Characterization of antitumor auto-antibodies using combinatorial peptide librari

使用组合肽文库表征抗肿瘤自身抗体

• 批准号: 8454976
• 负责人: WLODEK MANDECKI
• 金额: $ 27.24万
• 依托单位: PHARMASEQ, INC.
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-25 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8454976
• 关键词: Acetonitriles; Adsorption; Advanced Malignant Neoplasm; Affect; Affinity; Amino Acid Sequence; Amino Acids; Antibodies; Autoantibodies; Binding; Biological; Biological Markers; Buffers; Cancer Patient; Cancerous; Chemicals; Classification; Clinical; Collaborations; Complementarity Determining Regions; Complex; Development; Diagnostic; Diagnostic Neoplasm Staging; Discrimination; Disease; Early Diagnosis; Electromagnetics; Fingerprint; Fluorescence; Frequencies; Goals; Human; Immunoglobulins; Individual; Laboratories; Libraries; Ligands; Light; Malignant Neoplasms; Malignant neoplasm of ovary; Methods; Molecular Profiling; Organic solvent product; Outcome; Pattern; Peptide Library; Peptide Synthesis; Peptides; Phase; Positioning Attribute; Process; Proteins; Proteome; Radio; Randomized; Reader; Reading; Recording of previous events; Reproducibility; Research; Running; Sampling; Screening for Ovarian Cancer; Screening procedure; Sensitivity and Specificity; Serum; Solid; Speed; Staging; Structure; Surface; System; Time; Training; Translations; Tumor Antigens; Tumor Markers; Validation; base; cancer type; clinically relevant; combinatorial; design; falls; indexing; instrument; malignant breast neoplasm; particle; protein aminoacid sequence; serological marker; tumor

DESCRIPTION (provided by applicant): The development of circulating auto-antibodies to tumor-associated antigens (TAAs) has been observed at early cancer stages. TAA auto-antibodies are attractive as diagnostic markers because they are stable and persistent in cancerous conditions yet minimally present in normal individuals and most noncancerous conditions. However, the identification of auto-antibodies specific for a particular type of cancer is complicated due to the relatively low-abundance of an individual antibody within the complexity of the human proteome. The purpose of the present project is to develop an approach to detect auto-antibodies to tumor-associated antigens using an encoded combinatorial peptide library synthesized on PharmaSeq's light-activated radio-frequency p-Chips. Preparing the combinatorial library on the p-Chip platform serves two purposes: 1) to enrich for low-abundance proteins based on established principles of solid-phase affinity adsorption and 2) to rapidly identify the affinity ligand on each chip based on the encoded ID. The main project goal is to synthesize an RFID-encoded peptide library consisting of several thousands of random tetramers using the "split-and-mix" method. We will use a high speed fluidics-based analytical instrument previously developed by PharmaSeq to identify p-Chips carrying specific peptides with affinity to human auto- antibodies. In addition we will quantitatively characterize differences in immunoglobulin profiles between early stage ovarian and breast cancer patient and normal control samples. The methods developed will enable, for the first time, a true encoded one- particle-one-compound high throughput library synthesis and screening method that is capable of direct translation as a clinical diagnostic platform. PUBLIC HEALTH RELEVANCE: Auto-antibodies generated against tumor-associated antigens show great potential for the accurate, early diagnosis of cancer but identifying antibodies specific to a particular type of cancer is challenging, requiring a sensitive, high-throughput system that can discriminate key biomarkers against a high protein load. The implementation of an RFID- encoded combinatorial peptide library with PharmaSeq's light-activated p-Chip system will enable the simultaneous enrichment and identification of clinically-relevant biomarkers on a unified, high-throughput platform.

描述（由申请人提供）：在早期癌症阶段已观察到针对肿瘤相关抗原（TAA）的循环自身抗体的发展。 TAA 自身抗体作为诊断标记物很有吸引力，因为它们在癌症条件下稳定且持久，但在正常个体和大多数非癌症条件下存在最少。然而，对特定类型癌症具有特异性的自身抗体的鉴定 由于人类蛋白质组的复杂性中单个抗体的丰度相对较低，因此变得复杂。本项目的目的是开发一种方法，使用在 PharmaSeq 的光激活射频 p-Chips 上合成的编码组合肽库来检测肿瘤相关抗原的自身抗体。在 p-Chip 平台上制备组合文库有两个目的：1) 根据固相亲和吸附的既定原理富集低丰度蛋白质，2) 根据编码的 ID 快速识别每个芯片上的亲和配体。主要项目目标是使用“拆分和混合”方法合成由数千个随机四聚体组成的 RFID 编码肽库。我们将使用 PharmaSeq 先前开发的基于流体学的高速分析仪器来识别携带与人类自身抗体具有亲和力的特定肽的 p-Chips。此外，我们将定量表征早期卵巢癌和乳腺癌患者与正常对照样本之间免疫球蛋白谱的差异。开发的方法将首次实现真正编码的单颗粒一种化合物高通量库合成和筛选方法，该方法能够直接转化为临床诊断平台。 公共卫生相关性：针对肿瘤相关抗原产生的自身抗体在准确、早期诊断癌症方面显示出巨大潜力，但识别特定类型癌症的特异性抗体具有挑战性，需要一个能够区分关键生物标志物的灵敏、高通量系统对抗高蛋白质负荷。通过 PharmaSeq 的光激活 p-Chip 系统实施 RFID 编码的组合肽库，将能够在统一的高通量平台上同时富集和识别临床相关生物标志物。