Dynamic Simulations of Pathways Downstream of TGFβ, Wnt and EGF-Family Growth Factors, in Colorectal Cancer, including Mutations and Treatments with Onco-Protein Inhibitors

  • Lorenzo Tortolina
  • Nicoletta Castagnino
  • Cristina De Ambrosi
  • Annalisa Barla
  • Alessandro Verri
  • Gabriele Zoppoli
  • Luca Bagnasco
  • Daniela Piras
  • Franco Patrone
  • Alberto Ballestrero
  • Silvio Parodi
Part of the SIMAI Springer Series book series (SEMA SIMAI)

Abstract

With reference to colorectal cancer, we have reconstructed a Molecular Interaction Map downstream of TGFβ, Wnt and EGF-family. Based on an extensive and systematic direct/indirect data extrapolation from several dozens of published experimental papers, and some data interpolation that could fit with the general behavior of this signaling-network region, we were able to obtain an operative mathematical simulation model. We could simulate normal conditions of the network, behavior in the presence of important colorectal cancer mutations, behavior in the presence of virtual drug inhibitors of different specifically altered onco-proteins affected by excess of function. The dynamic behavior of the simulation seems quite reasonable, in terms of what is known about the physiology and the pathology of this signaling-network region. Preliminary experimental verification experiments look encouraging.

Notes

Acknowledgements

This paper was partially supported by: Liguria Region Project (N. 280 – 2010–2011): “Study and simulation of molecular interaction networks relevant in malignant transformation; search and study of inhibitors of the onco-proteins c-Myc and Bcl-XL”; CARIGE Foundation Project (N. 2010/228–16): “Analysis of molecular alterations in signal transduction networks downstream of EGFR-family receptors, in HER2 positive breast cancers and triple negative cancers. Rationalization at the clinical level of personalized antineoplastic therapies with onco-protein inhibitors”; Compagnia di San Paolo Project (1471 SD/CC N. 2009.1822): “Models and computational methods in the study of physiology and pathology of signaling networks of oncologic interest”; Istituto Superiore di Oncologia (ISO): Grant 2006 from Istituto Superiore di Sanità: “Development of new drugs capable of modifying the cancer micro-environment”. Grant RF-CAM-2006-353005 Regione Campania, from Italian Ministry of Health: “Molecular Diagnostic and Prognostic Markers of Thyroid Neoplasias”. Finally, we are deeply grateful to Kurt W. Kohn for the continuous exchange of ideas in the field of Molecular Interaction Maps, that he pioneered already a dozen years ago.

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Copyright information

© Springer-Verlag Italia 2012

Authors and Affiliations

  • Lorenzo Tortolina
    • 1
  • Nicoletta Castagnino
    • 1
  • Cristina De Ambrosi
    • 2
  • Annalisa Barla
    • 3
  • Alessandro Verri
    • 3
  • Gabriele Zoppoli
    • 4
  • Luca Bagnasco
    • 5
  • Daniela Piras
    • 5
  • Franco Patrone
    • 6
  • Alberto Ballestrero
    • 6
  • Silvio Parodi
    • 1
  1. 1.Department of Internal Medicine (Di.M.I.), Research Center for Computational Learning (CRAC)IRCCS Azienda Ospedaliera Universitaria San Martino-IST, Istituto Superiore di Oncologia (ISO)GenoaItaly
  2. 2.Department of Internal Medicine (Di.M.I.), Department of Computer and Information Science (DISI)Research Center for Computational Learning (CRAC), IRCCS Azienda Ospedaliera Universitaria San Martino-ISTGenoaItaly
  3. 3.Department of Computer and Information Science (DISI), Research Center for Computational Learning (CRAC)University of GenoaGenoaItaly
  4. 4.Department of Internal Medicine (Di.M.I.), Research Center for Computational Learning (CRAC)IRCCS Azienda Ospedaliera Universitaria San Martino-ISTGenoaItaly
  5. 5.Department of Internal Medicine (Di.M.I.)IRCCS Azienda Ospedaliera Universitaria San Martino-IST, Istituto Superiore di Oncologia (ISO)GenoaItaly
  6. 6.Department of Internal Medicine (Di.M.I.)IRCCS Azienda Ospedaliera Universitaria San Martino-ISTGenoaItaly

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