Targeting bidirectional signaling in lung stroma and cancer cells

靶向肺基质和癌细胞中的双向信号传导

基本信息

批准号：
10227777
负责人：
ERIC B. HAURA
金额：
$ 47.82万
依托单位：
H. LEE MOFFITT CANCER CTR & RES INST
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10227777
关键词：
Affect Amino Acids Behavior Biological Assay Cell Line Cell Proliferation Cells Chemicals Clinical Coculture Techniques Combined Modality Therapy Complex Data Dissection Drug Combinations Drug Design Drug Modulation Drug Sensitization Drug Targeting Drug Tolerance Drug resistance Engineering Fibroblasts Growth Factor Immunoblotting Immunohistochemistry In Vitro Individual Label Lead Ligation Lung MAP Kinase Gene Malignant Neoplasms Malignant neoplasm of lung Mediating Medical Mission Modeling Oncogenic Pathway interactions Patient-Focused Outcomes Patients Pharmaceutical Preparations Pharmacology Phenotype Population Protein Tyrosine Kinase Proteins Proteome Proteomics Proto-Oncogene Proteins c-akt Public Health RNA Interference Receptor Protein-Tyrosine Kinases Research Resistance Role Signal Pathway Signal Transduction Stromal Cells System Testing Tissue Microarray Tumor Tissue Tyrosine Kinase Inhibitor Tyrosine Phosphorylation United States National Institutes of Health Validation Xenograft Model Xenograft procedure anticancer activity base cancer cell cancer therapy cell type clinical development clinical translation connective tissue-activating peptide design drug action drug development drug sensitivity experimental study in vivo in vivo Model inhibitor/antagonist innovation kinase inhibitor loss of function lung cancer cell neoplastic cell new technology new therapeutic target novel novel drug combination patient derived xenograft model patient population phosphoproteomics protein expression receptor resistance mechanism response synergism tumor microenvironment

项目摘要

PROJECT ABSTRACT Resistance to tyrosine kinase inhibitors (TKI) in lung cancer (LC) is often connected to cancer-associated fibroblasts (CAFs), a major component of the tumor microenvironment (TME). CAFs can cause drug resistance via secretion of growth factors as well as direct contact with cancer cells. Furthermore, tumor cells educate TME fibroblasts to adapt a CAF phenotype, leading to complex and bi-directional signaling between cancer cells and CAFs. Importantly, TKIs do not simply shut down oncogenic signaling, but lead to an adaptive rewiring of the signaling network. In addition, most TKIs have multiple targets, and TKI off-targets can have important effects on efficacy and response, either by restricting or boosting it. This is not limited to cancer cells, but TKIs can simultaneously engage proteins and signaling pathways in cancer as well as stromal cells. Together, these scenarios create a highly dynamic, bi-directional and drug-specific adaptive signaling response of the cancer cell/CAF system, which results in modulation of drug sensitivity and development of drug-tolerant “persister” cell populations. We hypothesize a) that individual TKIs elicit drug- and cell-specific adaptive signaling responses and resistance mechanisms in the LC cell/CAF system, and b) that disrupting bi-directional signaling between LC cells and CAFs can enhance drug sensitivity and eliminate CAF-supported persister cells. Using unbiased, cell type-specific proteomics approaches, we will test these hypotheses in the following specific aims: 1) To characterize mechanisms and roles of fibroblast RTK pathway activation by cancer cells. Genetically activating RTK-driven signaling pathways inside CAFs will allow the characterization of bi-directional signaling of CAFs and LC cells using “cell type-specific labeling using amino acid precursors” (CTAP)-based phosphoproteomics and how it in turn affects LC cell proliferation, invasion and drug sensitivity. Relevant signaling pathways will be evaluated by proximity-ligation assays on patient-derived tissue microarrays (TMAs) and in orthotopic, heterotypic in vivo models. 2) To develop strategies to functionally engage TKI-induced adaptive signaling in CAFs and LC cells. Using CTAP-based chemical and phosphoproteomics, we will determine LC- and CAF-specific adaptive signaling responses and target profiles of clinical TKIs. Functional validation by RNAi and rescue experiments will identify CAF targeting drugs. Synergy with TKI will be evaluated in co-culture and in patient-derived xenograft (PDX) models. The approach is innovative, because it represents a novel way of targeting cancer by developing strategies to simultaneously engage signaling pathways in cancer cells as well as the TME, which are enabled by application of state-of-the-art proteomics. The proposed research is significant as it will transform our understanding of the dynamics and complexity of signaling evoked by LC cell-CAF interactions and the roles of these circuits in drug resistance and sensitization. Further, these studies will reveal conceptually novel opportunities for clinical development of targeted combination therapies for a patient population with a significant unmet medical need.

项目摘要肺癌（LC）中对酪氨酸激酶抑制剂（TKI）的抗性通常与癌症相关成纤维细胞（CAFS），肿瘤微环境（TME）的主要组成部分。 CAF可以通过生长因子的分泌以及与癌细胞的直接接触。此外，肿瘤细胞教育TME 成纤维细胞适应CAF表型，从而导致癌细胞和咖啡馆。重要的是，TKIS不仅会关闭致癌信号，而是导致自适应重新布线信号网络。此外，大多数TKI都有多个目标，而TKI脱离目标可以具有重要的效果通过限制或提高效力和响应。这不仅限于癌细胞，但是TKI可以同样，在癌症和基质细胞中参与蛋白质和信号通路。在一起，这些场景创造了癌症的高度动态，双向和药物特异性的自适应信号反应细胞/CAF系统，导致药物敏感性和耐药性“迫害”的发展细胞种群。我们假设a）单个TKI会引起药物和细胞特异性自适应信号传导 LC单元/CAF系统中的响应和电阻机制，b）破坏双向 LC细胞和CAF之间的信号传导可以增强药物敏感性并消除CAF支持的持久性细胞。使用公正的细胞类型特异性蛋白质组学方法，我们将在以下测试这些假设具体目的：1）表征癌细胞激活成纤维细胞RTK途径的机制和作用。 CAF内部的基因激活RTK驱动的信号通路将允许表征双向使用“使用氨基酸前体的细胞类型特异性标记”（CTAP）基于CAF和LC细胞的信号传导（CTAP）磷蛋白质组学及其如何影响LC细胞的增殖，侵袭和药物敏感性。相关的信号通路将通过对患者来源的组织微阵列（TMA）的接近结合测定进行评估在原位，异型型在体内模型中。 2）制定策略以在功能上吸引TKI引起 CAF和LC细胞中的自适应信号传导。使用基于CTAP的化学和磷酸蛋白质组学，我们将确定临床TKI的LC和CAF特异性自适应信号反应和目标谱。功能 RNAi和救援实验的验证将鉴定靶向药物的CAF。与TKI协同作用将在共培养和患者衍生的Xenographic（PDX）模型中进行评估。这种方法是创新的，因为它通过制定简单地参与信号通路的策略来代表一种靶向癌症的新型方式在癌细胞和TME中，通过应用最先进的蛋白质组学启用了TME。提议研究很重要，因为它将改变我们对信号传导的动态和复杂性的理解 LC细胞-CAF相互作用以及这些电路在耐药性和敏感性中的作用引起的。此外，这些研究将揭示有针对性组合的临床发展的概念上新的机会对患者群体的疗法，具有明显的未满足医疗需求。