Functional and pathway enrichment analysis for integrated regulatory network of high- and low-metastatic lung cancer

Abstract

Metastasis is a common feature of lung cancer, involving relationships between genes, proteins and miRNAs. However, lack of early detection and limited options for targeted therapies are weaknesses that cantribute to the dismal statistics observed in lung cancer metastasis. In this paper, gene expression profiling analysis for genes differentially expressed between high- (95D) and low-metastatic lung cancer cell lines (95C) was performed using gene annotation, pathway analysis, literature mining, and the integrated regulatory network as well as motif analysis of miRNA–DEG and TF–DEG. In addition, the expression of EGR-1 (early growth reponse-1) in surgically resected lung squamous carcinomas, adenocarcinomas and normal lung tissue was detected by immunohistochemistry to reveal the relationships between EGR-1 and lung cancer metastasis. A total of 570 different expressed genes (DEGs) were screened, the vast majority of up-regulated DEGs were connected to cell adhesion and focal adhesion. EGR-1 was observed in the center node of the regulatory network, which seems to play a role in the process of cancer metastasis, and further immunohistochemistry detection confirmed this reasoning. Besides EGR-1, several significant module-related DEGs were enriched in the pathway within cancer and focal adhesion according to KEGG pathway enrichment analysis of network modules. The construction of an integrated regulatory network and the functional prediction of EGR-1 provided us with the cytological basis of lung cancer metastasis research and an understanding of the mechanism of metastasis in lung cancer. EGR-1 should be considered as a potential target gene in therapeutic agent for lung cancer metastasis.