Proteomic, Glycomic and Autoantibody Lung Cancer Biomarker Validation

蛋白质组、糖组和自身抗体肺癌生物标志物验证

基本信息

批准号：
8883444
负责人：
A McGarry Houghton
金额：
$ 36.4万
依托单位：
FRED HUTCHINSON CANCER RESEARCH CENTER
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-07-01 至 2017-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8883444
关键词：
Age Antibodies Antibody Affinity Asbestos Autoantibodies Binding Biological Markers Blood Body mass index Breast Cancer Etiology Cancer Patient Cessation of life Chest Clinic Clinical Colon Colon Carcinoma Colorectal Data Diagnosis Diagnostic Dose Early Diagnosis Enzyme-Linked Immunosorbent Assay Epidemiologic Factors FDA approved Family history of Gender General Population Genomics Glycoproteins Growth Factor Health Image Immune Immune system Lung Malignant Neoplasms Malignant neoplasm of lung Malignant neoplasm of ovary Membrane Methods Modality Movement Neoplasm Metastasis Nodule Ovarian Pancreas Patient Care Performance Plasma Play Population Prostate Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Proteins Proteomics Radiation Randomized Controlled Trials Receiver Operating Characteristics Reporting Research Design Risk Risk Factors Role Sampling Scanning Sensitivity and Specificity Smoking Smoking History Sputum Cytology Screening Staging Survival Rate Techniques Technology Testing Translations United States Validation Variant Work X-Ray Computed Tomography burden of illness cancer diagnosis cardiovascular health case control clinical application cohort comparison group cost cytokine density design follow-up high risk interest lung cancer screening malignant breast neoplasm mortality novel performance tests predictive modeling receptor screening tumor microenvironment

项目摘要

DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer death in the United States and world-wide. In 2013, it is estimated that there will be at least 228,000 new cases of lung cancer diagnosed and more than 159,000 deaths in the United States - approximately equal to the next four most common causes of cancer-related mortality combined (colon, breast, prostate, pancreas). The potential benefits of lung cancer early detection are clear - when discovered at an early stage, lung cancer has 5 year survival rates over 50% while only 3.7% of metastatic lung cancer patients survive that long. To date, randomized controlled trials of most screening modalities such as chest x-ray and sputum cytology have not demonstrated any impact on lung cancer mortality. Also, no proteomic or genomic plasma markers have advanced sufficiently in validation trials to be viable FDA-approved candidates for widespread screening. Discovery of viable lung cancer early detection proteomic, glycomic and/or immunological biomarkers in blood that would work well on their own or in combination with low-dose chest computed tomography (CT) would be especially valuable since lung cancer is common, most often fatal and is expensive to treat - so it has high societal costs. We have taken a unique approach to biomarker discovery designed to overcome current obstacles. We created a high density antibody array containing 3200 different antibodies that we use to interrogate pre-diagnostic sample sets from multiple observational trials (i.e., hundreds of pre-diagnostic samples with well-matched cases and controls) in a nested case-control design study to evaluate proteomic, glycomic and autoantibody differences. Since our discovery method uses high affinity antibodies, our best performing markers can be readily transferred to ELISA-like methods facilitating formal validation and movement into the clinic. We have shown the technology is highly sensitive (low picogram levels) and reproducible (most coefficients of variation <10%). Furthermore, we have confirmed known and found new viable proteomic biomarker candidates in ovarian, breast, colon and lung cancer. Using pre-diagnostic lung cancer samples from the Cardiovascular Health Study (CHS), we found 30 proteomic, glycomic or autoantibody biomarkers that were significantly increased (p<0.002) in people that are diagnosed with lung cancer. Here, we propose to use samples from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to validate these candidates. Our specific aims are: (1) To use PLCO samples to preliminarily validate 30 potential lung cancer early detection proteomic, glycomic or autoantibody biomarker candidates (e.g., those with >2 x increases, p<0.002, AUC > 0.67). (2) To develop and assess the performance of a novel risk prediction model integrating the biomarkers assessed in Aim 1 with a variety of clinical and epidemiologic factors, including lung cancer subtype, smoking history, age, gender, body mass index, family history of lung and other cancers, radiation, asbestos and other exposures, that should potentially impact biomarker performance and risk prediction.

描述（由申请人提供）：肺癌是美国和全世界癌症死亡的主要原因。 2013 年，估计美国将至少诊断出 228,000 例肺癌新病例，并导致超过 159,000 例死亡 - 大约相当于接下来四种最常见的癌症相关死亡原因（结肠癌、乳腺癌、前列腺癌）的总和。、胰腺）。肺癌早期检测的潜在好处是显而易见的——当早期发现时，肺癌的 5 年生存率超过 50%，而只有 3.7% 的转移性肺癌患者能存活这么久。迄今为止，大多数筛查方式（例如胸部 X 光检查和痰细胞学检查）的随机对照试验尚未证明对肺癌死亡率有任何影响。此外，在验证试验中，还没有任何蛋白质组或基因组血浆标记物取得足够进展，能够成为 FDA 批准的广泛筛选的可行候选者。发现血液中可行的肺癌早期检测蛋白质组、糖组和/或免疫生物标志物，这些标志物可以单独使用或与低剂量胸部计算机断层扫描 (CT) 结合使用，这将特别有价值，因为肺癌很常见，而且通常是致命的而且治疗费用昂贵——因此社会成本很高。我们采用了独特的生物标志物发现方法，旨在克服当前的障碍。我们创建了包含 3200 种不同抗体的高密度抗体阵列，用于在嵌套病例对照设计研究中询问来自多个观察性试验的诊断前样本集（即数百个具有良好匹配的病例和对照的诊断前样本）评估蛋白质组、糖组和自身抗体的差异。由于我们的发现方法使用高亲和力抗体，因此我们性能最佳的标记物可以轻松转移到类似 ELISA 的方法，从而促进正式验证并进入临床。我们已经证明该技术具有高度灵敏性（低皮克级）和可重复性（大多数变异系数<10%）。此外，我们已经在卵巢癌、乳腺癌、结肠癌和肺癌中证实了已知并发现了新的可行的蛋白质组生物标志物候选物。使用来自心血管健康研究 (CHS) 的诊断前肺癌样本，我们发现 30 种蛋白质组、糖组或自身抗体生物标志物在诊断为肺癌的人群中显着升高 (p<0.002)。在这里，我们建议使用前列腺癌、肺癌、结直肠癌和卵巢癌 (PLCO) 癌症筛查试验的样本来验证这些候选药物。我们的具体目标是：（1）使用 PLCO 样本初步验证 30 个潜在的肺癌早期检测蛋白质组、糖组或自身抗体生物标志物候选物（例如，增加 >2 倍的那些，p<0.002，AUC > 0.67）。 (2) 开发并评估一种新型风险预测模型的性能，该模型将目标 1 中评估的生物标志物与各种临床和流行病学因素相结合，包括肺癌亚型、吸烟史、年龄、性别、体重指数、家族史肺癌和其他癌症、辐射、石棉和其他暴露，这可能会影响生物标志物的性能和风险预测。