...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Data-driven unbiased curation of the TP53 tumor suppressor gene mutation database and validation by ultradeep sequencing of human tumors
【24h】

Data-driven unbiased curation of the TP53 tumor suppressor gene mutation database and validation by ultradeep sequencing of human tumors

机译：数据驱动的TP53抑癌基因突变数据库的无偏向策划和超深测序对人类肿瘤的验证

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Cancer mutation databases are expected to play central roles in personalized medicine by providing targets for drug development and biomarkers to tailor treatments to each patient. The accuracy of reported mutations is a critical issue that is commonly overlooked, which leads to mutation databases that include a sizable number of spurious mutations, either sequencing errors or passenger mutations. Here we report an analysis of the latest version of the TP53 mutation database, including 34,453 mutations. By using several data-driven methods on multiple independent quality criteria, we obtained a quality score for each report contributing to the database. This score can now be used to filter for high-confidence mutations and reports within the database. Sequencing the entire TP53 gene from various types of cancer using next-generation sequencing with ultradeep coverage validated our approach for curation. In summary, 9.7% of all collected studies, mostly comprising numerous tumors with multiple infrequent TP53 mutations, should be excluded when analyzing TP53 mutations. Thus, by combining statistical and experimental analyses, we provide a curated mutation database for TP53 mutations and a framework for mutation database analysis.
机译：通过为药物开发和生物标记物提供针对每个患者的治疗方法，癌症突变数据库有望在个性化医学中发挥中心作用。报告的突变的准确性是一个通常被忽视的关键问题，这导致突变数据库包括大量的伪突变，包括测序错误或过客突变。在这里，我们报告了对TP53突变数据库的最新版本的分析，包括34,453个突变。通过在多个独立的质量标准上使用几种数据驱动的方法，我们为贡献给数据库的每个报告获得了质量得分。该分数现在可以用于过滤数据库中的高可信度突变和报告。使用具有超深覆盖率的下一代测序对来自各种类型癌症的整个TP53基因进行测序，验证了我们的治愈方法。总而言之，在分析TP53突变时，应排除所有收集的研究的9.7％，其中大多数是由多个不常见的TP53突变的肿瘤组成。因此，通过结合统计和实验分析，我们提供了一个针对TP53突变的精选突变数据库和一个针对突变数据库分析的框架。

著录项

  • 来源
  • 作者

    Karolina Edlund; Ola Larsson; Adam Ameur; Ignas Bunikis; Ulf Gyllensten; Bernard Leroy; Magnus Sundstroem; Patrick Micke; Johan Botling; Thierry Soussi;

  • 作者单位

    Department of Immunology, Genetics, and Pathology, and Uppsala University, SE-751 85 Uppsala, Sweden;

    Department of Oncology-Pathology, Cancer Center Karolinska, Karolinska Institute, SE-171 76 Stockholm, Sweden;

    SciLifeLab Uppsala, Uppsala University, SE-751 85 Uppsala, Sweden;

    SciLifeLab Uppsala, Uppsala University, SE-751 85 Uppsala, Sweden;

    SciLifeLab Uppsala, Uppsala University, SE-751 85 Uppsala, Sweden;

    Universite Pierre et Marie Curie-Paris6, 75005 Paris, France;

    Department of Immunology, Genetics, and Pathology, and Uppsala University, SE-751 85 Uppsala, Sweden;

    Department of Immunology, Genetics, and Pathology, and Uppsala University, SE-751 85 Uppsala, Sweden;

    Department of Immunology, Genetics, and Pathology, and Uppsala University, SE-751 85 Uppsala, Sweden;

    Department of Oncology-Pathology, Cancer Center Karolinska, Karolinska Institute, SE-171 76 Stockholm, Sweden,Universite Pierre et Marie Curie-Paris6, 75005 Paris, France;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    cancer genetics; genomic; locus-specific database;

    机译：癌症遗传学;基因组特定地点的数据库;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号