Supplementary Matrials

Supplementary Materials for:

Integrating network reconstruction with mechanistic modeling to predict cancer therapies

Melinda Halasz,* Boris N. Kholodenko, Walter Kolch,* Tapesh Santra*

*Corresponding author. Email: walter.kolch{at}ucd.ie (W.K.); tapesh.santra{at}ucd.ie (T.S.); melinda.halasz{at}ucd.ie (M.H.)

This PDF file includes:

  • Note S1. Details of the BMRA algorithm.
  • Note S2. Benchmarking the BMRA algorithm.
  • Note S3. Sensitivity of the BMRA algorithm to noise and data incompleteness.
  • Note S4. Mechanistic modeling and parameter calibration using the BMM algorithm.
  • Note S5. Implementing BMRA to reconstruct the EGFR and IGF1R pathways.
  • Note S6. Mechanistic modeling of the EGFR and IGF1R pathways and the BMM algorithm.
  • Fig. S1. Interaction strengths of EGF and IGF1 network based on model simulation and experimental data.
  • Fig. S2. Effect of AKT inhibitor on IRS1 phosphorylation in four CRC cell lines.
  • Fig. S3. Effect of p70S6K knockdown on IRS1 phosphorylation in four CRC cell lines.
  • Fig. S4. Dynamics of ERK and AKT phosphorylation in HCT116 cells exposed to different concentrations of ligand.
  • Fig. S5. Effects of p70S6K knockdown and BIBX1382 treatment on serum-grown HCT116 cells.
  • Fig. S6. The amount of phosphorylated ERK in response to p70S6K knockdown in serum-grown HCT116 cells.
  • Fig. S7. Combined effect of p70S6K knockdown and BIBX1382 treatment on apoptosis of HCT116 cells.
  • Fig. S8. Combined effect of p70S6K knockdown and BIBX1382 treatment on apoptosis (cell death) of HKE3 cells.
  • Fig. S9. Combined effect of p70S6K knockdown and BIBX1382 treatment on apoptosis (cell death) of HT29 cells.
  • Legend for Code S1
  • References (65–81)

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Technical Details

Format: Adobe Acrobat PDF

Size: 2.21 MB

Other Supplementary Material for this manuscript includes the following:

  • Code S1 (.rar format). MATLAB source codes for the BMRA, BMM algorithm, and the ODE models.

Citation: M. Halasz, B. N. Kholodenko, W. Kolch, T. Santra, Integrating network reconstruction with mechanistic modeling to predict cancer therapies. Sci. Signal. 9, ra114 (2016).

© 2016 American Association for the Advancement of Science

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