(PQ7)Multi-scale Analysis of Tumor Microenvironment Heterogeneity

(PQ7)肿瘤微环境异质性多尺度分析

• 批准号: 9378269
• 负责人: DEAN W FELSHER
• 金额: $ 72.94万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-07 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9378269
• 关键词: Acute; Archives; B-Lymphocytes; Behavior; Biological Markers; Biological Models; Blood; Cell Communication; Cells; Clinical; Clinical Research; Collaborations; Cytometry; Data; Dendritic Cells; Dependency; Detection; Effector Cell; Exhibits; Flow Cytometry; Frequencies; Gastroenterologist; Gene Expression; Gene Expression Profiling; Genes; Grant; Heterogeneity; Human; Human Resources; Imaging technology; Immune; Immune response; Immunotherapy; In Situ; Innate Immune System; Institutional Review Boards; Kinetics; Laboratories; Liver; Liver neoplasms; Location; MYC gene; Maintenance; Malignant neoplasm of liver; Measures; Mediating; Methods; Modeling; Molecular; Multiplexed Ion Beam Imaging; Neoplasm Metastasis; Oncogenes; Pathogenesis; Pathologic; Pathology; Population; Primary carcinoma of the liver cells; Protocols documentation; Recruitment Activity; Regulation; Research Personnel; Role; Specimen; Stream; Stromal Cells; System; T-Lymphocyte Subsets; Technology; Tetracyclines; The Cancer Genome Atlas; Time; Tissue Microarray; Training; Transgenic Mice; Transgenic Organisms; Tumor Tissue; Tumor stage; Universities; Work; adaptive immune response; base; bioluminescence imaging; cancer regression; cell motility; cell type; cytokine; data modeling; ex vivo imaging; imaging modality; imaging program; immune activation; in vivo; in vivo imaging; intravital microscopy; macrophage; mathematical model; member; molecular imaging; mouse model; neoplastic cell; novel; oncogene addiction; outcome forecast; predictive modeling; professor; prospective; reconstitution; tool; treatment response; tumor; tumor growth; tumor initiation; tumor microenvironment; tumor progression; tumorigenesis

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.

抽象的 肿瘤发生与异质性变化与先天和适应性免疫作用的变化有关 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。我们和其他人表明，癌基因 MYC COPT和/或颠覆这些免疫效应，从而避免免疫检测并促进肿瘤 微环境燃烧肿瘤的生长；但是，这似乎是以必要的方式发生的 可以预见的是，肿瘤高度容易受到急性致癌基因灭活的影响，从而使免疫作用成为 被激活，从而导致巨大的肿瘤回归，这一现象称为“癌基因成瘾”。因此， 我们假设这些不同宿主免疫效应的识别，数量和定位 在肿瘤发生和肿瘤消退期间的肿瘤微环境中，将鉴定出细胞生物标志物 将预测对癌基灭活的治疗反应。我们的方法是采用TET系统 MYC诱导的肝细胞癌（HCC）和MYC/Twist1诱导的模型的调节模型 转移性HCC。然后，要使用：FACS/CYTOF，codex/mibi，ivm/bli和基因表达/cibersort 鉴定细胞效应以及标志性基因和代谢产物。首先，我们的Myc-转基因小鼠模型 诱导的HCC已被我们和其他许多人广泛使用。使用TET系统，我们的模型展览 对Myc癌基因基因表达的精确可逆和滴定控制。发生肿瘤形成 随着时间的流逝，癌基因依赖性导致肿瘤回归，高度依赖于免疫 回复。此外，最近我们生成了一个未发表的鼠标模型，这表明了Myc- 与转基因扭曲结合时，诱导的肝肿瘤通过血流迅速转移。 表达。 Twist1先前与转移有关。我们获得了初步结果 显示转移与巨噬细胞募集有关，并且似乎需要募集。最后，我们发现了 我们可以使用可用的人类TCGA数据来识别与 人HCC的发病机理。这，肿瘤发生的所有阶段似乎都取决于基质和 免疫反应（初始，进展，转移，回归），代表了评估肿瘤的独特工具 微环境异质性。我们有三个目标：首先，剖析适应性的机制 先天免疫系统促进了HCC的进展，转移和回归。第二，确定 使用体内（IVM和BLI）成像的上述细胞群体的动力学和定位 特别强调细胞 - 细胞相互作用的技术，第三，评估这些发现的能力 对人HCC的临床行为和预后做出预测。