Assessment of serum peptide profiling to detect cancer-specific patterns

评估血清肽谱以检测癌症特异性模式

• 批准号: 7293621
• 负责人: PAUL TEMPST
• 金额: $ 161.31万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-29 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7293621
• 关键词: Biological Assay; Biological Markers; Blood; Blood Proteins; Cancer Detection; Cancer Patient; Clinical; Clinical Research; Coupled; Data Storage and Retrieval; Detection; Diagnostic; Endopeptidases; Enzymes; Exopeptidase; Label; Malignant Neoplasms; Malignant neoplasm of prostate; Measurement; Memorial Sloan-Kettering Cancer Center; Metabolic; Monitor; New York; Newly Diagnosed; Numbers; Operative Surgical Procedures; Outcome; Patients; Pattern; Peptide Hydrolases; Peptides; Performance; Phase; Plasma; Prostate; Proteins; Proteome; Proteomics; Radiation; Reading; Reproducibility; Resources; Robotics; Sampling; Serum; Site; Solid; System; Technology; Testing; Universities; base; cancer classification; cancer type; cell type; comparative; computerized data processing; healthy volunteer; magnetic beads; malignant breast neoplasm; metabolomics; mouse model; programs; prototype; repository; user-friendly

Description (provided by applicant): As cancer involves proliferation of altered cell types that produce high levels of specific proteins and some enzymes, such as proteases, it will not only modify the array of existing blood proteins (the "proteome") but also their metabolic products, i.e., peptides (the "peptidome"). We have developed and shown proof-of-principle of a prototype technology platform for automated, magnetic bead-based, solid-phase extraction of peptides from microliter volumes of serum, coupled to a MALDI-TOF mass spectrometric (MS) read-out. We have used this system to analyze different types of cancer and found that selected peptides, when combined as signatures, have utility as surrogate biomarkers for cancer-specific exoprotease activities, or panels of activities. Serum peptide profiling is thus a form of activity-based proteomics, i.e., monitoring blood proteome "metabolomic" products, and the degradative patterns appear to hold information for detection and classification of cancer. This proposal applies specific expertise from well-established clinical and research groups at Memorial Sloan-Kettering Cancer Center (MSKCC) and at New York University (NYU) to assess our analytical platform and apply it to detect prostate and breast cancer-specific patterns. Unlike earlier studies, we will leverage the clinical resources of MSKCC to analyze a far larger number of samples than previously attempted. We propose to assess robustness and reproducibility of both system and approach using mouse models, clinical samples from prostate cancer and breast cancer patients, and samples from healthy volunteers. Our proposal includes the following initiatives: (1) establish a mirror site at NYU of primary platform A (robotics plus MALDI-TOF MS) in its entirety, followed by comparative performance and reproducibility assessment; (2) develop and assess a secondary platform B (LC-MS); (3) develop and evaluate an alternative, MS-based functional proteomics platform to assay cancer-specific protease panels in plasma; (4) introduce quantitative components (using a repository of non-degradable, isotopically-labeled reference peptides) to both platforms A and B for direct measurements or for assays; (5) develop robust and user-friendly support technologies/programs for signal processing, data storage, analysis and sharing; (6) establish a repository of 1,400 reference samples and 120 reference and assay-substrate peptides. Relevance: Our proposal will evaluate and document whether serum peptide patterns have diagnostic value for cancer detection, or may mark a given clinical outcome, or may distinguish clinically insignificant from significant cancer. Such a test could, for example, identify patients with newly diagnosed cancer who might safely avoid surgery or radiation.

描述（由申请人提供）：由于癌症涉及改变的细胞类型的增殖，这些细胞类型产生高水平的特定蛋白质和某些酶，例如蛋白酶，它不仅会改变现有的血蛋白（“蛋白质组”）的数组，而且还会改变其代谢产物，即肽（“肽组”）。我们已经开发并显示了原型技术平台的原理证明，用于从微量体积的精华素体积中自动化的，基于磁珠的固相提取，并耦合到MALDI-TOF质谱（MS）读出。我们已经使用该系统来分析不同类型的癌症，并发现当将肽合并为特征时，将选择的肽作为癌症特异性杂质活动或活动板的替代生物标志物。因此，血清肽分析是一种基于活性的蛋白质组学的一种形式，即监测血液蛋白质组“代谢组”产物，而降解模式似乎具有用于检测和分类癌症的信息。该提案采用了纪念斯隆 - 凯特林癌症中心（MSKCC）和纽约大学（NYU）的临床和研究小组的特定专业知识，以评估我们的分析平台并将其应用于检测前列腺和乳腺癌特异性模式。与较早的研究不同，我们将利用MSKCC的临床资源来分析比以前尝试的要大得多的样本。我们建议使用小鼠模型，前列腺癌和乳腺癌患者的临床样本以及来自健康志愿者的样本来评估系统和方法的可靠性和可重复性。我们的建议包括以下倡议：（1）在其整体上，在主要平台A（机器人和MALDI-TOF MS）的NYU建立镜像站点，然后进行比较性能和可重复性评估； （2）开发和评估二级平台B（LC-MS）； （3）开发和评估一个基于MS的替代功能蛋白质组学平台，以测定等离子体中癌症特异性蛋白酶面板； （4）将定量组件（使用不可降解的，同位素标记的参考肽的存储库）向两个平台A和B进行直接测量或用于测定； （5）为信号处理，数据存储，分析和共享开发强大且用户友好的支持技术/程序； （6）建立一个由1,400个参考样品和120个参考和测定含肽的存储库。相关性：我们的建议将评估和记录血清肽模式是否具有癌症检测的诊断价值，或者可能标志着给定的临床结果，或者可能将临床上无关的癌症与重大癌症区分开。例如，这样的测试可以识别出可能安全避免手术或放射线的新诊断癌症患者。