Proteomics

摘要 蛋白质组学核心（核心3）的首要目标是提供最先进的，基于质谱的， 蛋白质组学和磷酸蛋白质组学数据和分析，以支持项目1-3。人类的基因改变 在过去的十年里，癌症已经被基因组学景观研究系统地绘制出来，然而， 这些改变对功能蛋白质组的影响还知之甚少。深层鳞片、肿块 基于质谱（MS）的蛋白质组学数据与基因组学数据（“蛋白质基因组学”）相结合， 显示出提高了识别由体细胞DNA变体或DNA 与单独的基因组表征相比，拷贝数改变（CNA）有助于缩小靶向 选择潜在的治疗干预。单靠蛋白质组学，特别是对蛋白质组学进行深入的定量分析， 翻译后修饰（PTM）提供了与疾病病理生理学相关的信号传导信息， 在很大程度上对基因组学是不透明的。 核心3将应用我们开发的基于微型质谱的蛋白质组学技术， 高度多重稳定同位素质量标记（TMT 16-plex），用于蛋白质组的精确相对定量 和磷酸化蛋白质组的非常少量的非常深的覆盖范围的研究转化的慢性 淋巴细胞性白血病（CLL）到里希特综合征（RS）。由此产生的蛋白质组数据，包括关键的 定量和位点特异性修饰信息，将与个性化的基因组数据整合， 生物信息学工具已被集成到基于云的管道PANOTOPLAN中。多组学聚类 并进行分析，以确定整个基线的整合蛋白基因组的内在结构， 处理的样品。我们将提取驱动潜在簇结构的蛋白质基因组学特征， 执行路径级分析以进一步表征CLL和RS样品中的每个簇。拷贝数与 将进行mRNA、蛋白质和磷蛋白的相关性，以确定顺式和反式调节基因。 将研究患者和小鼠模型中治疗反应的途径和分子机制。 使用单样本基因集富集分析（ssGSEA）和PTM标签富集分析进行探索 （PTM-SEA）将用于对生成的磷酸化数据进行途径分析。 为了能够更快速和特异性地分析从蛋白质和磷酸化肽中产生的感兴趣的靶标， 在发现实验中，蛋白质组学核心将开发高灵敏度的靶向MS分析， 项目1-3。所开发的分析将使用稳定的同位素标记标准品进行明确的鉴定， 定量并应用于天然和药物干扰状态下的人体生物样本和临床前样本。

Abstract The overarching goal of the Proteomics Core (Core 3) is to provide state-of-the-art, mass spectrometry-based- proteomics and phosphoproteomics data and analyses in support of Projects 1-3. Genetic alterations in human cancer have been systematically mapped by genomics landscape studies in the past decade, however, the direct consequences of these alterations on the functional proteome are poorly understood. Deep scale, mass spectrometry (MS)-based proteomic data when integrated with genomic data (`proteogenomics') have been shown to improve specificity for identifying cancer-relevant pathways triggered by somatic DNA variants or DNA copy number alterations (CNAs) compared to genomic characterization alone, and help to narrow target selection for potential therapeutic intervention. Proteomics alone, especially with deep, quantitative profiling of posttranslational modifications (PTM) provides information on signaling related to disease pathophysiology that are largely opaque to genomics. Core 3 will apply micro-scaled mass spectrometry-based proteomics technologies we have developed that utilize highly multiplexed stable-isotope mass tagging (TMT 16-plex) for precise relative quantification of the proteome and phosphoproteome of very small amounts with very deep coverage for the study of transformation of chronic lymphocytic leukemia (CLL) to Richter's Syndrome (RS). The resulting proteomic data, including the critical quantitative and site-specific modification information, will be integrated with personalized genomic data using bioinformatics tools that have been integrated into the cloud-based pipeline PANOPLY. Multi-omics clustering and analysis will be done to define the intrinsic structure of the integrated proteogenomes across baseline and treated samples. We will extract proteogenomic features that drive the underlying cluster structure and will perform pathway-level analysis to further characterize each cluster in CLL and RS samples. Copy number to mRNA, protein, and phosphoprotein correlations will be done to determine cis- and trans-regulated genes. Pathways and molecular mechanisms underlying treatment response in patient and mouse models will be explored using single sample Gene Set Enrichment Analysis (ssGSEA), and PTM Signature Enrichment Analysis (PTM-SEA) will be used to perform pathway analysis on phosphorylation data generated. To enable more rapid and specific analyses of proteins and phosphopeptides targets of interest emerging from the discovery experiments, the proteomics core will develop high sensitivity targeted MS assays, to be utilized in Projects 1-3. Assays developed will use stable isotope-labeled standards for unambiguous identification and quantification and applied to human biospecimens and preclinical samples in native and drug-perturbed states.