Transcription Factors Contribute to Differential Expression in Cellular Pathways in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

被引:0
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作者
Shiyi Liu
Xujun Wang
Wenyi Qin
Georgi Z. Genchev
Hui Lu
机构
[1] Shanghai Jiaotong University,Department of Bioinformatics and Biostatistics
[2] Shanghai Jiaotong University,SJTU
[3] University of Illinois at Chicago,Yale Joint Center for Biostatistics
关键词
LUAD; LUSC; Transcription factor; Gene expression features; Enrichment analysis; RNA-Seq;
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学科分类号
摘要
Lung cancers are broadly classified into small cell lung cancers and non-small cell lung cancers (NSCLC). Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are two common subtypes of NSCLC, and despite the fact that both occur in lung tissues, these two subtypes show a number of different pathological characteristics. To investigate the differences and seek potential therapy targets, we used bioinformatics methods to analyze RNA-Seq data from different aspects. The previous studies and comparative pathway enrichment analysis on publicly available data showed that expressed or inhibited genes are different in two cancer subtypes through important pathways. Some of these genes could not only affect cell function through expression, but also could regulate other genes’ expression by binding to a specific DNA sequence. This kind of genes is called transcription factor (TF) or sequence-specific DNA-binding factor. Transcription factors play important roles in controlling gene expression in carcinoma pathways. Our results revealed transcription factors that may cause differential expression of genes in cellular pathways of LUAD and LUSC, which provide new clues for study and treatment. Once such TF is NFE2l2 which may regulate genes in the Wnt signaling pathway, and the MAPK signaling pathway, thus leading to an increase the cell growth, cell division, and gene transcription. Another TF-XBP1 has high correlation with genes related to cell adhesion molecules and cytokine–cytokine receptor interaction pathways that may further affect the immune system. Moreover, the two TF and high correlated genes also show similar patterns in an independent GEO data set.
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页码:836 / 847
页数:11
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