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癌症基因组测序中的差异凸显了发现驱动突变的机会。

Discrepancies in cancer genomic sequencing highlight opportunities for driver mutation discovery.

作者信息

Hudson Andrew M, Yates Tim, Li Yaoyong, Trotter Eleanor W, Fawdar Shameem, Chapman Phil, Lorigan Paul, Biankin Andrew, Miller Crispin J, Brognard John

机构信息

Signalling Networks in Cancer Group, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, M20 4BX, UK.

RNA Biology Group, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, M20 4BX, UK.

出版信息

Cancer Res. 2014 Nov 15;74(22):6390-6396. doi: 10.1158/0008-5472.CAN-14-1020. Epub 2014 Sep 25.

Abstract

Cancer genome sequencing is being used at an increasing rate to identify actionable driver mutations that can inform therapeutic intervention strategies. A comparison of two of the most prominent cancer genome sequencing databases from different institutes (Cancer Cell Line Encyclopedia and Catalogue of Somatic Mutations in Cancer) revealed marked discrepancies in the detection of missense mutations in identical cell lines (57.38% conformity). The main reason for this discrepancy is inadequate sequencing of GC-rich areas of the exome. We have therefore mapped over 400 regions of consistent inadequate sequencing (cold-spots) in known cancer-causing genes and kinases, in 368 of which neither institute finds mutations. We demonstrate, using a newly identified PAK4 mutation as proof of principle, that specific targeting and sequencing of these GC-rich cold-spot regions can lead to the identification of novel driver mutations in known tumor suppressors and oncogenes. We highlight that cross-referencing between genomic databases is required to comprehensively assess genomic alterations in commonly used cell lines and that there are still significant opportunities to identify novel drivers of tumorigenesis in poorly sequenced areas of the exome. Finally, we assess other reasons for the observed discrepancy, such as variations in dbSNP filtering and the acquisition/loss of mutations, to give explanations as to why there is a discrepancy in pharmacogenomic studies, given recent concerns with poor reproducibility of data.

摘要

癌症基因组测序正越来越多地用于识别可指导治疗干预策略的可操作驱动突变。对来自不同机构的两个最著名的癌症基因组测序数据库(癌症细胞系百科全书和癌症体细胞突变目录)进行比较发现,在相同细胞系中错义突变的检测存在显著差异(一致性为57.38%)。这种差异的主要原因是外显子组富含GC区域的测序不足。因此,我们在已知的致癌基因和激酶中绘制了400多个测序始终不足的区域(冷点),其中368个区域两个机构均未发现突变。我们以新发现的PAK4突变为原理证明,对这些富含GC的冷点区域进行特异性靶向测序可导致在已知的肿瘤抑制基因和癌基因中识别出新的驱动突变。我们强调,需要在基因组数据库之间进行交叉引用,以全面评估常用细胞系中的基因组改变,并且在外显子组测序较差的区域仍有很大机会识别肿瘤发生的新驱动因素。最后,我们评估了观察到的差异的其他原因,例如dbSNP过滤的差异以及突变的获得/丢失,以解释为什么在药物基因组学研究中存在差异,鉴于最近对数据可重复性差的担忧。

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