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The Identification and Analysis of mRNA–lncRNA–miRNA Cliques From the Integrative Network of Ovarian Cancer

机译:卵巢癌综合网络中mRNA-lncRNA-miRNA的鉴定与分析

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摘要

Ovarian cancer is one of the leading causes of cancer mortality in women. Since little clinical symptoms were shown in the early period of ovarian cancer, most patients were found in phases III–IV or with abdominal metastasis when diagnosed. The lack of effective early diagnosis biomarkers makes ovarian cancer difficult to screen. However, in essence, the fundamental problem is we know very little about the regulatory mechanisms during tumorigenesis of ovarian cancer. There are emerging regulatory factors, such as long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), which have played important roles in cancers. Therefore, we analyzed the RNA-seq profiles of 407 ovarian cancer patients. An integrative network of 20,424 coding RNAs (mRNAs), 10,412 lncRNAs, and 742 miRNAs were construed with variance inflation factor (VIF) regression method. The mRNA–lncRNA–miRNA cliques were identified from the network and analyzed. Such promising cliques showed significant correlations with survival and stage of ovarian cancer and characterized the complex sponge regulatory mechanism, suggesting their contributions to tumorigenicity. Our results provided novel insights of the regulatory mechanisms among mRNAs, lncRNAs, and miRNAs and highlighted several promising regulators for ovarian cancer detection and treatment.
机译:卵巢癌是女性癌症死亡的主要原因之一。由于在卵巢癌的早期阶段几乎没有临床症状显示,因此大多数患者被诊断为III–IV期或腹部转移。缺乏有效的早期诊断生物标志物使卵巢癌难以筛查。但是,从本质上讲,根本问题是我们对卵巢癌的发生过程中的调控机制了解甚少。新兴的调节因素,例如长非编码RNA(lncRNA)和microRNA(miRNA),在癌症中发挥了重要作用。因此,我们分析了407例卵巢癌患者的RNA-seq图谱。使用方差膨胀因子(VIF)回归方法构建了一个包含20424个编码RNA(mRNA),10412个lncRNA和742个miRNA的整合网络。从网络中识别并分析了mRNA–lncRNA–miRNA群体。这样有希望的集团显示出与卵巢癌的存活和分期显着相关,并表征了复杂的海绵调节机制,表明它们对致瘤性的贡献。我们的研究结果提供了关于mRNA,lncRNA和miRNA之间调节机制的新颖见解,并着重介绍了几种有前途的卵巢癌检测和治疗调节剂。

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