Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms
We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems‐level per...
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| Published in | Molecular systems biology Vol. 9; no. 1; pp. 705 - n/a |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
05.11.2013
John Wiley & Sons, Ltd EMBO Press European Molecular Biology Organization Springer Nature |
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| Online Access | Get full text |
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| Abstract | We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer,
via
global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems‐level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14‐protein core network critical to the viability of multiple EGFR‐mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR‐mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance.
A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells.
Synopsis
A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells.
The interactome of lung cancer‐associated mutant forms of epidermal growth factor receptor (EGFR), consisting of 263 proteins, was built by integrating protein–protein interactions and tyrosine phosphorylation.
Systematic perturbations of the network nodes revealed a core network of 14 proteins, 9 of which were shown to be specifically associated with survival of EGFR‐mutant lung cancer cells.
Cells with acquired resistance to EGFR tyrosine kinase inhibitors showed differential dependence on the core network proteins.
A drug network associated with the core network proteins led to the identification of two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. |
|---|---|
| AbstractList | We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein-protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems‐level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14‐protein core network critical to the viability of multiple EGFR‐mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR‐mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells. Synopsis A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells. The interactome of lung cancer‐associated mutant forms of epidermal growth factor receptor (EGFR), consisting of 263 proteins, was built by integrating protein–protein interactions and tyrosine phosphorylation. Systematic perturbations of the network nodes revealed a core network of 14 proteins, 9 of which were shown to be specifically associated with survival of EGFR‐mutant lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors showed differential dependence on the core network proteins. A drug network associated with the core network proteins led to the identification of two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Abstract We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems‐level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14‐protein core network critical to the viability of multiple EGFR‐mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR‐mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein-protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance.We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein-protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems‐level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14‐protein core network critical to the viability of multiple EGFR‐mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR‐mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells. A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells. image The interactome of lung cancer‐associated mutant forms of epidermal growth factor receptor (EGFR), consisting of 263 proteins, was built by integrating protein–protein interactions and tyrosine phosphorylation. Systematic perturbations of the network nodes revealed a core network of 14 proteins, 9 of which were shown to be specifically associated with survival of EGFR‐mutant lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors showed differential dependence on the core network proteins. A drug network associated with the core network proteins led to the identification of two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. A ‘lung cancer'-specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR-mutant lung cancer cells. The interactome of lung cancer-associated mutant forms of epidermal growth factor receptor (EGFR), consisting of 263 proteins, was built by integrating protein–protein interactions and tyrosine phosphorylation. Systematic perturbations of the network nodes revealed a core network of 14 proteins, 9 of which were shown to be specifically associated with survival of EGFR-mutant lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors showed differential dependence on the core network proteins. A drug network associated with the core network proteins led to the identification of two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems‐level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14‐protein core network critical to the viability of multiple EGFR‐mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR‐mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells. Synopsis A ‘lung cancer’‐specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional screening, nine proteins were identified as essential for the viability of EGFR‐mutant lung cancer cells. The interactome of lung cancer‐associated mutant forms of epidermal growth factor receptor (EGFR), consisting of 263 proteins, was built by integrating protein–protein interactions and tyrosine phosphorylation. Systematic perturbations of the network nodes revealed a core network of 14 proteins, 9 of which were shown to be specifically associated with survival of EGFR‐mutant lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors showed differential dependence on the core network proteins. A drug network associated with the core network proteins led to the identification of two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. |
| Author | Okamoto, Isamu Rawal, Bhupendra Bennett, Keiryn Stukalov, Alexey Koomen, John Bai, Yun Song, Lanxi Haura, Eric B Fang, Bin Schell, Michael Kim, Jae‐Young Zhang, Guolin Colinge, Jacques Li, Jiannong Eschrich, Steven Winter, Georg Yoshida, Takeshi Qian, Xiaoning Superti‐Furga, Giulio Grebien, Florian Rix, Uwe |
| Author_xml | – sequence: 1 givenname: Jiannong surname: Li fullname: Li, Jiannong organization: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute – sequence: 2 givenname: Keiryn surname: Bennett fullname: Bennett, Keiryn organization: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences – sequence: 3 givenname: Alexey surname: Stukalov fullname: Stukalov, Alexey organization: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences – sequence: 4 givenname: Bin surname: Fang fullname: Fang, Bin organization: Proteomics and Molecular Oncology Program, H. Lee Moffitt Cancer Center and Research Institute – sequence: 5 givenname: Guolin surname: Zhang fullname: Zhang, Guolin organization: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute – sequence: 6 givenname: Takeshi surname: Yoshida fullname: Yoshida, Takeshi organization: Center for Clinical and Translational Research, Kyushu University Hospital – sequence: 7 givenname: Isamu surname: Okamoto fullname: Okamoto, Isamu organization: Center for Clinical and Translational Research, Kyushu University Hospital – sequence: 8 givenname: Jae‐Young surname: Kim fullname: Kim, Jae‐Young organization: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute – sequence: 9 givenname: Lanxi surname: Song fullname: Song, Lanxi organization: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute – sequence: 10 givenname: Yun surname: Bai fullname: Bai, Yun organization: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute – sequence: 11 givenname: Xiaoning surname: Qian fullname: Qian, Xiaoning organization: Department of Computer Science and Engineering, University of South Florida – sequence: 12 givenname: Bhupendra surname: Rawal fullname: Rawal, Bhupendra organization: Biostatistics Departments, H. Lee Moffitt Cancer Center and Research Institute – sequence: 13 givenname: Michael surname: Schell fullname: Schell, Michael organization: Biostatistics Departments, H. Lee Moffitt Cancer Center and Research Institute – sequence: 14 givenname: Florian surname: Grebien fullname: Grebien, Florian organization: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences – sequence: 15 givenname: Georg surname: Winter fullname: Winter, Georg organization: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences – sequence: 16 givenname: Uwe surname: Rix fullname: Rix, Uwe organization: Drug Discovery Department, H. Lee Moffitt Cancer Center and Research Institute – sequence: 17 givenname: Steven surname: Eschrich fullname: Eschrich, Steven organization: Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute – sequence: 18 givenname: Jacques surname: Colinge fullname: Colinge, Jacques organization: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences – sequence: 19 givenname: John surname: Koomen fullname: Koomen, John organization: Proteomics and Molecular Oncology Program, H. Lee Moffitt Cancer Center and Research Institute – sequence: 20 givenname: Giulio surname: Superti‐Furga fullname: Superti‐Furga, Giulio email: gsuperti@cemm.oeaw.ac.at organization: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences – sequence: 21 givenname: Eric B surname: Haura fullname: Haura, Eric B email: eric.haura@moffitt.org organization: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Department of Thoracic Oncology, Chemical Biology and Molecular Medicine Program, H. Lee Moffitt Cancer Center and Research Institute |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24189400$$D View this record in MEDLINE/PubMed |
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| DOI | 10.1038/msb.2013.61 |
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| Keywords | lung cancer interactome tyrosine kinase inhibitor proteomics epidermal growth factor receptor |
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| Snippet | We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer,
via
global analysis of... We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of... A ‘lung cancer'-specific mutant EGFR interactome was generated by a global analysis of protein–protein interactions and phosphorylation. After functional... Abstract We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis... |
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| SubjectTerms | Antineoplastic Agents - pharmacology Carbazoles - pharmacology CD11a antigen CD11b antigen Cell Line, Tumor Cell Survival - drug effects Chromatography Dependence Drug resistance Drug Resistance, Neoplasm - drug effects Drug Resistance, Neoplasm - genetics Drug Synergism EMBO31 EMBO37 Epidermal growth factor epidermal growth factor receptor Epidermal growth factor receptors ErbB Receptors - antagonists & inhibitors ErbB Receptors - genetics ErbB Receptors - metabolism Erlotinib Hydrochloride Etiology Experiments Furans Gene amplification Gene Expression Regulation, Neoplastic Genomics Grb2 protein Growth factors Humans interactome Kinases Lung cancer Mapping Mass spectrometry Molecular modelling Mutation Neoplasm Proteins - genetics Neoplasm Proteins - metabolism Perturbation Phosphorylation Protein interaction Protein Interaction Maps Protein Kinase Inhibitors - pharmacology Protein-tyrosine kinase Proteins Proteomics Quinazolines - pharmacology Scientific imaging Staurosporine - analogs & derivatives Staurosporine - pharmacology Tumor cell lines Tyrosine tyrosine kinase inhibitor Viability |
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| Title | Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms |
| URI | https://link.springer.com/article/10.1038/msb.2013.61 https://onlinelibrary.wiley.com/doi/abs/10.1038%2Fmsb.2013.61 https://www.ncbi.nlm.nih.gov/pubmed/24189400 https://www.proquest.com/docview/2299146951 https://www.proquest.com/docview/1449274668 https://pubmed.ncbi.nlm.nih.gov/PMC4039310 https://doaj.org/article/bc792efbcc2c4d1ebd85fd51a06f5c26 |
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