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Evaluating Translocation Gene Fusions by SNP Array Data

机译:通过SNP阵列数据评估易位基因融合体

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Somatic cell genetic alterations are a hallmark of tumor development and progression. Although various technologies have been developed and utilized to identify genetic aberrations, identifying genetic translocations at the chromosomal level is still a challenging task. High density SNP microarrays are useful to measure DNA copy number variation (CNV) across the genome. Utilizing SNP array data of cancer cell lines and patient samples, we evaluated the CNV and copy number breakpoints for several known fusion genes implicated in tumorigenesis. This analysis demonstrated the potential utility of SNP array data for the prediction of genetic aberrations via translocations based on identifying copy number breakpoints within the target genes. Genome-wide analysis was also performed to identify genes harboring copy number breakpoints across 820 cancer cell lines. Candidate oncogenes were identified that are linked to potential translocations in specific cancer cell lines.
机译:体细胞遗传改变是肿瘤发展和进展的标志。尽管已开发出各种技术来识别遗传畸变,但在染色体水平上鉴定遗传易位仍然是一项艰巨的任务。高密度SNP微阵列可用于测量整个基因组中的DNA拷贝数变异(CNV)。利用癌细胞系和患者样品的SNP阵列数据,我们评估了与肿瘤发生有关的几种已知融合基因的CNV和拷贝数断点。这项分析证明了SNP阵列数据在识别目标基因内的拷贝数断点的基础上,可通过易位预测遗传异常的潜在效用。还进行了全基因组分析,以鉴定具有820个癌细胞系拷贝数断点的基因。确定了与特定癌细胞系中潜在易位相关的候选致癌基因。

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