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用于癌症突变发现与解读的个性化基因组分析。

Personalized genomic analyses for cancer mutation discovery and interpretation.

作者信息

Jones Siân, Anagnostou Valsamo, Lytle Karli, Parpart-Li Sonya, Nesselbush Monica, Riley David R, Shukla Manish, Chesnick Bryan, Kadan Maura, Papp Eniko, Galens Kevin G, Murphy Derek, Zhang Theresa, Kann Lisa, Sausen Mark, Angiuoli Samuel V, Diaz Luis A, Velculescu Victor E

机构信息

Personal Genome Diagnostics, Baltimore, MD 21224, USA.

The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.

出版信息

Sci Transl Med. 2015 Apr 15;7(283):283ra53. doi: 10.1126/scitranslmed.aaa7161.

Abstract

Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients.

摘要

大规模平行测序方法已开始在临床中用于表征个体患者的肿瘤,并根据所识别的突变选择治疗方案。这些分析中的一个主要问题是,这些方法在多大程度上能识别出具有临床可操作性的改变,以及仅检查肿瘤组织是否足够,还是也应分析匹配的正常DNA以准确识别肿瘤特异性(体细胞)改变。为了解决这些问题,我们全面评估了来自15种肿瘤类型患者的815对肿瘤-正常配对样本。我们使用全外显子组或111个靶向基因的下一代测序来识别基因组改变,其敏感性分别>95%和>99%,特异性>99.99%,并得到了验证。这些分析显示,每个外显子组和靶向分析平均分别有140个和4.3个体细胞突变。超过75%的病例在与已知治疗方法或当前临床试验相关的基因中存在体细胞改变。对匹配的正常DNA的分析在3%表面上为散发性癌症的患者中识别出了癌症易感基因中的种系改变。相比之下,仅肿瘤测序方法无法明确识别癌症易感基因中的种系变化,并导致了额外的假阳性结果,分别占靶向分析和外显子组分析中所识别改变的31%和65%,包括在潜在可操作基因中。这些数据表明,匹配的肿瘤-正常测序分析对于精确识别和解释体细胞及种系改变至关重要,对癌症患者的诊断和治疗管理具有重要意义。

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