Genomic analysis across 53 canine cancer types reveals novel mutations and high clinical actionability potential.

A genomic understanding of the oncogenic processes and individual variability of human cancer has steadily fueled improvement in patient outcomes over the past 20 years. Mutations within tumour tissues are routinely assessed through clinical genomic diagnostic assays by academic and commercial laboratories to facilitate diagnosis, prognosis and effective treatment stratification. The application of genomics has unveiled a wealth of mutation-based biomarkers in canine cancers, suggesting that the transformative principles that have revolutionized human cancer medicine can be brought to bear in veterinary oncology. To advance clinical genomics and genomics-guided medicine in canine oncology, we have developed and validated a canine cancer next-generation sequencing gene panel for the identification of multiple mutation types in clinical specimens. With this panel, we examined the genomic landscapes of 828 tumours from 813 dogs, spanning 53 cancer types. We identified 7856 alterations, encompassing copy number variants, single nucleotide variants, indels and internal tandem duplications. Additionally, we evaluated the clinical utility of these alterations by incorporating a biomarker framework from comprehensive curation of primary canine literature and inferences from human cancer genomic biomarker literature and clinical diagnostics. Remarkably, nearly 90% of the cases exhibited mutations with diagnostic, prognostic or therapeutic implications. Our work represents a thorough assessment of genomic landscapes in a large cohort of canine cancers, the first of its kind for its comprehensive inclusion of multiple mutation types and structured annotation of biomarkers, demonstrating the clinical potential of leveraging mutation-based biomarkers in veterinary oncology.

Standing in the canine precision medicine knowledge gap: Improving annotation of canine cancer genomic biomarkers through systematic comparative analysis of human cancer mutations in COSMIC.

The accrual of cancer mutation data and related functional and clinical associations have revolutionised human oncology, enabling the advancement of precision medicine and biomarker-guided clinical management. The catalogue of cancer mutations is also growing in canine cancers. However, without direct high-powered functional data in dogs, it remains challenging to interpret and utilise them in research and clinical settings. It is well-recognised that canine and human cancers share genetic, molecular and phenotypic similarities. Therefore, leveraging the massive wealth of human mutation data may help advance canine oncology. Here, we present a structured analysis of sequence conservation and conversion of human mutations to the canine genome through a 'caninisation' process. We applied this analysis to COSMIC, the Catalogue of Somatic Mutations in Cancer, the most prominent human cancer mutation database. For the project's initial phase, we focused on the subset of the COSMIC data corresponding to Cancer Gene Census (CGC) genes. A total of 670 canine orthologs were found for 721 CGC genes. In these genes, 365 K unique mutations across 160 tumour types were converted successfully to canine coordinates. We identified shared putative cancer-driving mutations, including pathogenic and hotspot mutations and mutations bearing similar biomarker associations with diagnostic, prognostic and therapeutic utility. Thus, this structured caninisation of human cancer mutations facilitates the interpretation and annotation of canine mutations and helps bridge the knowledge gap to enable canine precision medicine.

Genomic tumor analysis provides clinical guidance for the management of diagnostically challenging cancers in dogs.

OBJECTIVE: To evaluate the diagnostic, prognostic, and therapeutic utility of a cancer genomic diagnostic assay (SearchLight DNA; Vidium Animal Health) for diagnostically ambiguous cancer cases. ANIMALS: 69 privately owned dogs with ambiguous cancer diagnoses and for which the genomic assay was performed. PROCEDURES: Genomic assay reports generated between September 28, 2020, and July 31, 2022, for dogs with malignancy or suspected malignancy were reviewed to determine the assay's clinical utility defined as providing diagnostic clarity, prognostic information, and/or therapeutic options. RESULTS: Genomic analysis provided diagnostic clarity in 37 of 69 cases (54%; group 1) and therapeutic and/or prognostic information in 22 of the remaining 32 cases (69%; group 2) for which the diagnosis remained elusive. Overall, the genomic assay was clinically useful in 86% (59/69) of cases. CLINICAL RELEVANCE: To our knowledge, this was the first study to evaluate the multifaceted clinical utility of a single cancer genomic test in veterinary medicine. Study findings supported the use of tumor genomic testing for dogs with cancer, particularly those that are diagnostically ambiguous and therefore inherently challenging to manage. This evidence-driven genomic assay provided diagnostic guidance, prognostic support, and therapeutic options for most patients with an unclear cancer diagnosis that would otherwise have an unsubstantiated clinical plan. Furthermore, 38% (26/69) of samples were easily obtained aspirates. Sample factors (sample type, percentage of tumor cells, and number of mutations) did not influence diagnostic yield. Our study demonstrated the value of genomic testing for the management of canine cancer.

Immune epitope database analysis resource.

The immune epitope database analysis resource (IEDB-AR: http://tools.iedb.org) is a collection of tools for prediction and analysis of molecular targets of T- and B-cell immune responses (i.e. epitopes). Since its last publication in the NAR webserver issue in 2008, a new generation of peptide:MHC binding and T-cell epitope predictive tools have been added. As validated by different labs and in the first international competition for predicting peptide:MHC-I binding, their predictive performances have improved considerably. In addition, a new B-cell epitope prediction tool was added, and the homology mapping tool was updated to enable mapping of discontinuous epitopes onto 3D structures. Furthermore, to serve a wider range of users, the number of ways in which IEDB-AR can be accessed has been expanded. Specifically, the predictive tools can be programmatically accessed using a web interface and can also be downloaded as software packages.

Immune epitope database analysis resource (IEDB-AR).

We present a new release of the immune epitope database analysis resource (IEDB-AR, http://tools.immuneepitope.org), a repository of web-based tools for the prediction and analysis of immune epitopes. New functionalities have been added to most of the previously implemented tools, and a total of eight new tools were added, including two B-cell epitope prediction tools, four T-cell epitope prediction tools and two analysis tools.