CancerVar: An artificial intelligence-empowered platform for clinical interpretation of somatic mutations in cancer.
CancerVar: An artificial intelligence-empowered platform for clinical interpretation of somatic mutations in cancer.
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DOI：
10.1126/sciadv.abj1624
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发表时间：
2022-05-06
期刊：
影响因子：
13.6
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中科院分区：
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手动整理了几个知识库，以支持对癌症中数千个热点体细胞突变的临床解释。然而，在这些数据库中观察到了不一致甚至相互矛盾的解释。此外，许多以前没有记录的突变可能对癌症有临床或功能影响，但现有的知识库没有系统地解释这些突变。为了应对这些挑战，我们开发了CancerVar，以便于根据AMP/ASCO/CAP 2017指南对1300万个体细胞突变进行自动化和标准化解释。我们进一步介绍了一个深度学习框架，以使用功能和临床特征来预测这些变体的致瘤性。与几个独立的知识库相比，CancerVar取得了令人满意的性能，并使用临床精选的数据集，展示了在体细胞变异分类中的实用价值。总之，通过将临床指南与深度学习框架相结合，CancerVar促进了体细胞变体的临床解释，减少了人工工作，提高了变体分类的一致性，并促进了指南的实施。CancerVar是一个基于AMP/ASCO/CAP 2017指南和深度学习的自动化体细胞变异解释工具。
Several knowledgebases are manually curated to support clinical interpretations of thousands of hotspot somatic mutations in cancer. However, discrepancies or even conflicting interpretations are observed among these databases. Furthermore, many previously undocumented mutations may have clinical or functional impacts on cancer but are not systematically interpreted by existing knowledgebases. To address these challenges, we developed CancerVar to facilitate automated and standardized interpretations for 13 million somatic mutations based on the AMP/ASCO/CAP 2017 guidelines. We further introduced a deep learning framework to predict oncogenicity for these variants using both functional and clinical features. CancerVar achieved satisfactory performance when compared to several independent knowledgebases and, using clinically curated datasets, demonstrated practical utility in classifying somatic variants. In summary, by integrating clinical guidelines with a deep learning framework, CancerVar facilitates clinical interpretation of somatic variants, reduces manual work, improves consistency in variant classification, and promotes implementation of the guidelines. CancerVar is an automated tool for somatic variant interpretation based on the AMP/ASCO/CAP 2017 guidelines and deep learning.