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

项目4.一个发现级功能蛋白质组/代谢组学平台，用于解决 基底膜肿瘤的异质性和寻找有效的治疗组合。 摘要： 最致命的癌症之一胶质母细胞瘤(GBM)的分子图谱揭示了一种分子 沿着一组可用药的核心通路聚集的改变的信号转导级联的景观。然而， 针对这些通路设计的药物在临床上失败了，可能是由于基因和功能上的原因。 肿瘤的异质性。单细胞分析可能以一种方式解决GBM的异质性 指出治疗疾病和抑制耐药性的联合疗法的基本原理。到目前为止，那些 分析仅限于两类。第一个是单细胞基因组和转录组分析，这是 发现级分析，但也很嘈杂，包含有限的功能信息。第二个是单身- 药物靶点产生的改变信号网络的细胞功能蛋白质组学分析。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，一个 想知道每一个细胞的分子密码(基因组)，该细胞的功能 (蛋白质组和代谢组)，以及两者之间的联系--转录组。这需要单人 从基因组学延伸到生物功能的细胞发现科学。我们假设，如此深的和 多层次分析可以揭示基底膜肿瘤如何适应或进化以发展对靶向的耐药性 治疗方法，从而指导为GBM患者设计成功的联合疗法。我们的具体目标是：

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: