Challenges in identifying cancer genes by analysis of exome sequencing data

被引:27
|
作者
Hofree, Matan [1 ,2 ,3 ,8 ]
Carter, Hannah [2 ,3 ,4 ]
Kreisberg, Jason F. [1 ,3 ]
Bandyopadhyay, Sourav [5 ]
Mischel, Paul S. [6 ]
Friend, Stephen [7 ]
Ideker, Trey [1 ,2 ,3 ,4 ]
机构
[1] CCMI, 9500 Gilman Dr, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, Dept Comp Sci & Engn, 9500 Gilman Dr, La Jolla, CA 92093 USA
[3] Univ Calif San Diego, Dept Med, 9500 Gilman Dr, La Jolla, CA 92093 USA
[4] Univ Calif San Diego, Moores Canc Ctr, 3855 Hlth Sci Dr, La Jolla, CA 92093 USA
[5] Univ Calif San Francisco, Diller Family Comprehens Canc Ctr, 1600 Divisadero St, San Francisco, CA 94115 USA
[6] Univ Calif San Diego, Ludwig Inst Canc Res, 9500 Gilman Dr, La Jolla, CA 92093 USA
[7] Sage Bionetworks, 110 Fairview Ave North, Seattle, WA 98109 USA
[8] Broad Inst MIT & Harvard, 415 Main St, Cambridge, MA 02142 USA
来源
NATURE COMMUNICATIONS | 2016年 / 7卷
基金
美国国家卫生研究院;
关键词
TERT PROMOTER MUTATIONS; SOMATIC MUTATIONS; OVARIAN-CANCER; TUMOR TYPES; DRIVER GENES; GENOME; MELANOMA; LEUKEMIA; NETWORK; VALIDATION;
D O I
10.1038/ncomms12096
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysis methods to specifically recover known cancer genes. While some cancer genes are identified by analysis of recurrence, spatial clustering or predicted impact of somatic mutations, many remain undetected due to lack of power to discriminate driver mutations from the background mutational load (13-60% recall of cancer genes impacted by somatic single-nucleotide variants, depending on the method). Cancer genes not detected by mutation recurrence also tend to be missed by all types of exome analysis. Nonetheless, these genes are implicated by other experiments such as functional genetic screens and expression profiling. These challenges are only partially addressed by increasing sample size and will likely hold even as greater numbers of tumours are analysed.
引用
收藏
页数:9
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