Hub Genes and Key Pathway Identification in Colorectal Cancer Based on Bioinformatic Analysis.

Jian Lv,Lili Li

doi:10.1155/2019/1545680

Abstract

Colorectal cancer (CRC) is one of the most common malignant tumors. The aim of the present study was to identify key genes and pathways to improve the understanding of the mechanism of CRC. GSE87211, including 203 CRC samples and 160 control samples, was screened to identify differentially expressed genes (DEGs). In total, 853 DEGs were obtained, including 363 upregulated genes and 490 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs were performed to obtain enrichment datasets. GO analysis showed that DEGs were significantly enriched in the extracellular region, cell-cell signaling, hormone activity, and cytokine activity. KEGG pathway analysis revealed that the DEGs were mainly enriched in the cytokine-cytokine receptor interaction, drug metabolism, androgen and estrogen metabolism, and neuroactive ligand-receptor interaction. The Protein-Protein Interaction (PPI) network of DEGs was constructed by using Search Tool for the Retrieval of Interacting Genes (STRING). The app MCODE plugged in Cytoscape was used to explore the key modules involved in disease development. 43 key genes involved in the top two modules were identified. Six hub genes (CXCL2, CXCL3, PTGDR2, GRP, CXCL11, and AGTR1) were statistically associated with patient overall survival or disease-free survival. The functions of six hub genes were mainly related to the hormone and chemokine activities. In conclusion, the present study may help understand the molecular mechanisms of CRC development.

Highlights

Colorectal cancer (CRC) is one of the leading causes of malignant tumors [1, 2]. e incidence rate of CRC is high, which seriously affects the patient’s health
It offers an efficient method for systematically screening tumor-related genes and identifying their regulatory mechanisms with bioinformatics [8, 9]. e hub genes are the highly connected nodes in the PPI network, which have high probabilities of engaging in essential biological regulation [10], and have been reported in various types of cancer. e ProteinProtein Interaction (PPI) network and hub genes analysis are used for revealing crucial biological processes [11], which provide efficient approaches for discovering key molecular mechanisms in cancer biology
Selected 10 CRC and 10 control samples were clustered together, respectively, according to the expression level of top 50 significant differentially expressed genes (DEGs) shown in the heatmap (Figure 1(b))

Summary

Introduction

Colorectal cancer (CRC) is one of the leading causes of malignant tumors [1, 2]. e incidence rate of CRC is high, which seriously affects the patient’s health. Erefore, it is necessary to identify molecular hub genes and key pathways for understanding the molecular mechanism and discovering potential biomarkers for CRC. Microarray technology is widely used in molecular mechanism exploration and has a wide range of application in molecular biology. It offers an efficient method for systematically screening tumor-related genes and identifying their regulatory mechanisms with bioinformatics [8, 9]. E ProteinProtein Interaction (PPI) network and hub genes analysis are used for revealing crucial biological processes [11], which provide efficient approaches for discovering key molecular mechanisms in cancer biology. It offers an efficient method for systematically screening tumor-related genes and identifying their regulatory mechanisms with bioinformatics [8, 9]. e hub genes are the highly connected nodes in the PPI network, which have high probabilities of engaging in essential biological regulation [10], and have been reported in various types of cancer. e ProteinProtein Interaction (PPI) network and hub genes analysis are used for revealing crucial biological processes [11], which provide efficient approaches for discovering key molecular mechanisms in cancer biology.

Methods

Results

Conclusion