Affinity-Based Serum Proteomics: Breast and Ovarian Can*

描述（由申请人提供）：我们的目标是发现和确认许多基于血清的肿瘤生物标志物，这些生物标志物足以诊断处于最可治疗阶段的每种乳腺癌和卵巢癌。 为了实现这一目标，我们利用一种新的蛋白质组学方法和血清样本，从一个丰富的和良好的特征标本库。 我们的蛋白质组学方法使用三个不同的重组抗体文库，每个文库包含10^8- 10^10个独特的结合序列。 我们选择可以结合来自癌症患者的血清中的表位的子文库，所述表位不存在于无癌症对照血清中。 这种方法与其他血清蛋白质组学方法相比具有几个优点，包括发现由差异翻译后修饰产生的生物标志物的能力和纯化每个靶标的能力，这有助于生物标志物鉴定（即，测序）和功能表征。 该重组文库淘选程序将发现数千个需要进一步确认的候选生物标志物。 虽然可以用标准ELISA技术进行确认，但我们打算使用两个高通量平台-抗体微阵列和悬浮测定系统。 这些平台使我们能够同时评估整个抗体子库以及其他抗体，并以直接类似于我们现在常规使用转录物微阵列的方式使用血清对乳腺癌和卵巢癌进行分子分类。 我们的研究设计将有助于乳腺癌和卵巢癌的早期发现。 此外，我们的研究计划包含了EDRN作为一个整体的机会。 例如，在我们的抗体分析期间，我们将邀请任何具有假定的卵巢癌或乳腺癌生物标志物的EDRN研究者向我们的阵列贡献他们的试剂。 此外，在我们的提案中，我们将制作一种抗体微阵列，用于评估与乳腺癌和卵巢癌相关的许多研究问题。 我们将提供使用这些阵列分析EDRN内的任何血清样本。 这些测量的所有数据将提供给提供标本的研究人员（或EDRN协调中心）。

DESCRIPTION (provided by applicant): Our goal is to discover and confirm a number of serum-based tumor biomarkers sufficient to diagnose every breast cancer and ovarian cancer in its most treatable stage. To accomplish this, we utilize a novel proteomics approach and serum samples from a rich and well-characterized specimen repository. Our proteomics approach uses three distinct recombinant antibody libraries that each contain between 10^8- to 10^10 unique binding sequences. We select the sub-libraries that can bind epitomes in serum from cancer patients that are not present in cancer-free control serum. This approach has several advantages over other serum proteomics approaches, including the capability to discover biomarkers resulting from differential post-translational modifications and the ability to purify each target, which facilitates biomarker identification (i.e., sequencing) and functional characterization. This recombinant library panning procedure will discover thousands of candidate biomarkers in need of further confirmation. Although confirmation could proceed with standard ELISA techniques, we intend to use two high-throughput platforms - antibody microarrays and a suspension assay system. These platforms allow us to simultaneously evaluate the entire antibody sub library alongside other antibodies, and to molecularly classify breast and ovarian cancer using serum in a manner directly analogous to how we now routinely use transcript microarrays. Our research design will facilitate the early detection of breast and ovarian cancer. In addition, our research plan contains opportunities for the EDRN as a whole. For example, during our antibody profiling we will invite any EDRN investigators having a putative ovarian or breast cancer biomarker to contribute their reagents to our array. Moreover, during our proposal we will have produced an antibody micro arrays useful for evaluating many research questions relevant to breast and ovarian cancer. We will offer to profile any serum samples from within EDRN using these arrays. All data from these measurements will be given to the researchers who provide the specimens (or the EDRN coordinating center).