Biomarker Developmental Laboratory

生物标志物发育实验室

• 批准号: 10688271
• 负责人: Karen Sue Anderson
• 金额: $ 36.79万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10688271
• 关键词: Academic Medical Centers; Antibodies; Antigens; Attention; Autoantibodies; Bacterial Antigens; Benign; Biochemical; Biological Assay; Biological Markers; Biopsy; Blinded; Blood Tests; Boston; Breast; CA-125 Antigen; CLIA certified; Cancer Center; Cancer Detection; Cancer Patient; Categories; Cells; Clinical; Collaborations; Collection; Complement; Custom; Detection; Development; Diagnosis; Diagnostic; Discrimination; Disease; Early Detection Research Network; Engineering; Ensure; Enzyme-Linked Immunosorbent Assay; Exclusion; Fungal Antigens; Genes; German population; Glycoproteins; Goals; Human; Human Genome; Immune; Immune response; Immunologist; Individual; Infection; Laboratories; Length; Lung; Lung diseases; Lung nodule; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of ovary; Mammography; Measures; Methods; Microbe; Morbidity - disease rate; Multicenter Studies; NCI Center for Cancer Research; Nucleic Acids; Pathogenesis; Performance; Phase; Plasmids; Play; Population; Predictive Value; Protein Array; Protein Array Analysis; Protein Glycosylation; Protein Microchips; Proteins; Proteome; Proteomics; Reporting; Role; Sampling; Screening Result; Screening for Ovarian Cancer; Screening for cancer; Serology; Serum Proteins; System; Target Populations; Technology; Testing; Time; Transvaginal Ultrasound; Ultrasonography; Universities; Unnecessary Surgery; Validation; Viral Antigens; Woman; Work; X-Ray Computed Tomography; antimicrobial; biomarker development; biomarker discovery; biomarker signature; biomarker validation; cancer biomarkers; cancer cell; candidate marker; chest computed tomography; circulating biomarkers; cohort; density; diagnostic assay; experience; imaging modality; immunogenic; immunoregulation; improved; infection rate; innovation; malignant breast neoplasm; microbial; microorganism; mortality; novel; protein biomarkers; repository; response; screening; success; validation studies

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.

项目概要/摘要 癌症筛查可以及早发现癌症并降低死亡率。然而，假阳性率高且误报率低 肺癌 (LC) 和卵巢癌 (OC) 筛查的敏感性导致不必要的手术和漏诊 癌症。我们的首要目标是开发循环生化生物标志物，以减少假阳性 LC 的 CT 扫描率并增加 OC 筛查的阳性预测值 CA125 和经阴道超声 (TVUS)。我们假设 LC 和 OC 患者具有不同的抗体 来自患有良性疾病的受试者的免疫反应，可用于检测癌症并排除 非癌症。我们将采用系统方法处理 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。我们的建议建立在我们丰富的经验之上 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结果 生物标志物已在盲法 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；虽然，需要多种自身抗体 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/或对不同的免疫反应来观察 来自各种微生物的个体抗原。异常的蛋白质糖基化是 LC 和 OC 的标志，我们 将利用我们独特的能力以高通量展示糖基化蛋白质。成功者 我们研究的实施需要在蛋白质组水平上评估抗体的高通量方法。 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质阵列 (HD-NAPPA)、反捕获蛋白质阵列 (CCPA) 和 多重溶液蛋白阵列 (MISPA)，结合最大的全长人类和微生物基因 集合（DNASU 质粒存储库），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特征。我们的 之前的成功，Videssa® Breast，这是一种经 CLIA 认证的乳腺癌血液检测，用于临床 乳房X光检查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 平台来评估报告的血清蛋白 标记物可补充我们的 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、波士顿大学、MD 安德森癌症中心的 LC 和 OC 筛查 中心和德国癌症研究中心，他们还将提供高质量的、特征明确的研究 来自我们目标人群的样本。我们将通过筛选蛋白质阵列来进行第一阶段 (PRoBE) 发现 与癌症和对照血清一起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 2 期验证。