MicroRNA-Based Detection of Barriers to Melanoma Progression

基于 MicroRNA 的黑色素瘤进展障碍检测

基本信息

批准号：
9349379
负责人：
Robert Laird Judson-Torres
金额：
$ 39.63万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-12 至 2019-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9349379
关键词：
Address Alpha Cell Apoptosis Artificial skin Automobile Driving BRAF gene Biological Assay Cancer Biology Cancerous Cell Cycle Regulation Cell Line Cell Proliferation Cell Therapy Cells Collaborations Complex Detection Development Disease Dissection Event Failure Future Gene Combinations Gene Targeting Genes Genetic Genetic Transcription Genome Genomics Goals Growth Heterogeneity Human Human Cell Line Individual Knowledge Lead Lesion Life Location Malignant Neoplasms Mammalian Cell Mammals Measures Melanoma Cell Messenger RNA Metabolism Methods MicroRNAs Modeling Molecular Molecular Profiling Morphology Mus Mutation Neoplasm Metastasis Normal Cell Organism Patients Phenotype Phylogenetic Analysis Physiological Physiology Population Population Analysis Population Heterogeneity Primary Lesion Property Proteins Regulation Reporting Research Research Project Grants Sampling Series Signal Transduction Skin Stimulus Structure System Techniques Technology Testing Time Translations Tumor stage Work accurate diagnosis actionable mutation advanced disease base cell type experimental study genome-wide human disease improved inhibitor/antagonist insight mRNA Differential Displays mRNA Stability melanocyte melanoma neoplastic cell novel novel strategies personalized medicine prevent programs public health relevance reconstitution senescence therapy resistant tool tumor tumor progression tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): An extraordinary aspect of complex multicellular organisms, such as mammals, is the diversity of different types of cells that arise from the same genome. Each type of cell, or cell state, differs drastically in morphology, function, and physiology and must be carefully regulated during both the development and the daily life of the organism. This includes both tight control of cell state transitions and the stabilization of cell states against external stimuli and internal disturbances, including genomic mutations. Underlying specific cell states are networks of expressed genes. Although it is now commonplace to measure the expression of every gene within a population of cells with a single experiment, little is known about how the individual genes within a large network function together. This is especially true in complex human diseases, such as cancer, where the population of cells from a single tumor can contain many different cell states. The objective of this project is to both identify and to functionally dissect networks of interacting genes that stabilize melanocytes and early- stage melanomas against transitions into more advanced disease states. The central approach is microRNA- based detection of functional gene networks. MicroRNAs (miRNAs) are transcribed from the genome but do not encode for proteins, rather regulating the translation and stability of mRNA networks. It has recently been shown that miRNAs serve as excellent tools for identifying networks of genes that regulate cell state transitions. These co-regulated networks of genes are enriched for genetic interactions, which can be identified using mapping techniques recently adapted for mammalian cells from their previous extensive use in single cell organisms. In the first aim of this application, these methods will be used to investigate the relationship between different melanoma driver mutations (those changes to the genome that initiate melanoma progression) and the networks of genes that stabilize against further progression, testing the hypothesis that different initiatig events result in distinct multigenic barriers to tumorigenesis. MiRNAs known to advance melanoma will be introduced into a panel of mouse melanocytes with different driver mutations. When progression is induced, the network of genes targeted by the miRNA will be experimentally determined and their individual function and genetic interactions investigated. In the second aim, the miRNA-targeted networks that correlate with human melanoma progression in both expression and function will be tested using primary patient samples and reconstituted skin culture. In the third aim, populations of tumor cells will be analyzed on the single cell leve. Each cell will be assayed for its ability to progress or to transition into a therapy-resistant cel state, and the miRNA profiles associated with each transition will be measured. Collectively, these approaches will improve our knowledge of the networks of genes that work together to prevent melanoma progression, increasing our potential to conduct meaningful personalized therapies for this deadly disease.

描述（由申请人提供）：复杂的多细胞生物体（例如哺乳动物）的一个非凡方面是来自同一基因组的不同类型细胞的多样性。每种类型的细胞或细胞状态在形态、功能和生理学方面都有很大差异，在生物体的发育和日常生活过程中必须仔细调节。这包括严格控制细胞状态转变以及稳定细胞状态以抵抗外部刺激和内部干扰（包括基因组突变）。特定细胞状态的基础是表达基因的网络。尽管现在通过一次实验来测量细胞群中每个基因的表达已经很常见，但对于大型网络中的各个基因如何共同发挥作用却知之甚少。在复杂的人类疾病中尤其如此，例如癌症，来自单个肿瘤的细胞群可以包含许多不同的细胞状态。该项目的目标是识别和功能性剖析相互作用基因的网络，这些基因可以稳定黑色素细胞和早期黑色素瘤，防止其转变为更晚期的疾病状态。核心方法是基于 microRNA 的功能基因网络检测。 MicroRNA (miRNA) 从基因组转录而来，但不编码蛋白质，而是调节 mRNA 网络的翻译和稳定性。最近的研究表明，miRNA 是识别调节细胞状态转变的基因网络的优秀工具。这些共同调控的基因网络丰富了遗传相互作用，可以使用最近适用于哺乳动物细胞的作图技术来识别它们，这些技术以前在单细胞生物中广泛使用。在本申请的第一个目标中，这些方法将用于研究不同黑色素瘤驱动突变（启动黑色素瘤进展的基因组变化）与稳定防止进一步进展的基因网络之间的关系，测试不同启动突变的假设事件导致了肿瘤发生的明显多基因障碍。已知可促进黑色素瘤发生的 miRNA 将被引入一组具有不同驱动突变的小鼠黑色素细胞中。当诱导进展时，将通过实验确定 miRNA 靶向的基因网络，并研究它们的个体功能和遗传相互作用。在第二个目标中，将使用原始患者样本和重建的皮肤培养物来测试与人类黑色素瘤的表达和功能进展相关的 miRNA 靶向网络。第三个目标是在单细胞水平上分析肿瘤细胞群。将检测每个细胞进展或转变为治疗抵抗细胞状态的能力，并测量与每次转变相关的 miRNA 谱。总的来说，这些方法将提高我们对共同预防黑色素瘤进展的基因网络的了解，增加我们对这种致命疾病进行有意义的个性化治疗的潜力。