Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA256194 | ENA |
REPOSITORIES: ENA
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Project description:MTA1, SOX4, EZH2 and TGF-β are all potent inducers of epithelial-mesenchymal transition (EMT) in cancer; however, the signaling relationship among these molecules in EMT is poorly understood. Here, we investigated the function of MTA1 in cancer cells and demonstrated that MTA1 overexpression efficiently activates EMT. This activation resulted in a significant increase in the migratory and invasive properties of three different cancer cell lines through a common mechanism involving SOX4 activation, screened from a gene expression profiling analysis. We showed that both SOX4 and MTA1 are induced by TGF-β and both are indispensable for TGF-β-mediated EMT. Further investigation identified that MTA1 acts upstream of SOX4 in the TGF-β pathway, emphasizing a TGF-β-MTA1-SOX4 signaling axis in EMT induction. The histone methyltransferase EZH2, a component of the polycomb (PcG) repressive complex 2 (PRC2), was identified as a critical responsive gene of the TGF-β-MTA1-SOX4 signaling in three different epithelial cancer cell lines, suggesting that this signaling acts broadly in cancer cells in vitro. The MTA1-SOX4-EZH2 signaling cascade was further verified in TCGA pan-cancer patient samples and in a colon cancer cDNA microarray, and activation of genes in this signaling pathway predicted an unfavorable prognosis in colon cancer patients. Collectively, our data uncover a SOX4-dependent EMT-inducing mechanism underlying MTA1-driven cancer metastasis and suggest a widespread TGF-β-MTA1-SOX4-EZH2 signaling axis that drives EMT in various cancers. We propose that this signaling may be used as a common therapeutic target to control epithelial cancer metastasis. We used microarrays to detect MTA1-regulated genes in cancer cells.
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Project description:RATIONALE: Measuring levels of transforming growth factor-beta (TGF-beta) in the blood of patients with epithelial cancers (head and neck, lung, breast, colorectal, and prostate) may help doctors predict how patients will respond to treatment with radiation therapy.
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