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: 7921180
• 负责人: PAUL TEMPST
• 金额: $ 34.94万
• 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 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7921180
• 关键词: Biological Assay; Biological Markers; Blood; Blood Proteins; Cancer Detection; Cancer Patient; Clinical; Clinical Research; Coupled; Data Storage and Retrieval; Detection; Diagnostic; Enzymes; Exopeptidase; Label; Malignant Neoplasms; Malignant neoplasm of prostate; Measurement; Memorial Sloan-Kettering Cancer Center; Metabolic; Monitor; New York; Newly Diagnosed; 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）：由于癌症涉及产生高水平的特定蛋白质和一些酶（如蛋白酶）的改变的细胞类型的增殖，因此它不仅会改变现有血液蛋白质（“蛋白质组”）的阵列，而且还会改变它们的代谢产物，即，肽（“肽组”）。我们已经开发并展示了一种原型技术平台的原理验证，该平台用于从微升体积的血清中自动化、基于磁珠的固相提取肽，并与MALDI-TOF质谱（MS）读数相结合。我们已经使用该系统来分析不同类型的癌症，并发现选定的肽，当组合作为签名时，具有作为癌症特异性外切蛋白酶活性或活性组的替代生物标志物的效用。因此，血清肽谱分析是基于活性的蛋白质组学的一种形式，即，监测血液蛋白质组“代谢组学”产物，并且降解模式似乎包含用于癌症检测和分类的信息。该提案应用了纪念斯隆-凯特琳癌症中心（MSKCC）和纽约大学（NYU）成熟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癌和乳腺癌的特定模式。与早期的研究不同，我们将利用MSKCC的临床资源来分析比以前尝试的更多的样本。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健康志愿者的样本来评估系统和方法的鲁棒性和再现性。我们的建议包括以下举措：（1）在纽约大学建立一个镜像站点的主要平台A（2）开发和评估二级平台B（LC-MS）;（3）开发和评估替代的基于MS的功能蛋白质组学平台，以测定血浆中的癌症特异性蛋白酶组;（4）引入数量成分（5）开发用于信号处理、数据存储、分析和共享的稳健且用户友好的支持技术/程序;（6）建立1,400个参考样品和120个参考和测定底物肽的储存库。相关性：我们的提案将评估和记录血清肽模式是否对癌症检测具有诊断价值，或可能标志给定的临床结果，或可能区分临床上不显著的癌症。例如，这种测试可以识别出新诊断的癌症患者，他们可以安全地避免手术或放射治疗。