Cancer Proteome Center at Washington Univ, Univ of North Carolina

华盛顿大学、北卡罗来纳大学癌症蛋白质组中心

• 批准号: 8766536
• 负责人: XIAN CHEN
• 金额: $ 219.77万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-22 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8766536
• 关键词: Address; Affinity; Antibodies; Automobile Driving; Award; Bioinformatics; Biological; Biological Assay; Biological Markers; Blood; Blood specimen; Cancer Biology; Cancer Diagnostics; Clinical; Clinical Data; Collection; Complex; Critical Pathways; Data; Development; Diagnosis; Diagnostic; Disease; Early Diagnosis; Early Intervention; Early treatment; Epigenetic Process; Epitopes; Frequencies; Gene Dosage; Genes; Genome; Genomics; Goals; Growth; Human; Immunoassay; Incidence; Individual; Institution; Instruction; Knowledge; Label; Lead; Life; Malignant Neoplasms; Maps; Mass Spectrum Analysis; Massive Parallel Sequencing; Measures; Metabolism; Methods; Minor; Mus; Mutation; Normal Range; North Carolina; Organ; Pathway interactions; Patients; Pattern; Peptide antibodies; Peptides; Phase; Plasma; Point Mutation; Post-Translational Protein Processing; Property; Protein Databases; Proteins; Proteome; Proteomics; Publishing; RNA Splicing; Recurrence; Research; Research Infrastructure; Resolution; Resources; Route; Sampling; Sensitivity and Specificity; Shotguns; Somatic Cell; Somatic Mutation; Statistical Models; System; Technology; TimeLine; Tissues; Translating; Translations; Validation; Variant; Washington; Xenograft Model; Xenograft procedure; advanced disease; base; cancer genome; cancer genomics; clinical application; clinical practice; data management; experience; genome analysis; genome sequencing; instrumentation; interest; loss of function mutation; malignant breast neoplasm; meetings; mortality; multiple reaction monitoring; mutant; operation; peripheral blood; programs; protein aminoacid sequence; tool; tumor

DESCRIPTION (provided by applicant): Biomarkers are unique, detectable signatures of cancer that are vital to early diagnosis and treatment. The causes of many cancers are somatic mutations in critical pathways that serve organ growth and metabolism. For over a decade there have been intense proteomic efforts to find biomarkers with clinical utility. There are thousands of published studies and thousands of candidate biomarkers of unknown value for the management of cancer. With the advent of whole genome sequencing, the challenge and immense potential value of characterizing the cancer proteome the readout of the genome-is unfolding. A new paradigm is therefore emerging -"genome-out" directed proteomics. In this application, we propose a comprehensive, blood-based, protein biomarker discovery and verification pipeline that addresses biomarker discovery by starting where the cancer biology begins: with the driving somatic mutations. In the discovery phase, we will use information about recurrent genomic mutations in cancer (i.e. those that occur with a greater than 5% incidence in any given cancer) that are identified by ongoing whole-genome sequencing efforts to focus our collection and analyses of high-throughput, quantitative proteomic data on samples provided by the NCI CPTC in concert with unique resources such as comprehensively sequenced "human in mouse" breast cancer xenografts. Proteomic analyses will include a multiplicity of high-resolution, current and advanced proteomics methods that can characterize intact proteins, massively complex peptide mixtures and protein modifications to elucidate the proteomic facade of cellular pathways and networks. Bioinformatic tools with rigorous statistical models will be applied to meet the challenges of querying the genome directly with proteomic data (proteogenomics). This will provide the orthogonality that cancer genomics requires to biologically validate copy number alterations, point mutations, splice variants, and the complex biological effects from loss of function mutations and epigenetic changes and translate these findings into actionable clinical information. With this melding of proteomic and genomic knowledge, clinically and biologically informed decisions will be made to select candidate biomarkers. The properties of each candidate will be verified by demonstrating an ability of the biomarker assay to reliably distinguish between blood samples taken from healthy individuals from those accrued from patients with cancer.

描述（由申请人提供）：生物标志物是癌症的独特、可检测的特征，对早期诊断和治疗至关重要。许多癌症的原因是服务于器官生长和代谢的关键途径中的体细胞突变。十多年来，蛋白质组学一直在努力寻找具有临床实用性的生物标志物。有成千上万的已发表的研究和成千上万的候选生物标志物的未知价值的管理癌症。随着全基因组测序的出现，表征癌症蛋白质组（基因组的读出）的挑战和巨大的潜在价值正在显现。因此，一种新的范式正在出现--“基因组外”定向蛋白质组学。在本申请中，我们提出了一个全面的、基于血液的蛋白质生物标志物发现和验证管道，该管道通过从癌症生物学开始的地方开始解决生物标志物发现问题：驱动体细胞突变。在发现阶段，我们将利用癌症中复发性基因组突变的信息（即在任何给定癌症中发生率大于5%的那些），其通过正在进行的全基因组测序工作来鉴定，以集中我们的高通量收集和分析，由NCI CPTC提供的样品定量蛋白质组学数据与独特的资源相结合，如全面测序的“人在小鼠中”乳腺癌异种移植物蛋白质组学分析将包括多种高分辨率，当前和先进的蛋白质组学方法，可以表征完整的蛋白质，大量复杂的肽混合物和蛋白质修饰，以阐明细胞通路和网络的蛋白质组学外观。将应用具有严格统计模型的生物信息学工具来应对直接使用蛋白质组学数据（蛋白质基因组学）查询基因组的挑战。这将提供癌症基因组学所需的正交性，以生物学验证拷贝数改变、点突变、剪接变体以及来自功能丧失突变和表观遗传变化的复杂生物学效应，并将这些发现转化为可操作的临床信息。随着蛋白质组学和基因组学知识的融合，将做出临床和生物学上知情的决定来选择候选生物标志物。将通过证明生物标志物测定可靠区分从健康个体采集的血液样品与从癌症患者采集的血液样品的能力来验证每种候选物的性质。