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Profiling autoantibodies for early detection of esophageal squamous cell carcinom

Profiling autoantibodies for early detection of esophageal squamous cell carcinom
分析自身抗体以早期发现食管鳞状细胞癌
批准号:
7741081
负责人:
LI ZHONG
金额:
$18.26万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-07-01 至 2011-06-30

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项目成果

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中文摘要
翻译
描述(申请人提供):食管鳞状细胞癌(ESCC)是世界范围内最常见的致命癌症之一,其5年生存率<15%。显著降低死亡率将需要成功的策略来诊断和治疗无症状的前驱病变和早期癌症。本申请的目的是开发一种基于血液的筛选试验,使用疾病相关自身抗体作为高危人群早期ESCC的生物标志物。我们开发了一种类似的非小细胞肺癌(NSCLC)早期检测方法,该方法诊断I期NSCLC的灵敏度和特异性超过91%。通过与博士的合作。NCI的Sanford Dawsey和Philip Taylor在过去的二十年里领导了中国食管癌高风险地区的流行病学研究,我们从ESCC和鳞状异常增生的各个阶段的患者以及高风险的“正常”个体中获得了大量的血清样本。在我们的初步研究中,我们从肿瘤组织中构建了ESCC T7噬菌体展示文库,并将该文库与患者和正常血清进行了生物筛选,以丰富仅在病例中发现的与自身抗体结合的肿瘤相关蛋白。我们在双色荧光微阵列系统上发现了2000个这样的蛋白质,该系统可用于疾病分类器的高通量发现和验证。我们的初步测试表明,在检测ESCC方面有很好的结果。在这项研究中,我们将首先用100个ESCC和100个对照血清样本作为训练集测试我们的生物标志物芯片。将进行统计分析,并生成分类器以区分病例和对照。其次,这些分类器将在盲交叉验证中评估其能力:1)在200名ESCC患者和200名对照组的单独验证集中区分ESCC和非癌症样本;2)通过150例有食管鳞状病变和150例无食管鳞状病变患者的样本,确定食管鳞状病变、ESCC的前体病变和早期癌症;3)识别未来将发展为ESCC的无症状患者,前瞻性地收集200例已发展为ESCC的患者和200例在3年内未发展为ESCC的患者的样本。如果这些研究的结果是有希望的,我们将在我们有持续合作和基础设施进行此类研究的高风险地区进行临床方案。公共卫生相关性:食管鳞状细胞癌是世界范围内最常见的致命癌症之一。降低死亡率需要早期发现这种疾病的成功战略。本研究的目的是开发一种血液检测方法,利用疾病相关自身抗体作为生物标志物来检测食管鳞状细胞癌的早期阶段。
英文摘要
DESCRIPTION (provided by applicant): Esophageal squamous cell carcinoma (ESCC) is one of the most common fatal cancers worldwide, which has a 5-year survival rate of <15%. Significant reduction in the mortality will require successful strategies to diagnose and treat asymptomatic precursor lesions and early stage cancers. The goal of this application is to develop a blood-based screening assay using disease-associated autoantibodies as biomarkers for early stage ESCC in high-risk populations. We have developed a similar test for early detection of non-small cell lung cancer (NSCLC), which achieved over 91% sensitivity and specificity for diagnosing stage I NSCLC. Through collaboration with Drs. Sanford Dawsey and Philip Taylor at the NCI, who have led esophageal cancer epidemiologic studies in high- risk regions in China over the last twenty years, we have access to a large number of serum samples from patients at all stages of ESCC and squamous dysplasia, and from high-risk "normal" individuals. In our preliminary study, we have constructed an ESCC T7 phage-display library from tumor tissues, and have biopanned this library with patient and normal sera to enrich tumor-associated proteins that bind to autoantibodies found only in the cases. We spotted 2000 of these proteins on a two-color fluorescent microarray system that can be used for high-throughput discovery and validation of disease classifiers. Our preliminary testing has demonstrated promising results in detecting ESCC. In this study we will first test our biomarker chips with 100 ESCC and 100 control serum samples, as a training set. Statistical analysis will be performed and classifiers will be generated for discriminating cases from controls. Second, these classifiers will be evaluated in a blind cross-validation for their ability to: 1) discriminate ESCC from non-cancer samples in a separate validation set of 200 ESCC patients and 200 controls; 2) identify esophageal squamous dysplasia, the precursor lesion of ESCC, and early-stage cancers, using samples from 150 patients with and 150 patients without these lesions; and 3) identify asymptomatic patients who will develop ESCC in the future, using prospectively collected samples from 200 such patients who did and 200 patients who did not develop ESCC within 3 years of sample collection. If the results of these studies are promising, we will proceed to clinical protocols in the high-risk regions where we have ongoing collaborations and the infrastructure to perform such studies. PUBLIC HEALTH RELEVANCE: Esophageal squamous cell carcinoma is one of the most common fatal cancers worldwide. Reduction of the mortality requires successful strategies for early detection of this disease. The goal of this study is to develop a blood test that can detect early stages of esophageal squamous cell carcinoma using disease associated autoantibodies as biomarkers.
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