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Constructing Gene Co-expression Networks for Prognosis of Lung Adenocarcinoma

机译:构建基因表达网络以预后肺腺癌

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Many studies of prognostic genes for cancer have focused on comparative analysis of gene expressions in cancer cells and normal cells. However, prognosis of cancer patients can be done more accurately by comparative analysis of patients with different conditions. In this study we partitioned the patients with lung adenocarcinoma into two groups, one with a wide-type TP53 gene and the other with somatic mutations in the TP53 gene, and constructed gene co-expression networks for the two groups. From the comparative analysis of the two GCNs we obtained several gene pairs with significantly different co-expression patterns in the two groups. The GCNs constructed in our study are more informative than other GCNs in the sense that ours provide the specific type of correlation between genes, the concordance and prognostic type of a gene. The GCNs will be informative for prognosis of lung adenocarcinoma, which is the most common type of lung cancer.
机译:癌症预后基因的许多研究都集中在比较癌细胞和正常细胞中基因表达的比较分析中。但是,通过对不同情况的患者进行比较分析,可以更准确地预测癌症患者的预后。在这项研究中,我们将肺腺癌患者分为两组,一组具有宽型TP53基因,另一组具有TP53基因的体细胞突变,并为两组构建了基因共表达网络。通过对两个GCN的比较分析,我们获得了两组中具有明显不同共表达模式的基因对。在我们的研究中构建的GCN比其他GCN更具信息意义,因为我们提供了基因之间特定的相关类型,基因的一致性和预后类型。 GCNs将为肺腺癌的预后提供信息,肺腺癌是最常见的肺癌类型。

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