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Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma
Hepatocyte growth factor (HGF) signaling through its receptor Met has been implicated in hepatocellular carcinoma tumorigenesis and progression. Met interaction with integrins is shown to modulate the downstream signaling to Akt and ERK (extracellular-regulated kinase). In this study, we developed a...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697704/ https://www.ncbi.nlm.nih.gov/pubmed/31452933 http://dx.doi.org/10.1038/s41540-019-0107-2 |
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author | Jafarnejad, Mohammad Sové, Richard J. Danilova, Ludmila Mirando, Adam C. Zhang, Yu Yarchoan, Mark Tran, Phuoc T. Pandey, Niranjan B. Fertig, Elana J. Popel, Aleksander S. |
author_facet | Jafarnejad, Mohammad Sové, Richard J. Danilova, Ludmila Mirando, Adam C. Zhang, Yu Yarchoan, Mark Tran, Phuoc T. Pandey, Niranjan B. Fertig, Elana J. Popel, Aleksander S. |
author_sort | Jafarnejad, Mohammad |
collection | PubMed |
description | Hepatocyte growth factor (HGF) signaling through its receptor Met has been implicated in hepatocellular carcinoma tumorigenesis and progression. Met interaction with integrins is shown to modulate the downstream signaling to Akt and ERK (extracellular-regulated kinase). In this study, we developed a mechanistically detailed systems biology model of HGF/Met signaling pathway that incorporated specific interactions with integrins to investigate the efficacy of integrin-binding peptide, AXT050, as monotherapy and in combination with other therapeutics targeting this pathway. Here we report that the modeled dynamics of the response to AXT050 revealed that receptor trafficking is sufficient to explain the effect of Met–integrin interactions on HGF signaling. Furthermore, the model predicted patient-specific synergy and antagonism of efficacy and potency for combination of AXT050 with sorafenib, cabozantinib, and rilotumumab. Overall, the model provides a valuable framework for studying the efficacy of drugs targeting receptor tyrosine kinase interaction with integrins, and identification of synergistic drug combinations for the patients. |
format | Online Article Text |
id | pubmed-6697704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66977042019-08-26 Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma Jafarnejad, Mohammad Sové, Richard J. Danilova, Ludmila Mirando, Adam C. Zhang, Yu Yarchoan, Mark Tran, Phuoc T. Pandey, Niranjan B. Fertig, Elana J. Popel, Aleksander S. NPJ Syst Biol Appl Article Hepatocyte growth factor (HGF) signaling through its receptor Met has been implicated in hepatocellular carcinoma tumorigenesis and progression. Met interaction with integrins is shown to modulate the downstream signaling to Akt and ERK (extracellular-regulated kinase). In this study, we developed a mechanistically detailed systems biology model of HGF/Met signaling pathway that incorporated specific interactions with integrins to investigate the efficacy of integrin-binding peptide, AXT050, as monotherapy and in combination with other therapeutics targeting this pathway. Here we report that the modeled dynamics of the response to AXT050 revealed that receptor trafficking is sufficient to explain the effect of Met–integrin interactions on HGF signaling. Furthermore, the model predicted patient-specific synergy and antagonism of efficacy and potency for combination of AXT050 with sorafenib, cabozantinib, and rilotumumab. Overall, the model provides a valuable framework for studying the efficacy of drugs targeting receptor tyrosine kinase interaction with integrins, and identification of synergistic drug combinations for the patients. Nature Publishing Group UK 2019-08-16 /pmc/articles/PMC6697704/ /pubmed/31452933 http://dx.doi.org/10.1038/s41540-019-0107-2 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jafarnejad, Mohammad Sové, Richard J. Danilova, Ludmila Mirando, Adam C. Zhang, Yu Yarchoan, Mark Tran, Phuoc T. Pandey, Niranjan B. Fertig, Elana J. Popel, Aleksander S. Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma |
title | Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma |
title_full | Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma |
title_fullStr | Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma |
title_full_unstemmed | Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma |
title_short | Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma |
title_sort | mechanistically detailed systems biology modeling of the hgf/met pathway in hepatocellular carcinoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697704/ https://www.ncbi.nlm.nih.gov/pubmed/31452933 http://dx.doi.org/10.1038/s41540-019-0107-2 |
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