Emily Mathieu, François Olivier
TIMC-TIMB Department, Faculty of Medicine, Institut de l'Ingénierie de l'Information de Santé, 38706 La Tronche, France.
Genetics. 2006 Mar;172(3):1809-20. doi: 10.1534/genetics.105.044099. Epub 2005 Dec 30.
Humans have invested several genes in DNA repair and fidelity replication. To account for the disparity between the rarity of mutations in normal cells and the large number of mutations present in cancer, an hypothesis is that cancer cells must exhibit a mutator phenotype (genomic instability) during tumor progression, with the initiation of abnormal mutation rates caused by the loss of mismatch repair. In this study we introduce a stochastic model of mutation in tumor cells with the aim of estimating the amount of genomic instability due to the alteration of DNA repair genes. Our approach took into account the difficulties generated by sampling within tumoral clones and the fact that these clones must be difficult to isolate. We provide corrections to two classical statistics to obtain unbiased estimators of the raised mutation rate, and we show that large statistical errors may be associated with such estimators. The power of these new statistics to reject genomic instability is assessed and proved to increase with the intensity of mutation rates. In addition, we show that genomic instability cannot be detected unless the raised mutation rates exceed the normal rates by a factor of at least 1000.
人类在DNA修复和保真复制方面投入了多个基因。为了解释正常细胞中突变的罕见性与癌症中存在的大量突变之间的差异，有一种假说认为，癌细胞在肿瘤进展过程中必须表现出突变表型（基因组不稳定），错配修复功能丧失会引发异常突变率。在本研究中，我们引入了一种肿瘤细胞突变的随机模型，旨在估计由于DNA修复基因改变导致的基因组不稳定程度。我们的方法考虑到了肿瘤克隆内抽样产生的困难以及这些克隆难以分离的事实。我们对两种经典统计方法进行了修正，以获得突变率升高的无偏估计量，并且我们表明此类估计量可能存在较大的统计误差。评估了这些新统计方法拒绝基因组不稳定的能力，并证明其会随着突变率强度的增加而增强。此外，我们表明，除非升高的突变率比正常率至少高1000倍，否则无法检测到基因组不稳定。
