Assié Guillaume, LaFramboise Thomas, Platzer Petra, Bertherat Jérôme, Stratakis Constantine A, Eng Charis
Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA.
Am J Hum Genet. 2008 Apr;82(4):903-15. doi: 10.1016/j.ajhg.2008.01.012. Epub 2008 Mar 20.
SNP arrays provide reliable genotypes and can detect chromosomal aberrations at a high resolution. However, tissue heterogeneity is currently a major limitation for somatic tissue analysis. We have developed SOMATICs, an original program for accurate analysis of heterogeneous tissue samples. Fifty-four samples (42 tumors and 12 normal tissues) were processed through Illumina Beadarrays and then analyzed with SOMATICs. We demonstrate that tissue heterogeneity-related limitations not only can be overcome but can also be turned into an advantage. First, admixture of normal cells with tumor can be used as an internal reference, thereby enabling highly sensitive detection of somatic deletions without having corresponding normal tissue. Second, the presence of normal cells allows for discrimination of somatic from germline aberrations, and the proportion of cells in the tissue sample that are harboring the somatic events can be assessed. Third, relatively early versus late somatic events can also be distinguished, assuming that late events occur only in subsets of cancer cells. Finally, admixture by normal cells allows inference of germline genotypes from a cancer sample. All this information can be obtained from any cancer sample containing a proportion of 40-75% of cancer cells. SOMATICs is a ready-to-use open-source program that integrates all of these features into a simple format, comprehensively describing each chromosomal event.
单核苷酸多态性(SNP)阵列可提供可靠的基因型,并能以高分辨率检测染色体畸变。然而,组织异质性目前是体细胞组织分析的一个主要限制因素。我们开发了SOMATICs,这是一个用于准确分析异质组织样本的原创程序。54个样本(42个肿瘤样本和12个正常组织样本)通过Illumina Beadarrays进行处理,然后用SOMATICs进行分析。我们证明,与组织异质性相关的限制不仅可以被克服,而且还可以转化为优势。首先,正常细胞与肿瘤细胞的混合可以用作内部对照,从而在没有相应正常组织的情况下实现对体细胞缺失的高度敏感检测。其次,正常细胞的存在有助于区分体细胞畸变和种系畸变,并且可以评估组织样本中携带体细胞事件的细胞比例。第三,假设晚期事件仅发生在癌细胞亚群中,也可以区分相对早期和晚期的体细胞事件。最后,正常细胞的混合使得能够从癌症样本中推断种系基因型。所有这些信息都可以从任何含有40%-75%癌细胞比例的癌症样本中获得。SOMATICs是一个即用型开源程序,它将所有这些功能集成到一个简单的格式中,全面描述每个染色体事件。