Project 2 modeling of drug resistance in breast cancer
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Project 2: Modeling of Drug Resistance in Breast Cancer. Aim 1: Contribution of cellular heterogeneity to the development of breast cancer drug resistance to targeted Molecular Therapeutics (MT). Cancer Biology Alissa Weaver – invasion Darren Tyson – proliferation

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Project 2: Modeling of Drug Resistance in Breast Cancer

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Project 2 modeling of drug resistance in breast cancer

Project 2: Modeling of Drug Resistance in Breast Cancer

Aim 1: Contribution of cellular heterogeneity to the development of breast cancer drug resistance to targeted Molecular Therapeutics (MT)

Cancer Biology

  • Alissa Weaver – invasion

  • Darren Tyson – proliferation

  • Simon Hayward - in vivo models

  • Carlos Arteaga & Brent Rexer - drug resistance

  • Jerome Jourquin - data integration

  • Shawn Garbett – computation

    Lourdes Estrada - coordination, outreach

    Vito Quaranta, Director

Biomathematics (Moffitt)

  • AlexanderAnderson - mathematical models of cancer

  • KatarzynaRejniak - mechanics of cell processes

  • David Basanta - game theory, computation

    Biomathematics (Vanderbilt)

  • Glenn Webb - ODEs, PDEs

    Chemical Engineering (Vanderbilt)

  • Jamey Young - metabolic flux


  • High resolution cellular responses to mt proliferation

    High Resolution Cellular Responses to MT(proliferation)

    Non-linear effects

    Time-dependent sensitivity to MT

    Erlotinib:

    27% inhibition, 24h

    43% inhibition, 48h

    Ensemble Cell Count Data

    Same as CHX at 48h but 40% less at 24h


    Project 2 modeling of drug resistance in breast cancer

    InterMitoticTime (IMT) Data

    EMG Model

    IMT

    IMT

    IMT

    Quiescent?

    Quiescent- Growth Model

    P

    Q

    erlotinib

    CHX

    DMSO


    Conclusions and future steps

    Conclusions and Future Steps

    • IC50 may not represent accurately cell responses to MT due to non-linear effects

    • MT may affect components of EMG differently

    • The exponential “fat tails” may contain quiescent population of cells

    Where is the position of oncogene-addicted cells in this high resolution landscape of cellular responses to MT?


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