A network-based approach to identify hub genes and key pathways in esophageal squamous cell carcinoma
-
Mobina Madihi,1 Mehrdad Ameri,2,*
1. Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran / Research Center for Clinical Virology, Tehran University of Medical Sciences, Tehran, Iran
2. Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Introduction: Esophageal cancer is the sixth leading cause of cancer death worldwide (1). The most common type of esophageal cancer is esophageal squamous cell carcinoma (ESCC), with high mortality (2). Screening this cancer using biomarkers in endemic areas with high-risk populations can reduce the mortality from this disease worldwide.
Gene expression profiling using microarray technology and the combination of resultant data with in silico approaches can provide valuable information about differentially expressed genes in cancer and normal cells (3, 4). Since several databases collect and maintain microarray data, we can analyze the gene expression profile of different cancer for different goals. This study was designed to discover hub genes and pathways which are enriched with differentially expressed genes in esophageal squamous cell carcinoma.
- Methods: A gene expression profile of esophageal squamous cell carcinoma (GSE75241) was obtained from gene expression omnibus (GEO) available at https://www.ncbi.nlm.nih.gov/geo. There are 15 tumor samples and 15 nonmalignant samples in the selected dataset. GEO2R was used to identify differentially expressed genes (DEGs) between tumor and normal samples. Genes with p-value < 0.05 and log fold change (logFC) > 1 and -1 < were considered as final DEGs. Up-regulated genes were used for further analysis. Enrichr (https://maayanlab.cloud/Enrichr) was exploited for enrichment analysis. Therefore, using Enrichr gene ontology (GO) term and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were conducted. Moreover, STRING (https://string-db.org/) was used for protein-protein interaction (PPI) network reconstruction and Cytoscape 3.9.0 was employed to visualize and analyze PPI-network. Using the CytoHubba plugin and degree centrality top 10 hub genes were selected. Ultimately, hub gene validation was performed using UALCAN available at http://ualcan.path.uab.edu/index.html.
- Results: Based on the selected criteria, 868 genes were up-regulated and 628 genes were down-regulated. Considering GO biological process, up-regulated DEGs are associated with “extracellular matrix organization”, “extracellular structure organization”, and “external encapsulating structure organization”. GO Molecular function revealed the relationship of up-regulated DEGs with “single-stranded DNA helicase activity”, “chemokine activity”, and “protease binding”. GO cellular components showed that up-regulated DEGs are related to “collagen-containing extracellular matrix”, “endoplasmic reticulum lumen”, and “focal adhesion”. KEGG pathway enrichment analysis showed the relationship of up-regulated DEGs with “ECM-receptor interaction”, “Focal adhesion”, and “AGE-RAGE signaling pathway in diabetic complications”.
PPI-network was reconstructed using STRING. The reconstructed network of up-regulated DEGs consisted of 823 nodes and 11269 edges. Based on degree, FN1, IL6, IL1B, CCNB1, PTPRC, CDK1, MMP9, BRCA1, TLR4, and MKI67 were considered as hub genes. UALCAN showed that among selected hub genes, only two genes (IL6 and IL1B) have a reverse relationship with the survival of esophageal carcinoma patients.
- Conclusion: Using an integrated network-based approach with microarray data our results revealed top pathways and biological components related to DEGs in esophageal squamous cell carcinoma. Moreover, we suggest two validated hub genes (IL6 and IL1B) as potential biomarkers in esophageal squamous cell carcinoma.
- Keywords: Esophageal cancer- esophageal squamous cell carcinoma (ESCC) -microarray
