Canine MHC-I genotyping and tumor specific neoantigen determination

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.