Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Proc Natl Acad Sci U S A. 2010 Oct 12;107(41):17604-9. doi: 10.1073/pnas.1009117107. Epub 2010 Sep 23.
Human cancer is caused by the accumulation of genetic alterations in cells. Of special importance are changes that occur early during malignant transformation because they may result in oncogene addiction and represent promising targets for therapeutic intervention. Here we describe a computational approach, called Retracing the Evolutionary Steps in Cancer (RESIC), to deduce the temporal sequence of genetic events during tumorigenesis from cross-sectional genomic data of tumors at their fully transformed stage. When applied to a dataset of 70 advanced colorectal cancers, our algorithm accurately predicts the sequence of APC, KRAS, and TP53 mutations previously defined by analyzing tumors at different stages of colon cancer formation. We further validate the method with glioblastoma and leukemia sample data and then apply it to complex integrated genomics databases, finding that high-level EGFR amplification appears to be a late event in primary glioblastomas. RESIC represents the first evolutionary mathematical approach to identify the temporal sequence of mutations driving tumorigenesis and may be useful to guide the validation of candidate genes emerging from cancer genome surveys.
人类癌症是由细胞中遗传改变的积累引起的。特别重要的是，在恶性转化早期发生的变化，因为它们可能导致癌基因成瘾，并代表治疗干预的有前途的靶点。在这里，我们描述了一种计算方法，称为回溯癌症中的进化步骤（RESIC），该方法从完全转化阶段的肿瘤的横截面基因组数据中推断肿瘤发生过程中的遗传事件的时间顺序。当应用于 70 例高级结直肠癌的数据集时，我们的算法准确预测了先前通过分析结肠癌形成的不同阶段的肿瘤所定义的 APC、KRAS 和 TP53 突变的顺序。我们还使用神经胶质瘤和白血病样本数据进一步验证了该方法，然后将其应用于复杂的综合基因组学数据库，发现高水平的 EGFR 扩增似乎是原发性神经胶质瘤中的晚期事件。RESIC 代表了识别驱动肿瘤发生的突变的时间顺序的第一个进化数学方法，它可能有助于指导从癌症基因组调查中出现的候选基因的验证。
