A High Throughput Diagnostic Assay for Lung Cancer

肺癌的高通量诊断分析

• 批准号: 6913043
• 负责人: Kathlynn C Brown
• 金额: $ 15.6万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2007-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6913043
• 关键词: biomarker; biotechnology; cell line; chemical binding; chemical conjugate; diagnosis design /evaluation; high throughput technology; lung neoplasms; nanotechnology; neoplasm /cancer classification /staging; neoplasm /cancer diagnosis; neoplastic cell; particle; peptide chemical synthesis; phage display

DESCRIPTION (provided by applicant): Within the United States, 170,000 new cases of lung cancer are diagnosed per year. Over 60% of these patients will die within one year, making lung cancer the largest cancer killer of both men and women. The correct histopathological diagnosis of a tumor is critical in determining the appropriate treatment. However, precise classification of tumors remains a significant biomedical challenge. Furthermore, tumors of similar histology can have different clinical outcomes, stressing the need for more detailed molecular classifications. Generation of ligands specific to receptor(s) on a surface of a lung cancer cell will impact clinical issues including functional diagnosis. Our overall goal is to generate a panel of cell-specific molecules that could be used to classify tumor types and utilize these cancer specific reagents in a high throughput diagnostic assay. Using phage display technologies, my laboratory has developed platform methodologies to isolate peptides that bind to and mediate uptake into specific cell lines. We have identified cell-specific targeting peptides for 25 different cell types, including 4 lung cancer cell lines. The isolated peptides display remarkable cell specificities, even among similar cells, and are able to discriminate between normal and cancerous cells as well as different lung tumor cells. This high discriminating power suggests that peptides could be identified that selectively bind to different tumor types, even those with similar classifications. We propose to expand this panel of lung specific reagents by isolating cell targeting peptides for 4 different lung cancer lines and then utilize these peptides as diagnostic reagents. These peptides will be assayed for affinity and cell-specificity. We will remove the peptides from the phage backbone and synthesize peptide scaffolds that retain their affinity and cell-specificity. We will develop a high throughput fluorescent assay based on peptide binding that will allow for a more molecular classification of lung cancer samples. The assay can be multiplexed so that multiple binding events can be examined on a single sample. At the end of this pilot project we will have developed a novel diagnostic platform that can be expanded to clinical samples. Furthermore, the technologies developed here can be applied to other forms of cancer.

描述（由申请人提供）： 在美国，每年新诊断出 170,000 例肺癌病例。其中超过 60% 的患者将在一年内死亡，使肺癌成为男性和女性最大的癌症杀手。肿瘤的正确组织病理学诊断对于确定适当的治疗至关重要。然而，肿瘤的精确分类仍然是一个重大的生物医学挑战。此外，相似组织学的肿瘤可能有不同的临床结果，强调需要更详细的分子分类。肺癌细胞表面受体特异性配体的产生将影响包括功能诊断在内的临床问题。我们的总体目标是生成一组细胞特异性分子，可用于对肿瘤类型进行分类，并在高通量诊断测定中利用这些癌症特异性试剂。使用噬菌体展示技术，我的实验室开发了平台方法来分离与特定细胞系结合并介导吸收的肽。我们已经鉴定出针对 25 种不同细胞类型（包括 4 种肺癌细胞系）的细胞特异性靶向肽。即使在相似的细胞中，分离的肽也显示出显着的细胞特异性，并且能够区分正常细胞和癌细胞以及不同的肺肿瘤细胞。这种高辨别力表明，可以鉴定出选择性结合不同肿瘤类型的肽，甚至是那些具有相似分类的肿瘤类型。我们建议通过分离 4 种不同肺癌系的细胞靶向肽来扩展这组肺部特异性试剂，然后利用这些肽作为诊断试剂。将分析这些肽的亲和力和细胞特异性。我们将从噬菌体骨架中去除肽并合成保留其亲和力和细胞特异性的肽支架。我们将开发一种基于肽结合的高通量荧光测定，这将允许对肺癌样本进行更多的分子分类。该测定可以是多重的，以便可以在单个样品上检查多个结合事件。在这个试点项目结束时，我们将开发出一个可以扩展到临床样本的新型诊断平台。此外，这里开发的技术可以应用于其他形式的癌症。