Division of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
PLoS Comput Biol. 2010 Jan;6(1):e1000631. doi: 10.1371/journal.pcbi.1000631. Epub 2010 Jan 1.
Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes.
肿瘤发生是一个多步骤的过程，正常细胞在积累能够使其逃避正常抑制其生长或导致细胞凋亡的生长控制检查点的基因突变后，转变为恶性肿瘤。因此，确定哪些突变组合协同促进癌症的发生和发展是非常重要的。DNA 拷贝数改变（CNAs）是肿瘤细胞中癌症基因失调控的一种方式。我们假设通过寻找共同发生的增益和/或缺失区域，可以识别癌症基因之间的协同相互作用。为此，我们开发了一种评分框架，将真正共同发生的异常与数据中存在的乘客突变和显性单信号区分开来。高共同发生的区域可以用于研究区域间的功能相互作用。对来自 95 个血液系统肿瘤细胞系的高分辨率 DNA 拷贝数数据的分析正确地鉴定了 T 细胞和 B 细胞恶性肿瘤中 T 细胞受体和免疫球蛋白基因座的共同发生的重组，表明我们可以恢复真正共同发生的基因组改变。此外，我们的分析揭示了共同发生的基因组缺失和增益网络，这些网络富含癌症基因。这些网络也高度富集基因之间的功能关系。我们进一步检查这些网络的子网络，即核心网络，其中包含许多已知的癌症基因。我们发现的共同发生的 DNA 缺失核心网络似乎独立于网络中的经典癌症基因。我们的研究结果表明，大规模、低强度的拷贝数改变可能是通过影响功能相关基因的大互连通网络的基因剂量来影响癌症发展或维持的一个重要特征。
