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Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival
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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3457970/ https://www.ncbi.nlm.nih.gov/pubmed/23049908 http://dx.doi.org/10.1371/journal.pone.0045969 |
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author | Stein, Gideon Y. Yosef, Nir Reichman, Hadar Horev, Judith Laser-Azogui, Adi Berens, Angelique Resau, James Ruppin, Eytan Sharan, Roded Tsarfaty, Ilan |
author_facet | Stein, Gideon Y. Yosef, Nir Reichman, Hadar Horev, Judith Laser-Azogui, Adi Berens, Angelique Resau, James Ruppin, Eytan Sharan, Roded Tsarfaty, Ilan |
author_sort | Stein, Gideon Y. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3457970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34579702012-10-03 Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival Stein, Gideon Y. Yosef, Nir Reichman, Hadar Horev, Judith Laser-Azogui, Adi Berens, Angelique Resau, James Ruppin, Eytan Sharan, Roded Tsarfaty, Ilan PLoS One Research Article 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. Public Library of Science 2012-09-25 /pmc/articles/PMC3457970/ /pubmed/23049908 http://dx.doi.org/10.1371/journal.pone.0045969 Text en © 2012 Stein et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Stein, Gideon Y. Yosef, Nir Reichman, Hadar Horev, Judith Laser-Azogui, Adi Berens, Angelique Resau, James Ruppin, Eytan Sharan, Roded Tsarfaty, Ilan Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival |
title | Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival |
title_full | Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival |
title_fullStr | Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival |
title_full_unstemmed | Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival |
title_short | Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival |
title_sort | met kinetic signature derived from the response to hgf/sf in a cellular model predicts breast cancer patient survival |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3457970/ https://www.ncbi.nlm.nih.gov/pubmed/23049908 http://dx.doi.org/10.1371/journal.pone.0045969 |
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