Biomarker Developmental Laboratory

项目总结/摘要 癌症筛查可以早期发现癌症并降低死亡率。然而，高假阳性率和低 肺癌（LC）和卵巢癌（OC）筛查的敏感性导致不必要的手术， 癌的我们的首要目标是开发循环生化生物标志物，减少假阳性 提高LC的CT扫描率，并增加OC筛查的阳性预测值 CA 125和经阴道超声（TVUS）。我们推测LC和OC患者的抗体水平不同， 来自患有良性疾病的受试者的免疫应答，其可以用于检测癌症和排除 非癌症我们将采取系统的方法与3种类型的抗体：自身抗体，抗微生物抗体， 抗体和抗异常糖蛋白抗体。我们的建议是基于我们在以下方面的丰富经验： 癌症生物标志物发现和免疫蛋白质组学技术。我们之前关于自身抗体的研究结果 生物标志物已经在盲态PRoBE 2期多中心验证研究中得到证实。我们的结果显示 自身抗体生物标志物对癌症具有高度特异性;尽管， 有足够的预测价值。人们越来越关注微生物在癌症与良性疾病中的作用 发展，这可以通过不同的总体感染率和/或对不同的免疫应答来观察。 来自不同微生物的抗原。蛋白质糖基化异常是LC和OC的标志， 将利用我们独特的能力以高通量展示糖基化蛋白质。成功 我们的研究的实施需要高通量方法来在蛋白质组水平上评估抗体。 在EDRN的支持下，我们开发了一套创新的免疫蛋白质组学技术，即高- 密度核酸可编程蛋白阵列（HD-NAPPA）、反捕获蛋白阵列（CCPA）和 多个在溶液中的蛋白质阵列（MISPA），结合最大的全长人类和微生物基因 收集（DNASU质粒库），使我们能够研究针对完整人类蛋白质组的抗体， 微生物蛋白质组和人类O-糖蛋白质组用于癌症中的抗体生物标志物签名。我们 之前的成功，Videssa® Breast，这是一种CLIA认证的乳腺癌血液检测，临床使用， 乳房X线摄影包括一组自身抗体标记物和血清蛋白标记物。与Videssa®一样， 我们还将使用Meso Scale Diagnostics（MSD）MultiArray平台评估报告的血清蛋白 这些标记物可用于补充我们的LC和OC抗体标记物。我们将与专家合作， 范德比尔特大学医学中心的LC和OC筛查，波士顿大学，MD安德森癌症 中心和德国癌症研究中心，谁也将提供获得高质量的良好特点， 从我们的目标人群中提取样本我们将通过筛选蛋白质阵列进行I期（PRoBE）发现 用癌症和对照血清检测癌症或对照特异性抗体。LC和LC的候选生物标志物 OC将使用ELISA或MISPA检测进行II期验证。

Project Summary/Abstract Cancer screening can detect cancer early and reduce mortality. However, high false positive rates and low sensitivities of lung (LC) and ovarian cancer (OC) screening result in unnecessary surgeries and missed cancers. Our overarching goal is to develop circulating biochemical biomarkers that reduce the false positive rate of the CT scan for LC and increase the positive predictive value of OC screening in combination with CA125 and trans-vaginal ultrasound (TVUS). We hypothesize that LC and OC patients have different antibody immune responses from subjects with benign diseases that can be explored for detecting cancer and excluding non-cancer. We will take a systems approach working with 3 types of antibodies: autoantibodies, anti-microbial antibodies and anti-aberrant glycoprotein antibodies. Our proposal builds on our extensive experience with cancer biomarker discovery and immunoproteomics technology. Our previous results on autoantibody biomarkers have been confirmed in blinded PRoBE phase 2 multicenter validation studies. Our results showed that autoantibody biomarkers are highly specific for cancer; although, multiple autoantibodies are needed for adequate predictive value. There is increased attention to the role microbes play in cancer vs. benign disease development, which can be observed by different overall infection rates and / or immune responses to different individual antigens from various microbes. Aberrant protein glycosylation is a hallmark of LC and OC, and we will exploit our unique capability to display glycosylated proteins in high throughput. The successful implementation of our study entails high throughput methods for assessing antibodies at the proteome level. With EDRN support, we have developed a set of innovative immunoproteomics technologies, namely high- density nucleic acid programmable protein array (HD-NAPPA), contra-capture protein array (CCPA) and multiple in solution protein array (MISPA), that, combined with the largest full-length human and microbial gene collection (DNASU plasmid repository), enable us to study antibodies against the full human proteome, microbial proteomes and the human O-glycoproteome for antibody biomarker signatures in cancer. Our previous success, Videssa® Breast, which is a CLIA-certified blood test for breast cancer used clinically with mammography, includes a panel of both autoantibody markers and serum protein markers. As with Videssa®, we will also use the Meso Scale Diagnostics (MSD) MultiArray platform to assess reported serum protein markers for their utility to complement our antibody markers for LC and OC. We will collaborate with experts on LC and OC screening at Vanderbilt University Medical Center, Boston University, MD Anderson Cancer Center, and German Cancer Research Center, who will also provide access to high quality well-characterized samples from our target populations. We will perform Phase I (PRoBE) discovery by screening protein arrays with cancer and control sera for cancer- or control-specific antibodies. Candidate biomarkers for both LC and OC will be Phase 2-validated using ELISA or MISPA assays.