Constructing Gene Co-expression Networks for Prognosis of Lung Adenocarcinoma

被引：0
|
作者：
Park, Byungkyu [1 ]
Im, Jinho [1 ]
Han, Kyungsook [1 ]
机构：
[1] Inha Univ, Dept Comp Engn, Incheon, South Korea
来源：
INTELLIGENT COMPUTING THEORIES AND APPLICATION, PT II | 2018年 / 10955卷
基金：
新加坡国家研究基金会;
关键词：
Geneco-expression network; Differential expression analysis; Cancer; Prognostic gene;
D O I：
10.1007/978-3-319-95933-7_92
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：831 / 839
页数：9
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