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

癌症 宇宙癌症数据库 医学 精密医学 癌症生物标志物 计算生物学 突变 肿瘤科 生物信息学 癌症研究 生物 病理 内科学 遗传学 基因
作者
Sharadha Sakthikumar,Salvatore Facista,Derick Whitley,Sara A. Byron,Zeeshan Ahmed,Manisha Warrier,Zhanyang Zhu,Esther Chon,Kathryn Banovich,David Haworth,William P.D. Hendricks,Guannan Wang
出处
期刊:Veterinary and Comparative Oncology [Wiley]
卷期号:21 (3): 482-491 被引量:3
标识
DOI:10.1111/vco.12911
摘要

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.
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