The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes.
The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes.
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DOI：
10.1038/ncomms11479
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发表时间：
2016-05-10
影响因子：
16.6
通讯作者：
Caldas C
中科院分区：
文献类型：
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作者：
Pereira B;Chin SF;Rueda OM;Vollan HK;Provenzano E;Bardwell HA;Pugh M;Jones L;Russell R;Sammut SJ;Tsui DW;Liu B;Dawson SJ;Abraham J;Northen H;Peden JF;Mukherjee A;Turashvili G;Green AR;McKinney S;Oloumi A;Shah S;Rosenfeld N;Murphy L;Bentley DR;Ellis IO;Purushotham A;Pinder SE;Børresen-Dale AL;Earl HM;Pharoah PD;Ross MT;Aparicio S;Caldas C
乳腺癌的基因组景观是复杂的，肿瘤间和肿瘤内的异质性是治疗该疾病的重要挑战。在这项研究中，我们对2，433例原发性乳腺肿瘤中的173个基因进行了测序，这些肿瘤具有拷贝数畸变（CNA），基因表达和长期临床随访数据。我们确定了40个突变驱动基因（Mut-driver），并确定了突变、驱动CNA谱、临床病理参数和生存率之间的关联。我们评估了Mut驱动突变的克隆状态，并使用mu等位基因分数估计肿瘤内异质性水平。PIK 3CA突变和生存率降低之间的关联在ER阳性癌症的三个亚组中被鉴定（通过17 q23、11 q13 -14或8 q24的扩增来定义）。高水平的肿瘤内异质性通常与更差的结局相关，但具有11 q13 -14扩增的高度侵袭性肿瘤的肿瘤内异质性水平较低。这些结果强调了乳腺癌基于基因组分层的重要性，并对设计治疗策略具有重要意义。 最近，许多努力致力于了解乳腺癌的基因组学。在这项研究中，作者将体细胞突变数据与先前发表的近2,500个乳腺癌样本的拷贝数畸变和基因表达信息相结合。
The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13–14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13–14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. Much effort has recently been devoted to understanding the genomics of breast cancer. In this study, the authors integrate somatic mutation data with previously published copy number aberration and gene expression information for nearly 2,500 breast cancer samples.