Rationally guided discovery platform for monoclonal antibodies against carbohydrate antigens using virus-like particle conjugate immunization and high throughput selection

使用病毒样颗粒缀合物免疫和高通量选择的合理引导的针对碳水化合物抗原的单克隆抗体的发现平台

• 批准号: 10574738
• 负责人: Daniel Ray Woldring
• 金额: $ 22.76万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-10 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10574738
• 关键词: Address; Affinity; Antibodies; Antibody Binding Sites; Antigens; Binding; Biological Markers; Breast; Cancer Patient; Carbohydrates; Carrier Proteins; Cell Separation; Cell surface; Cells; Clinical; Complement-Dependent Cytotoxicity; Cytometry; Diagnostic; Directed Molecular Evolution; Disease; Disease Outcome; Engineering; Ensure; Enzymes; Epitope Mapping; Epitopes; Genomics; Glycopeptides; Glycoproteins; Human; Imaging Device; Immune response; Immune system; Immunization; Immunoglobulin Somatic Hypermutation; Individual; Libraries; Light; Malignant Neoplasms; Malignant neoplasm of ovary; Malignant neoplasm of pancreas; Methodology; Methods; Molecular; Monoclonal Antibodies; Mus; Ovarian; Pancreas; Patient-Focused Outcomes; Pattern; Performance; Phylogenetic Analysis; Phylogeny; Polysaccharides; Protein Engineering; Sensitivity and Specificity; Specificity; Technology; Therapeutic; Therapeutic Monoclonal Antibodies; Time; Transgenic Mice; Tumor Cell Line; Tumor-Associated Carbohydrate Antigens; Vaccines; Virus-like particle; Yeasts; biomarker discovery; cancer biomarkers; cancer diagnosis; clinical diagnosis; design; diagnostic tool; diagnostic value; empowerment; glycosylation; guided inquiry; improved; in vivo; interest; lead candidate; lead optimization; malignant breast neoplasm; molecular diagnostics; molecular imaging; neoplastic cell; novel; overexpression; reconstruction; specific biomarkers; tumor; tumorigenesis; tumorigenic; vaccine development

This project will establish a protein engineering platform for evolving monoclonal antibody binding affinity and specificity to solve the notorious challenge of developing clinical mAbs against tumor associated carbohydrate antigens (TACAs). Our central hypothesis is that the merger of Qβ carrier protein-elicited mAb discovery and rationally-guided directed evolution will outpace existing methodologies for discovering powerful antibodies against challenging TACA glycosylated biomarkers. TACAs are unique biomarkers to multiple tumor types, yet they have been underutilized for molecular imaging and diagnostics because of challenges in developing selective, potent binders. Distinct glycosylation patterns of tumor cell surfaces are hallmark features that arise during oncogenesis through changes in expression levels of glyco-processing enzymes. Problematically, these aberrant tumorigenic features are usually undetected by the immune system and rarely identified as non-self. Even when recognized as an antigen, weak binding against monovalent glycans leads to an insufficient immune response. To address this need, we will apply our directed evolution methodology to develop lead candidate mAbs against TACAs selective to cancer with in vivo binding of KD<10nM and specificity >100-fold binding above control cells. This will be accomplished by first generating a diverse panel of TACA-specific antibodies via immunization of transgenic mice with multivalent Qβ vaccines. Dominant antibodies will be isolated and characterized for paratope diversity and the ability to selectively bind the glyco-targets. Next, we use rationally- guided directed evolution to achieve mAb binding affinity and specificity. Multiple TACA-specific mAbs obtained through immunization will undergo high-throughput yeast display directed evolution with site-wise diversification based on structural, stabilizing, and phylogenetic factors to overcome the routinely low affinity of anti-carbohydrate binders. Specificity and affinity will be evaluated against multiple human tumor cell lines. This project will: 1) establish a platform that drastically reduces initial discovery time for translatable molecular imaging and diagnostic tools against carbohydrate antigens; 2) significantly advance understanding of tumorigenic cell glycosylation patterns; and 3) mark a major step towards improving sensitivity and specificity of biomarker-based diagnosis of cancers including ovarian, breast, and pancreatic cancers.

该项目将建立一个蛋白质工程平台，用于进化单克隆抗体结合亲和力和 特异性解决开发针对肿瘤相关碳水化合物的临床单克隆抗体的臭名昭著的挑战 我们的中心假设是 Qβ 载体蛋白的合并引发了 mAb 的发现和 理性引导的定向进化将超越发现强大抗体的现有方法 对抗具有挑战性的 TACA 糖基化生物标志物。 TACA 是多种肿瘤类型的独特生物标志物，但在分子成像方面尚未得到充分利用 和诊断，因为开发选择性、有效的糖基化模式面临挑战。 肿瘤细胞表面的变化是肿瘤发生过程中通过表达变化而出现的标志性特征 问题在于，这些异常的致瘤特征通常是糖加工酶的水平。 未被免疫系统检测到，并且很少被识别为非自身，即使被识别为抗原， 与单价聚糖的弱结合导致免疫反应不足。 为了满足这一需求，我们将应用定向进化方法来开发主要候选单克隆抗体 抗 TACA 对癌症具有选择性，体内结合 KD<10nM，特异性 >100 倍以上结合 这将通过首先通过生成多种 TACA 特异性抗体来实现。 将分离并用多价Qβ疫苗对转基因小鼠进行免疫。 其特征在于互补位多样性和选择性结合糖靶标的能力接下来，我们合理地使用- 指导定向进化以获得单克隆抗体结合亲和力和特异性。 通过免疫将进行高通量酵母展示定向进化与位点 基于结构、稳定和系统发育因素的多样化，以克服亲和力通常较低的问题 抗碳水化合物结合剂的特异性和亲和力将针对多种人类肿瘤细胞系进行评估。 该项目将：1）建立一个平台，大大缩短可翻译分子的初始发现时间 针对碳水化合物抗原的成像和诊断工具；2) 显着增进对碳水化合物抗原的理解； 致瘤细胞糖基化模式；3) 标志着朝着提高敏感性和特异性迈出的重要一步 基于生物标志物的癌症诊断，包括卵巢癌、乳腺癌和胰腺癌。