Role of Antigen Glycosylation in Mucin Binding by Monoclonal Antibodies

抗原糖基化在单克隆抗体粘蛋白结合中的作用

• 批准号: 10045898
• 负责人: Cory Brooks
• 金额: $ 41.49万
• 依托单位: CALIFORNIA STATE UNIVERSITY FRESNO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10045898
• 关键词: Address; Adenocarcinoma; Antibodies; Antibody Affinity; Antibody Therapy; Antigens; Binding; Binding Proteins; Breast Cancer Patient; Cancer Vaccines; Cell Proliferation; Clinical; Complex; Computer Models; Crystallization; Data; Development; Engineering; Enzyme-Linked Immunosorbent Assay; Epitope Mapping; Epitopes; Equilibrium; Family; Future; Generations; Glycoproteins; Goals; Growth Factor Receptors; Health; Human; Immune system; Immunodominant Epitopes; Immunosuppression; Immunotherapy; Knowledge; Link; Malignant Neoplasms; Malignant neoplasm of pancreas; Modeling; Molecular; Molecular Conformation; Monoclonal Antibodies; Morphology; Mucin 1 protein; Mucins; Nature; Neoplasm Metastasis; Oncology; Outcomes Research; Patients; Pharmaceutical Preparations; Polysaccharides; Protein Region; Proteins; Publishing; Research; Roentgen Rays; Role; Sea Urchins; Site; Stretching; Structure; Tandem Repeat Sequences; Therapeutic; Therapeutic antibodies; Tn antigen; cancer biomarkers; cancer cell; cancer immunotherapy; cancer therapy; chimeric antigen receptor T cells; computer studies; design; glycosylation; molecular recognition; neoplastic cell; novel; outcome forecast; overexpression; receptor; structural biology; success; sugar; therapeutic target; therapy development; tool; tumor growth; vaccine development

PROJECT SUMMARY Immunotherapy has become one of the central pillars of cancer treatment. The deployment of antibody-based therapies has transformed the lives of thousands of patients. A molecular understanding of how antibodies interact with their targets is invaluable for the development of new successful antibody drugs and immunotherapy products. One of the most important targets for the discovery of new cancer immunotherapies is the mucin family of glycoproteins. Mucin proteins are frequently overexpressed and display altered abnormal glycosylation in several types of adenocarcimona. However, despite the importance of mucin proteins as immunotherapy targets, little is known regarding how antibodies bind these proteins. To address this gap in our knowledge, we propose using a panel of antibodies that bind the mucins MUC1 and MUC16 as models to understand molecular recognition of these important therapeutic targets. Preliminary studies in our lab have demonstrated that glycosylation of MUC1 influences the conformational dynamics of epitopes which in turn influence antibody binding. We will expand our understanding of this phenomenon using a combination of structural biology, computational modeling and binding studies on a panel of MUC1 specific antibodies. Specifically, we aim to determine the role of cancer associated mucin glycosylation in antibody recognition of MUC1 (AIM 1). Previously published results suggest that MUC16 antibodies bind non-linear epitopes localized within the tandem-repeat region of the protein. This region is heavily glycosylated, and the role of MUC16 glycosylation on antibody binding is unknown. Preliminary studies in our lab have determined that a humanized MUC16 antibody binds to an epitope with a SEA domain. Using several therapeutic antibody candidates as models, we propose to employ structural and binding studies to characterize the nature of non-linear MUC16 epitopes recognized by therapeutic antibodies (AIM 2).

项目摘要 免疫疗法已成为癌症治疗的核心支柱之一。基于抗体的部署 这些疗法改变了成千上万患者的生活。从分子上理解抗体 与其靶点相互作用对于开发新的成功的抗体药物和免疫疗法是非常宝贵的 产品.发现新的癌症免疫疗法的最重要的靶点之一是粘蛋白家族 糖蛋白粘蛋白经常过表达，并显示出改变的异常糖基化， 几种类型的腺癌然而，尽管粘蛋白作为免疫疗法的重要性 靶点，关于抗体如何结合这些蛋白质知之甚少。为了弥补我们知识上的差距，我们 我建议使用一组结合粘蛋白MUC1和MUC16的抗体作为模型来理解分子生物学。 这些重要的治疗靶点。我们实验室的初步研究表明， MUC1的糖基化影响表位的构象动力学，这反过来影响抗体 约束力我们将结合结构生物学， 一组MUC1特异性抗体的计算建模和结合研究。具体而言，我们的目标是 确定癌症相关粘蛋白糖基化在MUC1（AIM 1）的抗体识别中的作用。先前 公开的结果表明MUC16抗体结合位于串联重复序列内的非线性表位 蛋白质的区域。该区域是高度糖基化的，并且MUC16糖基化对抗体的作用 绑定是未知的。我们实验室的初步研究已经确定，人源化MUC16抗体结合 具有SEA结构域的表位。使用几种治疗性抗体候选物作为模型，我们建议采用 结构和结合研究，以表征非线性MUC16表位的性质， 治疗性抗体（AIM 2）。