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.

本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， 特异性，以解决开发针对肿瘤相关碳水化合物的临床mAb的臭名昭著的挑战 抗原（TACAs）。我们的中心假设是，Qβ载体蛋白的合并引发了mAb的发现， 理性引导的定向进化将超越现有的发现强大抗体的方法 针对挑战性的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，但它们在分子成像中的应用不足 和诊断，因为在开发选择性的，有效的粘合剂的挑战。不同的糖基化模式 是肿瘤发生过程中通过表达改变而出现的标志性特征。 糖加工酶的水平。问题是，这些异常的致瘤特征通常是 不被免疫系统发现，很少被识别为非自我。即使被识别为抗原， 对单价聚糖的弱结合导致免疫应答不足。 为了满足这一需求，我们将应用我们的定向进化方法来开发领先的候选mAb 针对对癌症具有选择性的TACA，体内结合KD高于<10nM and specificity >100倍结合 对照细胞。这将通过首先通过以下途径产生一组不同的TACA特异性抗体来实现： 用多价Qβ疫苗免疫转基因小鼠。将分离优势抗体， 其特征在于互补位多样性和选择性结合糖靶的能力。接下来，我们理性地使用- 指导定向进化以实现mAb结合亲和力和特异性。获得多个TACA特异性mAb 通过免疫将进行高通量酵母展示定向进化， 多样化的基础上的结构，稳定，和系统发育因素，以克服常规的低亲和力， 抗碳水化合物粘合剂。将针对多种人肿瘤细胞系评价特异性和亲和力。 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）显著提高对 致瘤细胞糖基化模式;和3）标志着朝着提高灵敏度和特异性迈出了重要一步 基于生物标志物的癌症诊断，包括卵巢癌、乳腺癌和胰腺癌。