Application of a Biphasic Mathematical Model of Cancer Cell Drug Response for Formulating Potent and Synergistic

Jinyan Shen1,2, Li Li1,3, Niall G Howlett1

  • 1Department of Cell and Molecular Biology, University of Rhode Island, Kingston, RI 02881, USA.

Cancers
|May 1, 2020
PubMed

Insights

Triple negative breast cancer cells are multi-driver, requiring combinations of targeted therapies. A biphasic model identifies potent, synergistic drug combinations for effective cell killing.

Area of Science:

  • Oncology
  • Pharmacology
  • Mathematical Biology

Background:

  • Triple negative breast cancer (TNBC) lacks targeted therapy due to its heterogeneity and absence of identifiable dominant drivers.
  • Existing treatments for TNBC are limited, necessitating novel therapeutic strategies.

Purpose of the Study:

  • To test the hypothesis that TNBC cells are multi-driver cancer cells.
  • To evaluate a biphasic mathematical model for identifying potent and synergistic drug combinations for TNBC.

Main Methods:

  • Assessed drug responses of two TNBC cell lines (MDA-MB-231, MDA-MB-468) to targeted therapies across various concentrations.
  • Applied a biphasic mathematical model to analyze drug response data.
  • Utilized immunoblotting to analyze signaling pathway alterations induced by drug treatments.

Main Results:

  • The biphasic model confirmed multi-driver dependence in both TNBC cell lines.
  • Individual driver inhibitors showed biphasic responses: partial inhibition at low concentrations and off-target toxicity at higher concentrations.
  • Combinations of drugs targeting multiple drivers demonstrated potent, synergistic, and cell-specific cancer cell killing.

Conclusions:

  • TNBC cells exhibit multi-driver proliferation characteristics.
  • The biphasic mathematical model is effective in identifying synergistic targeted drug combinations for TNBC.
  • This approach offers a promising strategy for developing effective therapies for triple negative breast cancer.

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