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• W2168459281 abstract "To determine the signaling pathways leading from Met activation to metastasis and poor prognosis, we measured the kinetic gene alterations in breast cancer cell lines in response to HGF/SF. Using a network inference tool we analyzed the putative protein-protein interaction pathways leading from Met to these genes and studied their specificity to Met and prognostic potential. We identified a Met kinetic signature consisting of 131 genes. The signature correlates with Met activation and with response to anti-Met therapy (p<0.005) in in-vitro models. It also identifies breast cancer patients who are at high risk to develop an aggressive disease in six large published breast cancer patient cohorts (p<0.01, N>1000). Moreover, we have identified novel putative Met pathways, which correlate with Met activity and patient prognosis. This signature may facilitate personalized therapy by identifying patients who will respond to anti-Met therapy. Moreover, this novel approach may be applied for other tyrosine kinases and other malignancies." @default.
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• W2168459281 date "2012-09-25" @default.
• W2168459281 modified "2023-09-23" @default.
• W2168459281 title "Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival" @default.
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• W2168459281 doi "https://doi.org/10.1371/journal.pone.0045969" @default.
• W2168459281 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3457970" @default.
• W2168459281 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23049908" @default.
• W2168459281 hasPublicationYear "2012" @default.
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