Project 4: A Discovery-Level Functional Proteomics/Metabolomics Platform for Resolving the Heterogeneity of GBM Tumors and Identifying Effective Therapy Combinations

项目4：用于解决GBM肿瘤异质性并识别有效治疗组合的发现级功能蛋白质组学/代谢组学平台

• 批准号: 9149720
• 负责人: James R. Heath
• 金额: $ 56.45万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9149720
• 关键词: Animal Model; Apoptosis; Behavior; Biochemical Pathway; Biological; Biological Assay; Biological Process; Biology; Cancer Center; Cells; Clinic; Code; Combined Modality Therapy; Data; Detection; Disease; Drug Combinations; Drug Design; Drug Targeting; Genetic; Genome; Genomics; Glioblastoma; Glycolysis; Heterogeneity; In Vitro; Kinetics; Malignant Neoplasms; Measurement; Metabolic; Modeling; Molecular; Molecular Profiling; Nanotechnology; Oxidative Phosphorylation; Pathway interactions; Patients; Pharmaceutical Preparations; Population; Positron-Emission Tomography; Proteins; Proteome; Proteomics; Reporter; Resected; Resistance; Resistance development; Science; Signal Transduction; Signaling Protein; Staining method; Stains; System; Testing; Tissues; Tumor Volume; cancer cell; design; effective therapy; fluorodeoxyglucose positron emission tomography; human subject; in vivo; individual patient; insight; metabolome; metabolomics; nanosystems; reconstruction; response; single cell analysis; subcutaneous; targeted treatment; tool; transcriptome; tumor; tumor heterogeneity

Project 4. A Discovery-Level Functional Proteomics/Metabolomics Platform for Resolving the Heterogeneity of GBM Tumors and Identifying Effective Therapy Combinations. ABSTRACT: Molecular profiling of glioblastoma (GBM) - one of the most lethal of all cancers - has revealed a molecular landscape of altered signal transduction cascades that cluster along a set of druggable core pathways. Yet, drugs designed to target these pathways have failed in the clinic, presumably due to the genetic and functional heterogeneity of the tumor. Single cell analyses may resolve the heterogeneity of GBM in a manner that can point to rationale combination therapies for treating the disease and suppressing resistance. So far, those analyses have been limited to two classes. The first is single-cell genome and transcriptome analysis, which is a discovery-level analysis, but is also noisy and contains limited functional information. The second is single- cell functional proteomic analysis of the altered signaling networks from which drug targets emerge. This tool can provide powerful new ways to look at known biology, but it does not permit discovery. In principle, one wants to know, for each single cell, the molecular code of the cell (the genome), the functionality of that cell (the proteome and metabolome), and the connection between the two – the transcriptome. This requires single cell discovery science that extends from genomics to biological function. We hypothesize that such a deep and multi-level analysis can unveil how GBM tumors adapt or evolve to develop resistance against targeted therapies, thus guiding the design of successful combination therapies for GBM patients. Our specific aims are:

项目4。一个发现级的功能蛋白质组学/代谢组学平台，用于解决 GBM肿瘤的异质性和鉴定有效的治疗组合。 摘要： 胶质母细胞瘤（GBM）-所有癌症中最致命的一种-的分子分析揭示了一种分子 改变的信号转导级联景观沿着沿着一组可药物化的核心途径聚集。然而， 针对这些途径设计的药物在临床上失败了，可能是由于遗传和功能上的原因。 肿瘤的异质性。单细胞分析可以以一种能够 指出了治疗疾病和抑制耐药性的合理组合疗法。到目前为止，那些 分析仅限于两类。首先是单细胞基因组和转录组分析， 这是一个发现级的分析，但也是嘈杂的，包含有限的功能信息。第二个是单身-- 细胞功能蛋白质组学分析药物靶点产生的改变的信号网络。此工具 可以提供强大的新方法来看待已知的生物学，但它不允许发现。原则上一 想知道每个细胞的分子密码（基因组），细胞的功能 (the蛋白质组和代谢组），以及两者之间的联系-转录组。这需要单 从基因组学到生物功能的细胞发现科学。我们假设，如此深的， 多水平分析可以揭示GBM肿瘤如何适应或进化以产生对靶向药物的抗性， 因此，指导GBM患者成功的联合治疗的设计。我们的具体目标是：