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Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance
BACKGROUND: In breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic intervention, ERBB2 is targeted by monoclonal antibody trastuzumab in adjuvant settings; however, de novo resistance to t...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2652436/ https://www.ncbi.nlm.nih.gov/pubmed/19118495 http://dx.doi.org/10.1186/1752-0509-3-1 |
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author | Sahin, Özgür Fröhlich, Holger Löbke, Christian Korf, Ulrike Burmester, Sara Majety, Meher Mattern, Jens Schupp, Ingo Chaouiya, Claudine Thieffry, Denis Poustka, Annemarie Wiemann, Stefan Beissbarth, Tim Arlt, Dorit |
author_facet | Sahin, Özgür Fröhlich, Holger Löbke, Christian Korf, Ulrike Burmester, Sara Majety, Meher Mattern, Jens Schupp, Ingo Chaouiya, Claudine Thieffry, Denis Poustka, Annemarie Wiemann, Stefan Beissbarth, Tim Arlt, Dorit |
author_sort | Sahin, Özgür |
collection | PubMed |
description | BACKGROUND: In breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic intervention, ERBB2 is targeted by monoclonal antibody trastuzumab in adjuvant settings; however, de novo resistance to this antibody is still a serious issue, requiring the identification of additional targets to overcome resistance. In this study, we have combined computational simulations, experimental testing of simulation results, and finally reverse engineering of a protein interaction network to define potential therapeutic strategies for de novo trastuzumab resistant breast cancer. RESULTS: First, we employed Boolean logic to model regulatory interactions and simulated single and multiple protein loss-of-functions. Then, our simulation results were tested experimentally by producing single and double knockdowns of the network components and measuring their effects on G1/S transition during cell cycle progression. Combinatorial targeting of ERBB2 and EGFR did not affect the response to trastuzumab in de novo resistant cells, which might be due to decoupling of receptor activation and cell cycle progression. Furthermore, examination of c-MYC in resistant as well as in sensitive cell lines, using a specific chemical inhibitor of c-MYC (alone or in combination with trastuzumab), demonstrated that both trastuzumab sensitive and resistant cells responded to c-MYC perturbation. CONCLUSION: In this study, we connected ERBB signaling with G1/S transition of the cell cycle via two major cell signaling pathways and two key transcription factors, to model an interaction network that allows for the identification of novel targets in the treatment of trastuzumab resistant breast cancer. Applying this new strategy, we found that, in contrast to trastuzumab sensitive breast cancer cells, combinatorial targeting of ERBB receptors or of key signaling intermediates does not have potential for treatment of de novo trastuzumab resistant cells. Instead, c-MYC was identified as a novel potential target protein in breast cancer cells. |
format | Text |
id | pubmed-2652436 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26524362009-03-07 Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance Sahin, Özgür Fröhlich, Holger Löbke, Christian Korf, Ulrike Burmester, Sara Majety, Meher Mattern, Jens Schupp, Ingo Chaouiya, Claudine Thieffry, Denis Poustka, Annemarie Wiemann, Stefan Beissbarth, Tim Arlt, Dorit BMC Syst Biol Research Article BACKGROUND: In breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic intervention, ERBB2 is targeted by monoclonal antibody trastuzumab in adjuvant settings; however, de novo resistance to this antibody is still a serious issue, requiring the identification of additional targets to overcome resistance. In this study, we have combined computational simulations, experimental testing of simulation results, and finally reverse engineering of a protein interaction network to define potential therapeutic strategies for de novo trastuzumab resistant breast cancer. RESULTS: First, we employed Boolean logic to model regulatory interactions and simulated single and multiple protein loss-of-functions. Then, our simulation results were tested experimentally by producing single and double knockdowns of the network components and measuring their effects on G1/S transition during cell cycle progression. Combinatorial targeting of ERBB2 and EGFR did not affect the response to trastuzumab in de novo resistant cells, which might be due to decoupling of receptor activation and cell cycle progression. Furthermore, examination of c-MYC in resistant as well as in sensitive cell lines, using a specific chemical inhibitor of c-MYC (alone or in combination with trastuzumab), demonstrated that both trastuzumab sensitive and resistant cells responded to c-MYC perturbation. CONCLUSION: In this study, we connected ERBB signaling with G1/S transition of the cell cycle via two major cell signaling pathways and two key transcription factors, to model an interaction network that allows for the identification of novel targets in the treatment of trastuzumab resistant breast cancer. Applying this new strategy, we found that, in contrast to trastuzumab sensitive breast cancer cells, combinatorial targeting of ERBB receptors or of key signaling intermediates does not have potential for treatment of de novo trastuzumab resistant cells. Instead, c-MYC was identified as a novel potential target protein in breast cancer cells. BioMed Central 2009-01-01 /pmc/articles/PMC2652436/ /pubmed/19118495 http://dx.doi.org/10.1186/1752-0509-3-1 Text en Copyright © 2009 Sahin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Sahin, Özgür Fröhlich, Holger Löbke, Christian Korf, Ulrike Burmester, Sara Majety, Meher Mattern, Jens Schupp, Ingo Chaouiya, Claudine Thieffry, Denis Poustka, Annemarie Wiemann, Stefan Beissbarth, Tim Arlt, Dorit Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance |
title | Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance |
title_full | Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance |
title_fullStr | Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance |
title_full_unstemmed | Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance |
title_short | Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance |
title_sort | modeling erbb receptor-regulated g1/s transition to find novel targets for de novo trastuzumab resistance |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2652436/ https://www.ncbi.nlm.nih.gov/pubmed/19118495 http://dx.doi.org/10.1186/1752-0509-3-1 |
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