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Transcriptomics-based screening of molecular signatures associated with patients overall survival and their key regulators in subtypes of breast cancer

机译:基于转录组织的分子鉴定筛查与乳腺癌亚型的患者整体存活及其关键调节剂相关的分子鉴定

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Molecular subtypes of breast cancer are associated with differences in prognosis and strategies of molecular targeted therapies. Gene regulatory mechanisms as one of the reasons might modulate these differences. In the present study, we proposed a comprehensive data analysis and systems biology approach to explore molecular signatures which reduce the chance of patients overall survival and the possible mechanisms of their regulation by transcription factors (TFs) and microRNAs (miRNAs) in the main subtypes of breast tumor consist of Basal like, Her2 enriched, Luminal A and Luminal B breast cancer. In this regards, we used available microarray datasets to assess common differentially expressed genes (DEGs) in breast cancer subtypes. Using Kaplan-Meier curve analysis we identified common DEGs which are associated with decreasing in the overall survival of breast cancer patients. Furthermore, gene regulatory networks (GRNs) were depicted based on TFs and miRNAs with interest target genes. Then GRNs were analyzed and using five algorithms (Control centrality, Betweenness, Degree, Classification, and MCDS) the key regulators were identified for each subtype. In this study, we highlighted mechanisms underlying the regulation of breast cancer molecular signatures by TFs and miRNAs which their alteration reduce the chance of survival rate in each subtype of breast cancer. Our current study in a holistic insight revealed the importance of some genes and their regulators as potential prognostic markers and/or therapeutic targets in breast cancer patients.
机译:乳腺癌的分子亚型与预后和分子靶向治疗策略的差异有关。基因调控机制可能是调节这些差异的原因之一。在本研究中,我们提出了一种全面的数据分析和系统生物学方法,以探索降低患者总体生存率的分子特征,以及转录因子(TFs)和微RNA(miRNA)在乳腺肿瘤主要亚型(基底样、Her2富集、管腔a和管腔B乳腺癌)中调节它们的可能机制。在这方面,我们使用可用的微阵列数据集来评估乳腺癌亚型中的常见差异表达基因(DEG)。利用Kaplan-Meier曲线分析,我们确定了与乳腺癌患者总体生存率下降相关的常见DEG。此外,基因调控网络(GRN)是基于TFs和含有目标基因的miRNA描述的。然后分析GRN,并使用五种算法(控制中心性、中间性、程度、分类和MCDS)确定每个亚型的关键调节器。在这项研究中,我们强调了TFs和miRNA调节乳腺癌分子特征的潜在机制,它们的改变降低了每种乳腺癌亚型的生存率。我们目前的整体研究揭示了一些基因及其调节因子作为乳腺癌患者潜在预后标志物和/或治疗靶点的重要性。

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