Proceedings of the National Academy of Sciences · 2009 · 197 citations · 28 references
MedicineMolecular BiologyOncologyBreast OncologyMolecular OncologyOncogenesCancer Cell SignalingCancer ProgressionMammary TumorsOncogenic Signaling PathwaysReceptor Tyrosine Kinase OncogenesSignal Transduction In CancerBreast Cancer Molecular SubtypesBreast Cancer PrognosisEpithelial-mesenchymal Transition In CancerEpithelial-mesenchymal Transition MarkersMet Receptor Tyrosine KinaseTransgenic Model GenerationTransgenic Mouse Cancer ModelsTransgenic Mouse Models
Elevated MET receptor tyrosine kinase correlates with poor outcome in breast cancer, yet the reasons for this are poorly understood. We thus generated a transgenic mouse model targeting expression of an oncogenic Met receptor (Met(mt)) to the mammary epithelium. We show that Met(mt) induces mammary tumors with multiple phenotypes. These reflect tumor subtypes with gene expression and immunostaining profiles sharing similarities to human basal and luminal breast cancers. Within the basal subtype, Met(mt) induces tumors with signatures of WNT and epithelial to mesenchymal transition (EMT). Among human breast cancers, MET is primarily elevated in basal and ERBB2-positive subtypes with poor prognosis, and we show that MET, together with EMT marker, SNAIL, are highly predictive of poor prognosis in lymph node-negative patients. By generating a unique mouse model in which the Met receptor tyrosine kinase is expressed in the mammary epithelium, along with the examination of MET expression in human breast cancer, we have established a specific link between MET and basal breast cancer. This work identifies basal breast cancers and, additionally, poor-outcome breast cancers, as those that may benefit from anti-MET receptor therapies.
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A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
Marc J. van de Vijver, Yudong D. He, Laura van ‘t Veer et al. · New England Journal of Medicine · 2002 · 6.5K citations · Full text
Medicine, Bioinformatics, Oncology +17
Stromal gene expression predicts clinical outcome in breast cancer
Greg Finak, Nicholas Bertos, François Pépin et al. · Nature Medicine · 2008 · 1.7K citations