Combination therapy for melanoma with BRAF/MEK inhibitor and immune checkpoint inhibitor: a mathematical model

Xiulan Lai1, Avner Friedman2

  • 1Institute for Mathematical Sciences, Renmin University of China, Beijing, 100872, People's Republic of China. xiulanlai@ruc.edu.cn.

BMC Systems Biology
|July 21, 2017
PubMed
Abstract

Insights

Combining BRAF/MEK and PD-1 inhibitors for melanoma shows a complex relationship. Low doses of both drugs are synergistic, but high doses can be antagonistic, potentially increasing tumor growth.

Area of Science:

  • Oncology
  • Immunology
  • Mathematical Biology

Background:

  • BRAF mutations drive melanoma proliferation via the MAPK pathway.
  • BRAF/MEK inhibitors offer initial efficacy but short-lived responses.
  • PD-1 inhibitors provide durable responses but have lower initial response rates.

Purpose of the Study:

  • To mathematically model the correlation between BRAF/MEK and PD-1 inhibitors in melanoma therapy.
  • To develop an efficacy map for combined drug concentrations.
  • To identify potential antagonistic interactions between the inhibitors.

Main Methods:

  • Development of a mathematical model using partial differential equations.
  • Inclusion of key cellular components (dendritic cells, cancer cells, T cells, MDSCs) and molecular factors (cytokines, PD-1/PD-L1).
  • Analysis of drug concentrations (γB for BRAF/MEK inhibitor, γA for PD-1 inhibitor).

Main Results:

  • A positive correlation exists between BRAF/MEK and PD-1 inhibitors at low doses, leading to decreased tumor volume.
  • Antagonistic effects were observed at certain high doses, where increasing one drug could unexpectedly increase tumor growth.
  • An efficacy map was generated to visualize these dose-dependent interactions.

Conclusions:

  • Identifying zones of drug antagonism is crucial for optimizing melanoma treatment strategies.
  • Animal experiments and early clinical trials are needed to pinpoint these antagonistic dose ranges.
  • Avoiding antagonistic zones will be vital for improving outcomes in advanced clinical trials.

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