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Constructing Gene Co-expression Networks for Prognosis of Lung Adenocarcinoma

机译:构建基因共表达网络以预后肺腺癌预后

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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:许多对癌症的预后基因的研究侧重于癌细胞和正常细胞基因表达的比较分析。然而,通过对不同条件的患者的比较分析,可以更准确地进行癌症患者的预后。在这项研究中,我们将肺腺癌患者分为两组,一种具有宽型TP53基因,另一种具有TP53基因的体细胞突变,并为两组构建基因共表达网络。根据两组GCNS的比较分析,我们在两组中获得了几种具有显着不同的共表达模式的基因对。在我们的研究中构建的GCNS比其他GCN在这种意义上更为丰富的信息,因为我们的基因之间提供了基因,一致性和预后类型之间的特定类型的相关性。 GCNS将是肺腺癌预后的信息,这是最常见的肺癌类型。

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