Canine MHC-I genotyping and tumor specific neoantigen determination

犬 MHC-I 基因分型和肿瘤特异性新抗原测定

• 批准号: 10220542
• 负责人: William Hildebrand
• 金额: $ 49.2万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-11 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10220542
• 关键词: Address; Advanced Malignant Neoplasm; Algorithms; Alleles; Base Pairing; Behavior Therapy; Binding; Canis familiaris; Cell Culture Techniques; Cell Line; Cells; Clinical; Clinical Data; Clinical Trials; Collaborations; Crystallization; Data; Data Analyses; Data Commons; Databases; Development; Etiology; Funding; Genome; Genotype; Heterogeneity; Human; Immune system; Institutes; Major Histocompatibility Complex; Malignant Neoplasms; Mass Spectrum Analysis; Measures; Modeling; Molecular; National Cancer Institute; Neural Network Simulation; Oncology; Outcome; Peptides; Population; Pre-Clinical Model; Proteins; Publishing; Quality Control; Research; Resources; Rodent Model; Sampling; Sequence Read Archive; Software Tools; Structure; Time; Training; Translating; Translational Research; Treatment outcome; Vaccination; Validation; Work; artificial neural network; cancer immunotherapy; cancer prevention; cancer therapy; data resource; exome sequencing; experience; genome sequencing; human genomics; immunogenicity; immunotherapy trials; mutant; neoantigens; next generation sequencing; pre-clinical; prevent; software development; success; tool; transcriptome; transcriptome sequencing; translational model; tumor; whole genome

Abstract Being naturally occurring and with an intact immune system, spontaneous cancers in pet dogs have the potential to effectively bridge a current gap between preclinical models and human clinical trials, advancing cancer immunotherapy. However, a current lack of essential resources creates roadblocks to the effective use of canine cancers. The deficiency is clearly seen in predicting tumor-specific neoantigen (TSNA), attractive targets in cancer treatment and prevention. TSNAs arise when intracellular mutant peptides, created by cancer-associated somatic alterations, are presented by the cell’s histocompatibility complex class I (MHC-I) molecules. Hence, MHC-I genotyping is a prerequisite for TSNA prediction. However, with few MHC-I alleles known to date, MHC-I genotyping for the dog is a significant challenge. Moreover, because of the very limited MHC-I protein crystal structures and experimental peptide binding data, there currently lack public tools to predict TSNAs specifically for the dog, in contrast to the human with many tools developed. With the next generation sequencing (NGS) data published for thousands of dogs from hundreds of breeds, now is the time to address these deficiencies. We propose to combine our expertise, NGS data analysis by the Zhao (PI) lab and MHC-I characterization by the Hildebrand (MPI) lab, to develop software tools and data resources for large scale MHC-I genotyping and systematic TSNA prediction for the dog. We will also genotype MHC-I alleles of thousands of dogs sequenced and predict TSNAs for hundreds of canine tumors characterized. We will use our proposed MHC-I genotype and TSNA discovery tools to assist a NCI-funded immunotherapy trial via collaboration with Dr. Steven Dow, and the Vaccination Against Canine Cancer Study (VACCS) trial via collaboration with Dr. Douglas Thamm. By establishing resources that are critically missing at present, our work will significantly enhance the applicability of the dog model for translational research.

摘要 由于是自然发生的，具有完整的免疫系统，宠物狗的自发性癌症具有 有可能有效地弥合临床前模型和人类临床试验之间的差距，取得进展 癌症免疫疗法。然而，目前缺乏必要的资源给有效利用造成了障碍。 患上犬癌。这一缺陷在预测肿瘤特异性新抗原(TSNA)方面明显存在，很吸引人 癌症治疗和预防的目标。TSNAs产生于细胞内突变多肽，由 与癌症相关的体细胞改变，由细胞的组织相容性复合体I类(MHC-I)呈现 分子。因此，MHC-I基因分型是预测TSNA的先决条件。然而，由于MHC-I等位基因很少 到目前为止，对狗进行MHC-I基因分型是一个巨大的挑战。此外，由于非常有限的 MHC-I蛋白晶体结构和实验多肽结合数据，目前还缺乏公共工具来 预测专门针对狗的TSNA，与开发了许多工具的人类相反。 随着来自数百个品种的数千只狗的下一代测序(NGS)数据的公布， 现在是解决这些不足的时候了。我们建议结合我们的专业知识，通过以下方式进行NGS数据分析 由希尔德布兰德(MPI)实验室进行赵(PI)实验室和MHC-I表征，以开发软件工具和数据 犬MHC-I大规模基因分型和TSNA系统预测的资源。我们还将 对数千只犬的MHC-I等位基因进行测序并预测数百种犬肿瘤的TSNAs 特色化的。我们将使用我们建议的MHC-I基因和TSNA发现工具来帮助NCI资助的 与Steven Dow博士合作进行的免疫治疗试验和犬癌疫苗接种研究 (VACCS)试验通过与道格拉斯·塔姆博士的合作进行。 通过建立目前严重缺失的资源，我们的工作将显著增强 狗模型在翻译研究中的适用性。