Epithelial-mesenchymal transition markers screened in a cell-based model and validated in lung adenocarcinoma

Abstract

BACKGROUND: Re-capture of the differences between tumor and normal tissues observed at the patient level in cell cultures and animal models is critical for applications of these cancer-related differences. The epithelial-mesenchymal transition (EMT) process is essential for tumor migratory and invasive capabilities. Although plenty of EMT markers are revealed, molecular features during the early stages of EMT are poorly understood. METHODS: A cell-based model to induce lung cell (A549) EMT using conditioned medium of in vitro cancer activated fibroblast (WI38) was established. High-throughput sequencing methods, including RNA-seq and miRNA-seq, and advanced bioinformatics methods were used to explore the transcriptome profile transitions accompanying the progression of EMT. We validated our findings with experimental techniques including transwell and immunofluorescence assay, as well as the TCGA data. RESULTS: We have constructed an in vitro cell model to mimic the EMT in patients. We discovered that several new transcription factors were among the early genes (3 h) to respond to cancer micro-environmental cues which could play critical roles in triggering further EMT signals. The early EMT markers also included genes encoding membrane transporters and blood coagulation function. Three of the nine-examined early EMT hallmark genes, GALNT6, SPARC and HES7, were up-regulated specifically in the early stages of lung adenocarcinoma (LUAD) and confirmed by TCGA patient transcriptome data. In addition, we showed that miR-3613, a regulator of EGFR pathway genes, was constantly repressed during EMT progress and indicative of an epithelial miRNA marker. CONCLUSIONS: The CAF-stimulated EMT cell model may recapture some of the molecular changes during EMT progression in clinical patients. The identified early EMT hallmark genes GALNT6, SPARC and HES7and miR-3613 provide new markers and therapeutic targets for LUAD for the further clinical diagnosis and drug screening.