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

基本信息

批准号：
10630913
负责人：
William Hildebrand
金额：
$ 46.27万
依托单位：
UNIVERSITY OF GEORGIA
依托单位国家：
美国
项目类别：
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/10630913
关键词：
Acceleration Address Advanced Malignant Neoplasm Algorithms Alleles Base Pairing Behavior Binding Breeding Canis familiaris Cell Culture Techniques Cell Line Cells Clinical Clinical Data Clinical Trials Collaborations Data Data Analyses Data Commons Databases Development Etiology Funding Genome Genotype Heterogeneity Human Immune system Major Histocompatibility Complex Malignant Neoplasms Mass Spectrum Analysis Measures Modeling Molecular National Cancer Institute Neural Network Simulation Oncology Outcome Peptides Population Pre-Clinical Model Procedures Proteins Publishing Quality Control Research Resources Rodent Model Sampling Sequence Read Archive Software Tools Structure Time Training Translating Translational Research Vaccination Validation Work artificial neural network cancer immunotherapy cancer prevention cancer therapy canine model data resource exome sequencing experience genome sequencing human genomics immunogenicity immunotherapy trials mutant neoantigens next generation sequencing pre-clinical predictive tools prevent software development success tool transcriptome transcriptome sequencing treatment and outcome tumor whole genome

项目摘要

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.

抽象的宠物狗的自发性癌症是自然发生的且具有完整的免疫系统，因此具有有潜力有效弥合当前临床前模型和人体临床试验之间的差距，推进然而，目前缺乏必要的资源为有效利用癌症免疫疗法造成了障碍。这种缺陷在预测肿瘤特异性新抗原（TSNA）方面很明显，很有吸引力。癌症治疗和预防中的靶点是由细胞内突变肽产生的。癌症相关的体细胞改变由细胞的 I 类组织相容性复合体 (MHC-I) 呈现因此，MHC-I 基因分型是 TSNA 预测的先决条件。然而，MHC-I 等位基因很少。迄今为止，MHC-I 基因分型对于狗来说是一个重大挑战，而且由于其非常有限。 MHC-I蛋白晶体结构和实验肽结合数据，目前缺乏公共工具与开发了许多工具的人类相比，专门为狗预测 TSNA。随着数百个品种的数千只狗的下一代测序（NGS）数据的发布，现在是解决这些缺陷的时候了，我们建议将我们的专业知识与 NGS 数据分析结合起来。赵 (PI) 实验室和 Hildebrand (MPI) 实验室的 MHC-I 表征，开发软件工具和数据我们还将为狗提供大规模 MHC-I 基因分型和系统 TSNA 预测的资源。对数千只狗的基因型 MHC-I 等位基因进行测序并预测数百种犬肿瘤的 TSNA 我们将使用我们提出的 MHC-I 基因型和 TSNA 发现工具来协助 NCI 资助的项目。与 Steven Dow 博士合作进行的免疫治疗试验以及犬癌症疫苗接种研究 (VACCS) 试验是与 Douglas Thamm 博士合作进行的。通过建立目前严重缺失的资源，我们的工作将显着增强狗模型在转化研究中的适用性。