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站在犬类精准医学的知识鸿沟前:通过对COSMIC中人类癌症突变进行系统比较分析来改善犬类癌症基因组生物标志物的注释。

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.

作者信息

Sakthikumar Sharadha, Facista Salvatore, Whitley Derick, Byron Sara A, Ahmed Zeeshan, Warrier Manisha, Zhu Zhanyang, Chon Esther, Banovich Kathryn, Haworth David, Hendricks William P D, Wang Guannan

机构信息

Vidium Animal Health, a TGen Subsidiary, Phoenix, Arizona, USA.

Translational Genomics Research Institute, Phoenix, Arizona, USA.

出版信息

Vet Comp Oncol. 2023 Sep;21(3):482-491. doi: 10.1111/vco.12911. Epub 2023 May 29.

Abstract

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.

摘要

癌症突变数据以及相关功能和临床关联的积累已经彻底改变了人类肿瘤学,推动了精准医学和生物标志物指导的临床管理的发展。犬类癌症中的癌症突变目录也在不断增加。然而,由于缺乏犬类直接的高功率功能数据,在研究和临床环境中对其进行解释和利用仍然具有挑战性。众所周知,犬类和人类癌症在遗传、分子和表型上具有相似性。因此,利用大量的人类突变数据可能有助于推动犬类肿瘤学的发展。在这里,我们通过一个“犬化”过程对序列保守性以及人类突变向犬类基因组的转化进行了结构化分析。我们将此分析应用于COSMIC(癌症体细胞突变目录),这是最著名的人类癌症突变数据库。在该项目的初始阶段,我们专注于COSMIC数据中与癌症基因普查(CGC)基因相对应的子集。在721个CGC基因中总共发现了670个犬类直系同源基因。在这些基因中,跨越160种肿瘤类型的36.5万个独特突变成功地转化为犬类坐标。我们鉴定出了共同的假定癌症驱动突变,包括致病性和热点突变以及与诊断、预后和治疗效用具有相似生物标志物关联的突变。因此,这种对人类癌症突变的结构化犬化有助于对犬类突变进行解释和注释,并有助于弥合知识差距以实现犬类精准医学。

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