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Identification of Networks of Co-Occurring Tumor-Related DNA Copy Number Changes Using a Genome-Wide Scoring Approach

机译:使用全基因组评分方法鉴定与肿瘤相关的同时发生的DNA拷贝数变化的网络

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摘要

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.
机译:肿瘤发生是一个多步骤的过程,在此过程中,正常细胞会随着基因突变的积累而转变成恶性肿瘤,从而使其能够逃避正常情况下会抑制其生长或导致凋亡的生长控制检查点。因此,重要的是确定在癌症发展和进程中协同作用的突变组合。 DNA拷贝数改变(CNA)是使肿瘤细胞中的肿瘤基因失控的一种方式。我们假设癌症基因之间的协同相互作用可以通过寻找共同发生的收益和/或损失区域来确定。为此,我们开发了一个评分框架,以将真正的同现像差与乘客突变和数据中存在的主要单个信号分开。可以针对区域之间的功能相互作用研究高共现的结果区域。分析来自95个血液肿瘤细胞系的高分辨率DNA拷贝数数据,分别正确鉴定了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现重组,表明我们可以真正康复共同发生的基因组改变。此外,我们的分析揭示了共同存在的基因组损失和收获网络,这些网络丰富了癌症基因。这些网络还高度丰富了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,同时发生DNA丢失的核心网络似乎独立于网络中的规范癌症基因。我们的发现表明,大规模,低强度的拷贝数改变可能通过影响功能相关基因的大型互连网络的基因剂量而成为癌症发展或维持的重要特征。

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