Therapeutic Antibody Discovery from Pancreatic Cancer B Cell Repertoires

从胰腺癌 B 细胞库中发现治疗性抗体

• 批准号: 8832750
• 负责人: David Scott Johnson
• 金额: $ 21.75万
• 依托单位: GIGAGEN, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-26 至 2016-05-25
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8832750
• 关键词: Address; Affinity; Antibodies; Antigen Targeting; Antigens; Antineoplastic Agents; B cell repertoire; B-Lymphocytes; Bioinformatics; Caliber; Cancer Patient; Capital; Cells; Clinical; Clinical Data; Computing Methodologies; DNA Library; Data; Detection; Development; Diagnostic; Drug Targeting; Elderly; Evolution; Fertilization in Vitro; Frequencies; Generations; Genomics; Geometry; Guilt; Health; Human; Hybridomas; Immunoglobulins; Industry; Knowledge; Laboratories; Lead; Libraries; Licensing; Light; Light-Chain Immunoglobulins; Link; Malignant Neoplasms; Malignant neoplasm of pancreas; Mammalian Cell; Methodology; Methods; Metric; Microfluidic Microchips; Microfluidics; Mining; Mission; Molecular; Molecular Target; Monoclonal Antibodies; Mus; Neoplasm Metastasis; Pancreas; Patients; Phage Display; Pharmaceutical Preparations; Phase; Phase I Clinical Trials; Plasma Cells; Probability; Proteins; Protocols documentation; Research; Services; Small Business Innovation Research Grant; Sorting - Cell Movement; Staging; Technology; Testing; Therapeutic; Therapeutic Agents; Therapeutic antibodies; Time; Tissues; Tube; Tumor-Infiltrating Lymphocytes; United States National Institutes of Health; angiogenesis; clinical efficacy; cost; cytokine; deep sequencing; digital; drug candidate; immunogenicity; in vivo; innovation; monomer; next generation sequencing; novel; oncology; pancreatic neoplasm; peripheral blood; pre-clinical; programs; research study; tumor

DESCRIPTION (provided by applicant): The Specific Aim of this SBIR Phase I project is to build a technology for discovery of monoclonal antibody (mAb) drug candidates for pancreatic cancer from rare primary B cells. Pancreatic cancer has proven resilient to drugs that target oncology's "usual suspects", including proteins related to angiogenesis, proliferation, and metastasis (Mackenzie & McCollum, 2009). mAbs are therapeutic agents of choice for oncology (Gura, 2002; Elder, 2011). Traditionally, mAb discovery programs identify a lead target antigen and screen antibody libraries for affinity using either phage display or mouse hybridomas. As an alternative, some academic and industry groups have been using human B cell hybridomas (Lang et al., 1990; Yu et al., 2008) to mine natural repertoires for candidate therapeutic antibodies. B cell hybridomas are technically challenging and inefficient, but natural antibodies have several advantages, including low immunogenicity, in vivo affinity maturation, and excellent expressability in mammalian cells (Hoet et al., 2005; Beerli & Rader, 2010). Next-generation sequencing (NGS) deep repertoire sequencing methods may help overcome the technical problems with B cell repertoire mining. Canonical NGS methods are used to deep sequence immunoglobulin (Ig) heavy or light monomers produced by clonal B or plasma cells. However, conventional NGS methods miss the single-cell context of paired Ig, requiring guesswork to pair Ig monomers and affinity screen (Reddy et al., 2010). GigaGen uses high-tech genomics to generate, for the first time, DNA libraries with native Ig pairing from millions o single human B cells. We address many of the shortcomings with existing methodologies through the following innovations: (i) deep droplet digital single cell genomics; (ii) detection of affinity maturation in vivo; (iii) comparisons among tissues, time points, and patients; and (iv) integration with protein display. In Phase I, we will adapt our technology specifically for pancreatic cancer mAb discovery. First, in order to capture rare antibodies, we will increase the cell throughput of our microfluidic device at least tenfold. Second, we will develop protocols for disaggregation of tumor infiltrating B cells (TIL-Bs) from pancreatic tumors. We will accomplish the Specific Aim by performing the following tasks: (i) Validate a novel microfluidic chip geometry for >10x higher cell throughput; (ii) Test methods for disaggregation and sorting of TIL-Bs from pancreatic tumors; and (iii) Sequence pancreatic cancer patient peripheral blood and TIL-Bs to discover lineages undergoing affinity maturation. We will be successful if we achieve the following metrics: (i) Generate droplets at 60-200μm in diameter, <5% droplet merging, multiple-cell encapsulation rates of <3%, and cell throughput of at least 400Hz across at least 20 experiments; (ii) Mis-linking of heavy and light chain Ig should not differ significanty between libraries generated on the old and new chips (two-proportion z-test; α=0.05; power=0.8); (iii) Recover at least 100,000 unique B cell clones from each of 6 pancreatic TIL-B libraries; and (iv) Discover >10 Ig sequences undergoing affinity maturation and shared between TIL-Bs and peripheral blood from the same patient, or undergoing convergent evolution. Phase I will generate a curated list of candidate antibodies with strong therapeutic potential. In Phase II, we will bring our candidate mAbs through standard preclinical development (Zhao et al., 2009). We expect this stage of development to cost $1-2m and last 18-24 months. By the end of Phase II, we hope to have sufficient data for clinical development of a novel lead mAb, either with a biopharma partner or by raising venture capital.

描述（由申请方提供）：该SBIR I期项目的具体目的是建立一种从罕见的原代B细胞中发现胰腺癌单克隆抗体（mAb）候选药物的技术。胰腺癌已被证明对靶向肿瘤学的“通常嫌疑人”的药物具有弹性，包括与血管生成、增殖和转移相关的蛋白质（麦肯齐和麦科勒姆，2009）。mAb是肿瘤学的首选治疗剂（Gura，2002; Elder，2011）。传统上，mAb发现程序鉴定前导靶抗原并使用噬菌体展示或小鼠杂交瘤筛选抗体文库的亲和力。作为替代，一些学术和工业团体已经使用人B细胞杂交瘤（Lang et al.，1990; Yu等人，2008）来挖掘候选治疗性抗体的天然库。B细胞杂交瘤在技术上具有挑战性且效率低下，但天然抗体具有几个优点，包括低免疫原性、体内亲和力成熟和在哺乳动物细胞中的优异表达能力（Hoet et al.，2005; Beerli & Rader，2010）。下一代测序（NGS）深度库测序方法可能有助于克服B细胞库挖掘的技术问题。典型NGS方法用于对克隆B或浆细胞产生的免疫球蛋白（IG）重链或轻链单体进行深度测序。然而，常规的NGS方法错过了配对的IG的单细胞背景，需要猜测来配对IG单体和亲和筛选（Reddy等人，2010年）。GigaGen使用高科技基因组学首次从数百万个单个人类B细胞中产生具有天然IG配对的DNA文库。我们通过以下创新解决了现有方法的许多缺点：（i）深滴数字单细胞基因组学;（ii）体内亲和力成熟的检测;（iii）组织，时间点和患者之间的比较;以及（iv）与蛋白质展示的整合。在第一阶段，我们将调整我们的技术，专门用于胰腺癌mAb的发现。首先，为了捕获稀有抗体，我们将把微流控装置的细胞通量提高至少十倍。第二，我们将开发从胰腺肿瘤中分离肿瘤浸润性B细胞（TIL-Bs）的方案。我们将通过执行以下任务来实现具体目标：（i）构建一种新的微流体芯片几何结构，用于> 10倍更高的细胞通量;（ii）用于来自胰腺肿瘤的TIL-B的解聚和分选的测试方法;以及（iii）对胰腺癌患者外周血和TIL-B进行测序，以发现经历亲和力成熟的谱系。如果我们达到以下指标，我们将是成功的：（i）产生直径为60-200μm的液滴，<5%的液滴合并，<3%的多细胞包封率，以及在至少20次实验中至少400 Hz的细胞通量;（ii）在旧芯片和新芯片上产生的文库之间，重链和轻链IG的错误连接不应有显著差异（双比例z检验; α=0.05;功效=0.8）;（iii）从6个胰腺TIL-B文库中的每一个回收至少100，000个独特的B细胞克隆;和（iv）发现>10个经历亲和力成熟并且在来自同一患者的TIL-B和外周血之间共享或经历趋同进化的IG序列。第一阶段将产生一个具有强大治疗潜力的候选抗体的精选列表。在II期，我们将通过标准临床前开发带来我们的候选mAb（Zhao等人，2009年）。我们预计这一阶段的开发将花费100万至200万美元，持续18至24个月。到第二阶段结束时，我们希望有足够的数据用于临床开发一种新的先导mAb，无论是与生物制药合作伙伴还是通过筹集风险资本。