Original Article
Identification of the key transcription factors in esophageal squamous cell carcinoma
Abstract
Background: Esophageal cancer (EC) is a common human malignancy worldwide. Esophageal squamous cell carcinoma (ESCC) is the predominant subtype in China. The tumorigenesis mechanism in ESCC is unclear. The aim of this study was to identify key transcription factors (TFs) in ESCC and elucidate the mechanism of it.
Methods: A total of ten published microarray datasets of ESCC was downloaded from the Gene Expression Omnibus (GEO). Then, bioinformatics analyses including differentially expressed genes (DEGs) analysis, gene ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, TFs-genes regulatory network construction was performed. Quantitative real-time polymerase chain reactions (qRT-PCR) were used to detect the expression levels of TFs and DEGs in ESCC. The association between stage and TFs and the association between survival and TFs were evaluated based on The Cancer Genome Atlas (TCGA), respectively.
Results: A total of 1,248 dysregulated genes were selected as DEGs in ESCC. A total of 26 TFs and corresponding target-genes were identified. The ESCC-specific transcriptional regulatory network was constructed. The network was consisted of 882 edges and 631 nodes. BRCA1, SOX10, ARID3A, ZNF354C and NFIC had the highest connectivity with DEGs, and regulated 92, 89, 82, 79 and 78 DEGs in the network, respectively. All these 1,248 DEGs were significantly enriched in cell cycle, DNA replication and oocyte meiosis pathways. The qRT-PCR results were consistent with our microarray analysis. High expression of SREBF1 and TFAP2A were significantly correlated with the longer overall survival time of patients with ESCC.
Conclusions: BRCA1, SOX10, ARID3A, ZNF354C and NFIC might be the key TFs in carcinogenesis and development of ESCC by regulating their corresponding target-genes involved in cell cycle, DNA replication and oocyte meiosis pathways. SREBF1 and TFAP2A may be two potential prognostic biomarkers of ESCC.
Methods: A total of ten published microarray datasets of ESCC was downloaded from the Gene Expression Omnibus (GEO). Then, bioinformatics analyses including differentially expressed genes (DEGs) analysis, gene ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, TFs-genes regulatory network construction was performed. Quantitative real-time polymerase chain reactions (qRT-PCR) were used to detect the expression levels of TFs and DEGs in ESCC. The association between stage and TFs and the association between survival and TFs were evaluated based on The Cancer Genome Atlas (TCGA), respectively.
Results: A total of 1,248 dysregulated genes were selected as DEGs in ESCC. A total of 26 TFs and corresponding target-genes were identified. The ESCC-specific transcriptional regulatory network was constructed. The network was consisted of 882 edges and 631 nodes. BRCA1, SOX10, ARID3A, ZNF354C and NFIC had the highest connectivity with DEGs, and regulated 92, 89, 82, 79 and 78 DEGs in the network, respectively. All these 1,248 DEGs were significantly enriched in cell cycle, DNA replication and oocyte meiosis pathways. The qRT-PCR results were consistent with our microarray analysis. High expression of SREBF1 and TFAP2A were significantly correlated with the longer overall survival time of patients with ESCC.
Conclusions: BRCA1, SOX10, ARID3A, ZNF354C and NFIC might be the key TFs in carcinogenesis and development of ESCC by regulating their corresponding target-genes involved in cell cycle, DNA replication and oocyte meiosis pathways. SREBF1 and TFAP2A may be two potential prognostic biomarkers of ESCC.
