Role of Antigen Glycosylation in Mucin Binding by Monoclonal Antibodies

项目总结 免疫治疗已成为癌症治疗的中心支柱之一。以抗体为基础的部署 治疗已经改变了成千上万患者的生活。对抗体如何产生的分子理解 与其靶点的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最重要的靶点之一是粘蛋白家族。 糖蛋白。粘蛋白蛋白经常过度表达，并表现为异常糖基化改变 几种类型的腺鳞癌。然而，尽管粘蛋白蛋白作为免疫疗法的重要性 对于抗体是如何结合这些蛋白质的，人们知之甚少。为了解决我们知识中的这一差距，我们 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 认识到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，进而影响抗体 有约束力的。我们将结合结构生物学来扩大我们对这一现象的理解， 对一组MUC1特异性抗体进行计算建模和结合研究。具体来说，我们的目标是 确定肿瘤相关粘蛋白糖基化在抗体识别MUC1(AIM 1)中的作用。先前 已发表的结果表明，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。该区域高度糖基化，MUC16糖基化对抗体的作用 绑定未知。我们实验室的初步研究已经确定人源化的MUC16抗体与 一个具有海洋领域的表位。使用几个候选的治疗性抗体作为模型，我们建议使用 结构和结合研究以表征被识别的非线性MUC16表位的性质 治疗性抗体(AIM 2)。

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).