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Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies
The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network consider...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4467132/ https://www.ncbi.nlm.nih.gov/pubmed/25671297 |
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author | Tortolina, Lorenzo Duffy, David J. Maffei, Massimo Castagnino, Nicoletta Carmody, Aimée M. Kolch, Walter Kholodenko, Boris N. Ambrosi, Cristina De Barla, Annalisa Biganzoli, Elia M. Nencioni, Alessio Patrone, Franco Ballestrero, Alberto Zoppoli, Gabriele Verri, Alessandro Parodi, Silvio |
author_facet | Tortolina, Lorenzo Duffy, David J. Maffei, Massimo Castagnino, Nicoletta Carmody, Aimée M. Kolch, Walter Kholodenko, Boris N. Ambrosi, Cristina De Barla, Annalisa Biganzoli, Elia M. Nencioni, Alessio Patrone, Franco Ballestrero, Alberto Zoppoli, Gabriele Verri, Alessandro Parodi, Silvio |
author_sort | Tortolina, Lorenzo |
collection | PubMed |
description | The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions. Starting from an initial “physiologic condition”, the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model. Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal. |
format | Online Article Text |
id | pubmed-4467132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-44671322015-06-22 Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies Tortolina, Lorenzo Duffy, David J. Maffei, Massimo Castagnino, Nicoletta Carmody, Aimée M. Kolch, Walter Kholodenko, Boris N. Ambrosi, Cristina De Barla, Annalisa Biganzoli, Elia M. Nencioni, Alessio Patrone, Franco Ballestrero, Alberto Zoppoli, Gabriele Verri, Alessandro Parodi, Silvio Oncotarget Research Paper The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions. Starting from an initial “physiologic condition”, the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model. Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal. Impact Journals LLC 2014-12-31 /pmc/articles/PMC4467132/ /pubmed/25671297 Text en Copyright: © 2015 Tortolina et al. http://creativecommons.org/licenses/by/2.5/ 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 credited. |
spellingShingle | Research Paper Tortolina, Lorenzo Duffy, David J. Maffei, Massimo Castagnino, Nicoletta Carmody, Aimée M. Kolch, Walter Kholodenko, Boris N. Ambrosi, Cristina De Barla, Annalisa Biganzoli, Elia M. Nencioni, Alessio Patrone, Franco Ballestrero, Alberto Zoppoli, Gabriele Verri, Alessandro Parodi, Silvio Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies |
title | Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies |
title_full | Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies |
title_fullStr | Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies |
title_full_unstemmed | Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies |
title_short | Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies |
title_sort | advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4467132/ https://www.ncbi.nlm.nih.gov/pubmed/25671297 |
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