A transcriptional program for detecting TGFbeta-induced EMT in cancer

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. Transforming growth factor beta (TGFbeta) is one of the best-studied drivers of EMT, and many drugs are available to target this signalling pathway. A comprehensive bioinformatics approach was employed to derive a signature for TGFbeta-induced EMT which can be used to score TGFbeta-driven EMT in cells and clinical specimens. Considering this signature in pan-cancer cell and tumour datasets, a number of cell lines (including Basal B breast cancer and cancers of the central nervous system) show evidence for TGFbeta-driven EMT and carry a low mutational burden across the TGFbeta signalling pathway. Further, 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 tumour types with evidence of TGFbeta-induced EMT. Tumour types with high scores showed significantly lower survival rates compared to those with low scores, and also carry a lower mutational burden in the TGFbeta 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 TGFbeta. Implications: The TGFbeta-induced EMT signature may be useful to identify patients with mesenchymal-like tumours that could benefit from targeted therapeutics to inhibit pro-mesenchymal TGFbeta signalling and disrupt the metastatic cascade