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目的:通过整合分析基因的表达与拷贝数变异(CNV)识别癌症的驱动基因及调控子mi RNAs。方法:通过整合基因表达与CNV数据,分别计算了乳腺癌、结肠癌、肺癌、肾癌、膀胱癌、头颈癌六种癌症中mi RNAs的调控得分,提出了一个识别驱动基因和显著调控子mi RNAs的方法。结果:本文研究发现,CNV区域上编码的基因相比于非CNV区域上编码的基因更倾向于受mi RNAs调控。但是,癌相关CNV区域上的基因相比正常CNV区域上的基因更少受mi RNAs调控。本研究识别出了EXOSC4、ZNF7、BOP1等原癌基因,以及mi R-488、mi R-27a、mi R-454等在多种癌症中都起调控作用的调控子mi RNAs。结论:本文的方法为癌症研究带来了新的启发,这些具有调控扩增基因过表达作用的mi RNAs的发现,有助于我们更进一步了解癌基因表达的复杂调控机制,进而推动癌症的诊断、治疗和预后。
OBJECTIVE: To identify the cancer-driven genes and miRNAs by integrating the gene expression and copy number variation (CNV). Methods: By integrating gene expression with CNV data, we calculated the regulatory score of mi RNAs in six types of breast cancer, colon cancer, lung cancer, kidney cancer, bladder cancer and head and neck cancer respectively. RNAs method. Results: In this study, it was found that genes encoded on the CNV region are more likely to be regulated by miRNAs than genes encoded on non-CNV regions. However, genes on cancer-associated CNV regions are less regulated by miRNAs than genes on normal CNV regions. This study identified proto-oncogenes such as EXOSC4, ZNF7 and BOP1 as well as regulatory miRNAs that play a regulatory role in various cancers such as mi R-488, mi R-27a and mi R-454. CONCLUSIONS: The method of this article brings new insights into cancer research. The discovery of mi RNAs that regulate the overexpression of the amplified genes will help us understand more about the complex regulatory mechanisms of oncogene expression and thus promote the diagnosis of cancer , Treatment and prognosis.