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Updated: Mar 8, 2026

Studying TGF-β Signaling and TGF-β-induced Epithelial-to-mesenchymal Transition in Breast Cancer and Normal Cells
Published on: October 27, 2020
A Transcriptional Program for Detecting TGFβ-Induced EMT in Cancer
Momeneh Foroutan1,2, Joseph Cursons2,3,4, Soroor Hediyeh-Zadeh2
1The University of Melbourne Department of Surgery, St. Vincent's Hospital, Parkville, Victoria, Australia.
Abstract:
Most cancer deaths are due to metastasis, and epithelial-to-mesenchymal transition (EMT) plays a central role in driving cancer cell metastasis. EMT is induced by different stimuli, leading to different signaling patterns and therapeutic responses. TGFβ is one of the best-studied drivers of EMT, and many drugs are available to target this signaling pathway. A comprehensive bioinformatics approach was employed to derive a signature for TGFβ-induced EMT which can be used to score TGFβ-driven EMT in cells and clinical specimens. Considering this signature in pan-cancer cell and tumor datasets, a number of cell lines (including basal B breast cancer and cancers of the central nervous system) show evidence for TGFβ-driven EMT and carry a low mutational burden across the TGFβ signaling pathway. Furthermore, significant variation is observed in the response of high scoring cell lines to some common cancer drugs. Finally, this signature was applied to pan-cancer data from The Cancer Genome Atlas to identify tumor types with evidence of TGFβ-induced EMT. Tumor types with high scores showed significantly lower survival rates than those with low scores and also carry a lower mutational burden in the TGFβ pathway. The current transcriptomic signature demonstrates reproducible results across independent cell line and cancer datasets and identifies samples with strong mesenchymal phenotypes likely to be driven by TGFβ.Implications: The TGFβ-induced EMT signature may be useful to identify patients with mesenchymal-like tumors who could benefit from targeted therapeutics to inhibit promesenchymal TGFβ signaling and disrupt the metastatic cascade. Mol Cancer Res; 15(5); 619-31. ©2017 AACR.
Insights
A new bioinformatics signature identifies TGFβ-driven epithelial-to-mesenchymal transition (EMT) in cancers. This signature helps predict patient survival and potential drug responses in metastatic cancers.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Epithelial-to-mesenchymal transition (EMT) is crucial for cancer metastasis.
- Transforming growth factor beta (TGFβ) is a key inducer of EMT, with targeted therapies available.
- Understanding TGFβ-driven EMT is vital for predicting cancer progression and therapeutic outcomes.
Purpose of the Study:
- To develop a comprehensive bioinformatics signature for TGFβ-induced EMT.
- To assess the prevalence and clinical relevance of TGFβ-driven EMT across various cancer types.
- To explore the relationship between TGFβ-driven EMT, mutational burden, and patient survival.
Main Methods:
- Utilized a comprehensive bioinformatics approach to derive a TGFβ-induced EMT signature.
- Applied the signature to pan-cancer cell line and The Cancer Genome Atlas (TCGA) tumor datasets.
- Analyzed mutational burden and drug response in relation to TGFβ-driven EMT scores.
Main Results:
- Identified specific cell lines and tumor types exhibiting TGFβ-driven EMT, often with low TGFβ pathway mutational burden.
- Observed significant variations in drug responses among cell lines with high TGFβ-driven EMT scores.
- High TGFβ-driven EMT scores correlated with significantly lower patient survival rates and lower TGFβ pathway mutational burden.
Conclusions:
- The developed transcriptomic signature reliably identifies TGFβ-driven EMT across independent datasets.
- This signature can pinpoint mesenchymal-like tumors driven by TGFβ signaling.
- The findings suggest potential for targeted therapies inhibiting TGFβ signaling to improve outcomes for patients with high-scoring tumors.
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