Department of Genetics, Institute for Cancer Research, Clinic for Cancer and Surgery, Oslo University Hospital, Montebello, N-0310 Oslo, Norway.
Proc Natl Acad Sci U S A. 2010 Sep 28;107(39):16910-5. doi: 10.1073/pnas.1009843107. Epub 2010 Sep 13.
We present an allele-specific copy number analysis of the in vivo breast cancer genome. We describe a unique bioinformatics approach, ASCAT (allele-specific copy number analysis of tumors), to accurately dissect the allele-specific copy number of solid tumors, simultaneously estimating and adjusting for both tumor ploidy and nonaberrant cell admixture. This allows calculation of "ASCAT profiles" (genome-wide allele-specific copy-number profiles) from which gains, losses, copy number-neutral events, and loss of heterozygosity (LOH) can accurately be determined. In an early-stage breast carcinoma series, we observe aneuploidy (>2.7n) in 45% of the cases and an average nonaberrant cell admixture of 49%. By aggregation of ASCAT profiles across our series, we obtain genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. In addition, the ASCAT profiles reveal differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between the five previously identified molecular breast cancer subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. Finally, from the ASCAT profiles, we construct a genome-wide map of allelic skewness in breast cancer, indicating loci where one allele is preferentially lost, whereas the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development.
我们提出了一种针对体内乳腺癌基因组的等位基因特异性拷贝数分析。我们描述了一种独特的生物信息学方法,即 ASCAT(肿瘤等位基因特异性拷贝数分析),可准确剖析实体瘤的等位基因特异性拷贝数,同时估计和调整肿瘤倍性和非异常细胞混合。这允许从其中计算“ ASCAT 图谱”(全基因组等位基因特异性拷贝数图谱),从而可以准确确定增益,损耗,拷贝数中性事件和杂合性丢失(LOH)。在早期乳腺癌系列中,我们观察到 45%的病例存在非整倍体(> 2.7n),并且平均存在 49%的非异常细胞混合。通过在我们的系列中聚集 ASCAT 图谱,我们获得了乳腺癌中增益和损耗的基因组频率分布,以及 LOH 和拷贝数中性事件的全基因组视图。此外,ASCAT 图谱揭示了五个先前鉴定的分子乳腺癌亚型之间异常肿瘤细胞分数,倍性,增益,损耗,LOH 和拷贝数中性事件的差异。基底样乳腺癌与其他亚型相比,LOH 的频率明显更高,其 ASCAT 图谱显示在肿瘤发展过程中大片段丢失基因组物质,随后是全基因组复制,导致近三倍体基因组。最后,从 ASCAT 图谱中,我们构建了乳腺癌中等位基因偏斜的全基因组图谱,表明存在一个等位基因优先丢失而另一个等位基因优先获得的基因座。我们假设这些替代等位基因对乳腺癌的发展有不同的影响。
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