A High Throughput Diagnostic Assay for Lung Cancer

肺癌的高通量诊断分析

基本信息

批准号：
7067131
负责人：
Kathlynn C Brown
金额：
$ 15.23万
依托单位：
UT SOUTHWESTERN MEDICAL CENTER
依托单位国家：
美国
项目类别：
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/7067131
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

项目摘要

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，每年诊断出170,000例新的肺癌病例。这些患者中有60％会在一年内死亡，这使肺癌成为男性和女性中最大的癌症杀手。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。但是，肿瘤的精确分类仍然是一项重大的生物医学挑战。此外，相似组织学的肿瘤可能具有不同的临床结局，强调需要进行更详细的分子分类。在肺癌细胞表面上特有受体特有的配体的产生将影响临床问题，包括功能诊断。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特定于癌症的试剂。使用噬菌体显示技术，我的实验室开发了平台方法来分离结合并介导摄取到特定细胞系的肽。我们已经确定了针对25种不同细胞类型的细胞特异性靶向肽，包括4种肺癌细胞系。分离的肽甚至在相似细胞之间也表现出显着的细胞特异性，并且能够区分正常和癌细胞以及不同的肺部肿瘤细胞。这种高歧视能力表明，可以鉴定肽可以选择性地结合不同的肿瘤类型，即使是具有相似分类的肽类型。我们建议通过分离4种不同的肺癌系的细胞靶向肽，然后利用这些肽作为诊断试剂来扩展该肺部特定试剂。这些肽将用于亲和力和细胞特异性。我们将从噬菌体主链中去除肽，并合成保留其亲和力和细胞特异性的肽支架。我们将基于肽结合开发高吞吐量荧光测定法，这将允许对肺癌样品进行更分子的分类。可以对该测定进行多种多样，以便可以在单个样本上检查多个结合事件。在此试点项目的结尾，我们将开发出一个新颖的诊断平台，可以扩展到临床样本。此外，这里开发的技术可以应用于其他形式的癌症。