TY - JOUR
T1 - Advances in dynamic modeling of colorectal cancer signalingnetwork regions, a path toward targeted therapies
AU - Tortolina, Lorenzo
AU - Duffy, David J.
AU - Maffei, Massimo
AU - Castagnino, Nicoletta
AU - Carmody, Aimée M.
AU - Kolch, Walter
AU - Kholodenko, Boris N.
AU - De Ambrosi, Cristina
AU - Barla, Annalisa
AU - Biganzoli, Elia M.
AU - Nencioni, Alessio
AU - Patrone, Franco
AU - Ballestrero, Alberto
AU - Zoppoli, Gabriele
AU - Verri, Alessandro
AU - Parodi, Silvio
PY - 2015
Y1 - 2015
N2 - The interconnected network of pathways downstream of the TGFß, WNT and EGFfamilies 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.
AB - The interconnected network of pathways downstream of the TGFß, WNT and EGFfamilies 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.
KW - Colorectal cancer
KW - Dynamic modeling
KW - Onco-protein inhibitors
KW - Signaling-network
KW - Target therapies
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M3 - Article
AN - SCOPUS:84924939965
VL - 6
SP - 5041
EP - 5058
JO - Oncotarget
JF - Oncotarget
SN - 1949-2553
IS - 7
ER -