Modeling tumor-stroma crosstalk in lung cancer to identify targets for therapy

模拟肺癌中的肿瘤-基质串扰以确定治疗靶点

基本信息

批准号：
9308914
负责人：
Vivek Mittal
金额：
$ 41.2万
依托单位：
METHODIST HOSPITAL RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-07-02 至 2020-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9308914
关键词：
Address Autocrine Communication Beds Biology Bone Marrow Cancer Patient Candidate Disease Gene Cells Clinic Clinical Clinical Trials Complement Computer Simulation Computer software Data Development Dimensions Drug Targeting Drug-sensitive Employee Strikes Encapsulated Endothelial Cells Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor Epithelial Epithelial Cells Erlotinib Gefitinib Genes Genetic Genetically Engineered Mouse Growth Harvest Human Impairment In Vitro Individual Infiltration Ligands Lung MMP14 gene Malignant neoplasm of lung Mediating Modeling Mus Mutation Myelogenous Myeloid Cells Non-Small-Cell Lung Carcinoma Outcome Pathway interactions Patients Pharmacology RNA Receptor Protein-Tyrosine Kinases Resistance Role Signal Pathway Signal Transduction Software Tools Source Specimen Stromal Cells Study models Therapeutic Tissues Treatment Efficacy Validation Visualization software autocrine base cancer cell carcinogenesis cell stroma cell type conventional therapy crizotinib deep sequencing design genome wide association study improved in vitro Assay inhibitor/antagonist insight kinase inhibitor macrophage molecular targeted therapies monocyte mouse model neoplastic cell network models neutrophil novel novel therapeutics paracrine public health relevance receptor targeted treatment therapeutic target therapy resistant transcriptome transcriptome sequencing treatment response tumor tumor growth tumor progression

项目摘要

DESCRIPTION (provided by applicant): There is an unmet need for molecularly targeted therapies for the treatment of non-small cell lung cancer (NSCLC). Taking into account the emerging paradigm that the reprogrammed intratumoral stromal cells contribute to carcinogenesis, we have employed integrated experimental and computational approaches to identify tumor-stroma crosstalk pathways that drive NSCLC progression. To explore paracrine/autocrine crosstalk, we performed RNA deep sequencing analysis of specific cellular myeloid and epithelial compartments isolated from freshly harvested lungs of NSCLC patients, and a genetically engineered mouse model of NSCLC. We compared transcriptomes of intratumoral myeloid cells (monocytic, neutrophils and macrophages) and tumor epithelial cells with their counterparts within matched adjacent non-neoplastic tissue. In this application, we will develop a multi-cellular crosstalk signaling network modeling and visualization software tool (Aim 1) and apply this model to multi-cellular RNA-seq data to identify tumor-stroma crosstalk pathways; genes involved in these signaling mechanisms will be considered potential candidates that mediate NSCLC tumor progression and will undergo rapid validation using in vitro assays (Aim 2). Finally, we will determine the function of selected crosstalk pathways in NSCLC progression and in mediating therapeutic resistance (Aim 3). In summary, this study explores the relatively understudied tumor-stroma crosstalk pathways as a largely untapped source of drug targets and has tremendous potential for the development of novel therapeutic strategies that target tumor-stroma interactions and may complement existing treatments that target cancer cells.

描述（由适用提供）：对非小细胞肺癌（NSCLC）治疗的分子靶向疗法有未满足的需求。考虑到重新编程的肿瘤内基质细胞有助于致癌的新兴范式，我们采用了综合的实验和计算方法来识别驱动NSCLC进展的肿瘤 - 基质串扰途径。为了探索旁分泌/自分泌串扰，我们对从NSCLC患者的新鲜收获的肺以及NSCLC的基因工程小鼠模型进行了对特定细胞髓样和上皮室的RNA深度测序分析。我们比较了肿瘤内髓样细胞（单核细胞，嗜中性粒细胞和巨噬细胞）和肿瘤上皮细胞的转录组与在匹配的相邻的非肿瘤组织中的对应物。在此应用程序中，我们将开发多细胞串扰信号网络建模和可视化软件工具（AIM 1），并将该模型应用于多细胞RNA-seq数据以识别肿瘤 - 基质串扰途径；这些信号传导机制涉及的基因将被视为介导NSCLC肿瘤进展的潜在候选，并使用体外测定法（AIM 2）进行快速验证。最后，我们将确定选定的串扰途径在NSCLC进展和介导治疗抗性中的功能（AIM 3）。总而言之，这项研究探讨了相对理解的肿瘤串扰途径，作为在很大程度上未开发的药物靶标的来源，并具有巨大的潜力，可以开发出靶向肿瘤细胞相互作用的新型治疗策略，并可能补充靶向癌细胞的现有治疗方法。