COSMIC (the Catalogue of Somatic Mutations in Cancer): a resource to investigate acquired mutations in human cancer
COSMIC (the Catalogue of Somatic Mutations in Cancer): a resource to investigate acquired mutations in human cancer
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DOI：
10.1093/nar/gkp995
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发表时间：
2010-01-01
影响因子：
14.9
通讯作者：
Futreal, P. Andrew
中科院分区：
文献类型：
--
作者：
Forbes, Simon A.;Tang, Gurpreet;Futreal, P. Andrew
癌症体细胞突变目录（COSMIC）（http://www.sanger.ac.uk/cosmic/）是有关人类癌症体细胞获得性突变信息的最大公共资源，可无限制免费获取。目前（2009年8月第43版），COSMIC包含了在近370,000个肿瘤中的13,423个基因上进行的150万次实验的详细信息，描述了超过90,000个个体突变。数据来自两个来源，科学文献中的出版物（第43版包含7797篇精选文章）以及英国桑格研究所癌症基因组计划（CGP）的全基因组筛选的全部结果。世界上大多数关于人类癌症点突变的文献现已被整理到COSMIC中，并且在不断更新，对整理融合基因突变的更加强调推动了这一信息的扩展；现在已经描述了超过2700个融合基因突变。全基因组测序筛选现在正在识别癌症中的大量基因组重排，COSMIC现在也在展示这些分析的详细信息。对COSMIC数据的查看主要是通过网络进行的，重点是根据基因和/或癌症表型的选择提供突变范围和频率统计。图形视图提供了大量数据的易于理解的总结，导出功能可以提供用户所选数据的精确细节。
The catalogue of Somatic Mutations in Cancer (COSMIC) (http://www.sanger.ac.uk/cosmic/) is the largest public resource for information on somatically acquired mutations in human cancer and is available freely without restrictions. Currently (v43, August 2009), COSMIC contains details of 1.5-million experiments performed through 13 423 genes in almost 370 000 tumours, describing over 90 000 individual mutations. Data are gathered from two sources, publications in the scientific literature, (v43 contains 7797 curated articles) and the full output of the genome-wide screens from the Cancer Genome Project (CGP) at the Sanger Institute, UK. Most of the world's literature on point mutations in human cancer has now been curated into COSMIC and while this is continually updated, a greater emphasis on curating fusion gene mutations is driving the expansion of this information; over 2700 fusion gene mutations are now described. Whole-genome sequencing screens are now identifying large numbers of genomic rearrangements in cancer and COSMIC is now displaying details of these analyses also. Examination of COSMIC's data is primarily web-driven, focused on providing mutation range and frequency statistics based upon a choice of gene and/or cancer phenotype. Graphical views provide easily interpretable summaries of large quantities of data, and export functions can provide precise details of user-selected data.