Abstract
Esophageal squamous cell carcinoma (ESCC) is one of the most common and deadly causes of cancer worldwide. However, to date, the mechanisms underlying its pathogenesis remain unclear. The present study investigated the gene expression profile of human esophageal cancer cell line TE-1, a cell model for ESCC, to gain insight to the genetic regulation of this disease. Human esophageal cancer TE-1 cells and normal esophageal HET-1A cells were cultured for isolation of total RNA. Differential expression of RNA transcripts was assessed using the Agilent 4×44 K microarray, combined with real-time PCR (qRT-PCR) for validation. Classification and function of the differential genes were illustrated by bioinformatics processing including hierarchical clustering and gene ontology (GO) analysis. We identified 4,986 transcripts with differential expression (fold-change ≥1.5, P<0.05), including 2,368 up-regulated and 2,618 down-regulated transcripts. GO analysis showed that the dysregulated transcripts were associated with biological process, cellular component, and molecular function. After bioinformatic analysis of significantly regulated signaling pathways, we found these transcripts may target 35 gene pathways, including p53 signaling, glioma, ubiquitin-mediated proteolysis, insulin signaling, cell cycle, inositol phosphate metabolism, mTOR signaling, and MAPK signaling. The differentially expressed transcripts were screened between the esophageal cancer cell line TE-1 and normal esophageal cell line HET-1A, as well as their target gene pathways. Further data mining is related to prevention and treatment of esophageal cancer.
Keywords:
Esophageal cancer; cDNA microarray; cell line; differential gene expression.