(PQ7)Multi-scale Analysis of Tumor Microenvironment Heterogeneity

摘要 肿瘤的发生与先天性和适应性免疫效应物的异质性进化变化有关， 肿瘤微环境记录、识别和量化这些细胞和分子变化 可以改变我们对肿瘤发生的理解。我们和其他人已经表明，癌基因，如 MYC会吸收和/或破坏这些免疫效应物，从而逃避免疫检测并促进肿瘤生长。 微环境，燃料肿瘤生长;然而，这似乎发生的方式， 可以预见的是，肿瘤极易受到急性癌基因失活的影响，从而使免疫效应物变得 激活，从而导致戏剧性的肿瘤消退，这种现象称为“癌基因成瘾”。因此，我们认为， 我们假设这些不同的宿主免疫效应物的鉴定、定量和定位 在肿瘤发生和肿瘤消退过程中的肿瘤微环境中， 将预测对癌基因失活的治疗反应。我们的方法是采用泰特系统 MYC诱导的肝细胞癌（HCC）的调节模型和MYC/Twist 1诱导的肝细胞癌（HCC）的模型。 转移性HCC。然后，利用：FACS/CyTOF、CODEX/MIBI、IVM/BLI和基因表达/CIBERSORT， 鉴定细胞效应物和标志基因和代谢物。首先，我们的MYC转基因小鼠模型- 诱导的HCC已被我们和许多其他人广泛使用。采用泰特系统，我们的模型展览 MYC癌基因的基因表达的精确可逆和可滴定控制。发生肿瘤形成 随着时间的推移，癌基因依赖性导致肿瘤消退，这高度依赖于免疫系统。 反应此外，最近我们建立了一个未发表的小鼠模型，戏剧性地说明了MYC- 当与转基因Twist 1结合时， 表情Twist 1以前与转移有关。我们已经获得了初步结果， 显示转移与巨噬细胞的募集有关，并且似乎需要巨噬细胞的募集。最后，我们发现 我们可以使用现有的人类TCGA数据来识别与肿瘤相关的潜在细胞效应子。 人HCC的发病机制。因此，肿瘤发生的所有阶段似乎都依赖于间质细胞， 免疫应答（初始、进展、转移、消退），代表了评估肿瘤- 微环境异质性我们有三个目标：第一，剖析适应性的机制， 和先天免疫系统促进HCC的进展，转移和消退;第二，确定 使用体内（IVM和BLI）成像的上述鉴定的细胞群的动力学和定位 技术，特别强调细胞间的相互作用，第三，评估这些发现的能力， 预测人类HCC的临床表现和预后。

ABSTRACT Tumorigenesis is associated with heterogeneous evolving changes of innate and adaptive immune effectors in the tumor microenvironment. Recording, identifying and quantifying these cellular and molecular changes could transform our understanding of tumorigenesis. We and others have shown that oncogenes, such as MYC co-opt and/or subvert these immune effectors, thereby evading immune detection and promoting a tumor microenvironment that fuels tumor growth; however, this appears to occur in a manner that necessarily and predictably leaves tumors highly vulnerable to acute oncogene inactivation, whereby immune effectors become activated, thereby resulting in dramatic tumor regression, a phenomenon called “oncogene addiction”. Hence, we hypothesize that the identification，quantification and localization of these different host immune effectors in the tumor microenvironment during tumorigenesis and tumor regression will identify cellular biomarkers that will predict therapeutic response to oncogene inactivation. Our approach will be to employ the Tet system regulated model of MYC-induced hepatocellular carcinoma (HCC) and MYC/Twist1-induced model of metastatic HCC. Then, to utilize: FACS/CyTOF, CODEX/MIBI, IVM/BLI, and Gene expression/CIBERSORT to identify cellular effectors and hallmark genes and metabolites. First, our transgenic mouse model of MYC- induced HCC has been widely utilized by us and many others. Employing the Tet System, our model exhibit precise reversible and titrable control of the gene expression of the MYC oncogene. Tumor formation occurs slowly over time, oncogene-dependency results in tumor regression that is highly dependent on the immune response. Further, recently we generated a not published mouse model dramatically illustrating that MYC- induced liver tumors rapidly metastasize through the blood stream when combined with transgenic Twist1 expression. Twist1 has previously been associated with metastasis. We have obtained preliminary results that show metastasis is associated with and appears to require recruitment of macrophages. Finally, we have found that we can use human TCGA data available to identify potential cellular effectors associated with the pathogenesis of human HCC. Thus, all stages of tumorigenesis appear to be dependent on the stromal and immune response (initial, progressed, metastatic, regressed) and represent a unique tool to assess tumor- microenvironment heterogeneity. We have three aims: first, to dissect the mechanism by which the adaptive and innate immune system facilitates HCC progression, metastasis, and regression; second, to determine the kinetics and localizations of the above identified cell populations using in vivo (IVM and BLI) imaging technologies with special emphasis on cell-cell interactions and, third, to assess the ability of these findings to make predictions regarding the clinical behavior and prognosis of human HCC.