Advances in dynamic modeling of colorectal cancer signalingnetwork regions, a path toward targeted therapies

Lorenzo Tortolina, David J. Duffy, Massimo Maffei, Nicoletta Castagnino, Aimée M. Carmody, Walter Kolch, Boris N. Kholodenko, Cristina De Ambrosi, Annalisa Barla, Elia M. Biganzoli, Alessio Nencioni, Franco Patrone, Alberto Ballestrero, Gabriele Zoppoli, Alessandro Verri, Silvio Parodi

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)5041-5058
Number of pages18
Issue number7
Publication statusPublished - 2015


  • Colorectal cancer
  • Dynamic modeling
  • Onco-protein inhibitors
  • Signaling-network
  • Target therapies

ASJC Scopus subject areas

  • Oncology


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