2014-REVIEW-identifying driver mutation in sequenced cancer genome

somatic  mutations 含义很广,包括:SNVs,Indel,CNAs,SVs等
However, the resulting sequencing datasets are large and complex, obscuring the clinically important mutations in a background of errors, noise, and random mutations.
Cancer is driven largely by somatic mutations that accumulate in the genome over an individual’s lifetime, with additional contributions from epigenetic and transcriptomic alterations
低通量时代研究,成功例子: imatinib has been used to target cells expressing the BCR-ABL fusion gene  in chronic myeloid leukemia
gefitinib has been used to inhibit the epidermal growth factor receptor in lung cancer
NGS的三大挑战:1,indentying somatic mutations,误差/ 肿瘤异质性 2,识别driver genes 3,确定由somatic mutations 改变的pathways和其它生物过程
误差来源:optical PCR duplicates, GC-bias, strand bias (where reads indicating a possible mutation only align to one strand of DNA) and alignment artifacts resulting from low complexity or repetitive regions in the genome.
most methods for somatic mutation detection address only a subset of the possible sources of error,call snp的软件众多
identifying driver mutations的三个要点:
1,identifying recurrent mutations;
2,predicting the functional impact of individual mutations;
3,assessing combinations of mutations using pathways, interaction networks, or statistical correlations.
1,直接看突变频率的那些软件to determine whether the observed number of mutations in the gene is significantly greater than the number expected according to a background mutation rate (BMR).
BMR 实在是太难确定了,低了会导致很多假阳性,而高了,又错过很多真实的driver mutations,但是突变频率非常高的那些基因肯定是没有问题的,比如说TP53,无论什么样的算法都会认为它是driver gene
evolutionary conservation,
known protein domains,
non-random clustering of mutations,
protein structure,
3,pathways, interaction networks, and de novo approaches的那些软件:
pathway(KEGG,GO,GSEA) 4个limitations,首先,大多数 annotated gene sets 包含的基因数太多,而我们的突变基因占该gene set的比例远达不到统计显著性。
最后,只关注已知的 pathways, or gene set
首先,我们忽略了non-coding somatic mutations
其次,很多我们定义的癌症种类其实是a mixture of these subtypes
最后,不同的NGS数据如何综合研究,包括WGS,WES,RNA sequencing, DNA methylation, and chromatin modifications

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