摘要
目的挖掘乳腺癌各亚型关键调控子并评估其预后能力。方法整合TCGA数据库中乳腺癌样本基因表达、拷贝数变异和DNA甲基化数据,分亚型筛选癌症相关基因。以此为基础,挖掘各亚型的四类motif,将同亚型四类motif合并构建各亚型miRNA-TF调控网络。随后,挖掘每个网络hub节点,并对其预后能力进行评估。结果各调控网络中的10个hub miRNA分别为乳腺癌亚型关键调控子。结论基于miRNA-TF调控网络能有效识别出乳腺癌亚型预后相关生物标志物。
Objective To identificate the key regulator in breast cancer subtypes and evaluate their prognosis. Methods The cancer-related genes of each subtype were identified through the integration of gene expression, copy number variation and DNA methylation data of TCGA breast cancer samples. Then, four types of motifs were obtained based on the genes. The miRNA-TF mediated regulatory network for each subtype was constructed by merging these motifs. Furthermore, hub nodes were identified for each network, and survival analysis was carry out. Results Regulatory network analysis showed that 10 hub miRNA of each subtype were key regulators in breast cancer subtypes. Conclusion Based on the miRNA-TF regulatory net- works can identify the prognostic markers for breast cancer subtypes.
出处
《哈尔滨医科大学学报》
CAS
2017年第1期21-24,共4页
Journal of Harbin Medical University
基金
国家自然科学基金资助项目(81372492)
