Affinity Based Strategies to Fast Track Development of Colon Cancer Biomarkers

基于亲和力的策略快速开发结肠癌生物标志物

• 批准号: 8129616
• 负责人: SAMIR M HANASH
• 金额: $ 65.76万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-16 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8129616
• 关键词: Affinity; Antibodies; Apoptosis; Biological Markers; Cancer Etiology; Cessation of life; Colon; Colon Carcinoma; Colorectal Cancer; Custom; Development; Diagnosis; Diagnostic; Early Diagnosis; Enzyme-Linked Immunosorbent Assay; Goals; Incubated; Inflammation; Insulin Resistance; Lectin; MAP Kinase Gene; Malignant Neoplasms; Methods; Pathway interactions; Phospho-Specific Antibodies; Plasma; Process; Prostaglandins; Proteins; Proteome; Proteomics; Regulation; Sampling; Screening procedure; Signal Pathway; Sorting - Cell Movement; Specificity; Technology; Tissue Sample; Tissues; Toll-like receptors; Transforming Growth Factors; Triage; United States; Validation; angiogenesis; base; density; glycosylation; improved; novel; tumor

DESCRIPTION (provided by applicant): Colorectal cancer (CRC) is one of the most common cancers in the United States and the second ranked cause of cancer related death. This project proposes to perform both broad proteomic and glycomic screens and targeted analyses to discover early detection and diagnostic biomarkers of CRC. The goal is to improve colon screening by the addition of highly sensitive markers that together with each other or existing markers yield good specificity. We will interrogate unique prediagnostic plasma samples, tissue from primary CRC tumors, and plasma from CRC cases on custom high-density antibody microarrays (up to 6000 different analytes) to discover novel proteomic and glycomic biomarkers. Parallel arrays will be incubated with plasma or tissue lysate for proteomic comparison or glycosylation (via incubation with different lectins). This microarray approach employs technology with unparalleled sensitivity, enabling interrogation down to the low picomolar concentration of the circulating proteome. Biomarker candidates that pass the statistical threshold on a "discovery" array will be retained and be re-examined using new samples on smaller arrays (to reduce the false discovery rate) - a step we will refer to as "pre-validation" to indicate that a potential biomarker would have shown up as statistically significant in multiple sample sets but was not yet subjected to formal characterization or validation. This unique triage process allows for rapid sorting of potential biomarkers, allowing us to focus on only the most promising. The best candidates will then be evaluated with more conventional ELISA and lectin based methods. Our approaches will specifically target proteomic and glycomic changes in proteins critical for the regulation of apoptosis, proliferation, angiogenesis, inflammation/prostaglandins, insulin resistance, toll-like receptor (TLR), transforming growth factor (TGF)-¿ and STAT signaling pathway deregulation during CRC to discover biomarkers of early detection and diagnosis. These include over 300 phospho-specific antibodies and their matched non-phospho-specific counterparts to 21 MAPK, 12 TGF-¿, and many STAT pathway targets.

描述（由申请人提供）：结直肠癌（CRC）是美国最常见的癌症之一，也是癌症相关死亡的第二大原因。本项目建议进行广泛的蛋白质组学和糖组学筛选以及有针对性的分析，以发现CRC的早期检测和诊断生物标志物。目标是通过添加高灵敏度标记物来改善结肠筛查，这些标记物彼此或现有标记物一起产生良好的特异性。我们将在定制的高密度抗体微阵列（多达6000种不同的分析物）上询问独特的诊断前血浆样本、原发性结直肠癌肿瘤组织和结直肠癌病例血浆，以发现新的蛋白质组学和糖组学生物标志物。平行阵列将与血浆或组织裂解液孵育，用于蛋白质组学比较或糖基化（通过与不同凝集素孵育）。这种微阵列方法采用了具有无与伦比灵敏度的技术，可以对循环蛋白质组的低皮摩尔浓度进行查询。在“发现”阵列上通过统计阈值的生物标记候选物将被保留，并使用较小阵列上的新样本进行重新检查（以减少错误的发现率）-我们将此步骤称为“预验证”，以表明潜在的生物标记物在多个样本集中显示为统计显著性，但尚未进行正式表征或验证。这种独特的分诊过程可以快速分类潜在的生物标志物，使我们能够只关注最有希望的生物标志物。然后将使用更传统的ELISA和基于凝集素的方法对最佳候选物进行评估。我们的方法将专门针对在CRC期间对细胞凋亡、增殖、血管生成、炎症/前列腺素、胰岛素抵抗、toll样受体（TLR）、转化生长因子(TGF)-¿和STAT信号通路解除调控至关重要的蛋白质的蛋白质组学和糖组学变化，以发现早期检测和诊断的生物标志物。其中包括超过300种磷酸化特异性抗体及其与21种MAPK、12种TGF-¿和许多STAT途径靶点相匹配的非磷酸化特异性抗体。