We are analyzing https://link.springer.com/article/10.1186/1752-0509-3-1.

Title:
Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance | BMC Systems Biology
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.
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Keywords {🔍}

cells, erbb, trastuzumab, cell, protein, figure, network, prb, cancer, article, pubmed, knockdown, cyclin, resistant, level, google, scholar, breast, hcc, proteins, cmyc, phosphorylation, data, cas, results, table, transition, novo, expression, cdk, file, egf, resistance, hours, knockdowns, receptors, simulations, experimental, model, egfr, logical, levels, erα, additional, cycle, treatment, system, interactions, combinatorial, receptor,

Topics {✒️}

author information authors helmholtz program sb-cancer molecular genome analysis anticancer drug target erbb-receptor regulated network time-lapse profile article download pdf erbb receptor-regulated g1/ denis thieffry selective anti-proliferative agents egf-erbb signalling holger fröhlich targeted anticancer prodrug erbb2-positive breast cancer phosphorylation profile similar systems biology approach spot-specific background signals nitrocellulose coated oncyte-slides de novo resistant related subjects tamoxifen-resistant mcf-7 cells real-time impedance measurements targeting egfr signalling anti-erbb3 antibody seribantumab de novo resistance circumventing de novo full size image receptor tyrosine kinases her2-targeting antibodies modulate e2f transcription factor mock profile cell cycle arrest g0/g1 arrested cells erbb-receptor signaling reduced-serum medium optimem ig prostate-cancer g1 cell-cycle control metastatic breast cancer sk-br-3 cells responded predict therapeutic strategies breast cell lines drug-target network transcription factors c-myc privacy choices/manage cookies qrt-pcr results showing hcc1954 cell line cell cycle progression c-myc inhibitor 10058-f4 breast cancer patients solid black arrows

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         description: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. 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. 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.
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         Physiological
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      name:Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany
      name:Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany
      name:Technologies Avancées pour le Génome et la Clinique, INSERM U928, Université de la Méditerranée, Marseille, France
      name:Technologies Avancées pour le Génome et la Clinique, INSERM U928, Université de la Méditerranée, Marseille, France
      name:Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany
      name:Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany
      name:Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany
      name:Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany

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