制 放射疗法。我们证明，在免疫原性低的肿瘤中，巨噬细胞被重新连接如下 暴露在死亡的癌细胞中，从而抑制肿瘤免疫环境的多种特征。 这包括T细胞控制残留疾病的能力，以及树突状细胞的成熟。这样做的目的是 建议是了解这种抑制发生的机制，确定对 巨噬细胞抑制，并利用这一点来识别对电流反应差的患者群体 治疗。我们假设暴露在濒临死亡的细胞中重新连接巨噬细胞信号，从而先天 MyD88的激活抑制了局部的肿瘤免疫。这项研究的具体目的是：1.测试 假设MyD88的缺失阻止了NFKB驱动的抗炎基因转录并导致 增加IRF3驱动的干扰素转录；2：检验通过MerTK介导的信号重新连接的假设 巨噬细胞改变对肿瘤环境中限制免疫功能的佐剂的反应；以及3： 测试MyD88基因表达模式与不良患者预后相关的假设。我们的研究 设计结合了CT引导的多种真实胰腺肿瘤模型的放射治疗，并使用 放射治疗剂量和分级的范围。这些与独特的基因敲除和分析相结合，使我们能够 在体外和体内鉴定不同的髓系反应。我们对临床样本的分析使用了高质量 生物信息学方法，使我们能够评估肿瘤环境对生物反应的影响 在病人样本中加入天然佐剂。

The critical preliminary data for this proposal is that contrary to the accepted dogma, following exposure to endogenous immune adjuvants MyD88 delivers a negative signal to macrophages that limits tumor control by radiation therapy. We demonstrate that in poorly immunogenic tumors, macrophages are rewired following exposure to dying cancer cells such that they suppress multiple features of the tumor immune environment. This includes the ability of T cells to control residual disease, and dendritic cell maturation. The aim of this proposal is to understand the mechanisms by which this suppression occurs, identify the regulation of macrophage suppression, and use this to identify patient populations that will respond poorly to current therapies. We hypothesize that exposure to dying cells rewires macrophage signaling such that innate activation of MyD88 suppresses local tumor immunity. The specific aims of this study are to 1: Test the hypothesis that loss of MyD88 prevents NFKB driven-anti-inflammatory gene transcription and results in increased IRF3 driven IFN transcription; 2: Test the hypothesis that signaling through Mertk-mediated ‘rewiring’ of macrophages changes the response to adjuvants limiting immune function in the tumor environment; and 3: Test the hypothesis that MyD88 patterns of gene expression are linked to poor patient outcome. Our study design incorporates CT-guided radiation therapy of multiple authentic pancreatic tumor models and using a range of RT doses and fractionations. These are combined with unique knockouts and assays that allow us to identify divergent myeloid responses in vitro and in vivo. Our analyses of clinical samples use high quality bioinformatic approaches that allow us to evaluate effect of the tumor environment on the biological response to innate adjuvants in patient samples.