<p>In this paper, first of all, we present a stochastic tumor-immune model with adoptive cell transfer therapy. Then, we derive a threshold parameter <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\lambda \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>λ</mi> </math></EquationSource> </InlineEquation> that classifies the long-term dynamical behavior of tumor cells. When <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\lambda &lt;0\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>λ</mi> <mo>&lt;</mo> <mn>0</mn> </mrow> </math></EquationSource> </InlineEquation>, the tumor cells are extinct, while <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\lambda &gt;0\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>λ</mi> <mo>&gt;</mo> <mn>0</mn> </mrow> </math></EquationSource> </InlineEquation>, the tumor cells are persistent and the model has a unique invariant probability measure. Finally, we find that the mathematical expectation of tumor cell population and the stochastic perturbation intensity have a non-monotonic relationship while the threshold <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\lambda \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>λ</mi> </math></EquationSource> </InlineEquation> and the stochastic perturbation intensity have a monotonic relationship. These results further deepen understanding to stochasticity in tumor therapy.</p>

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Threshold dynamics of a stochastic tumor-immune model with adoptive cell transfer therapy

  • Xiao-Bing Zhang,
  • Rui-Yan Ning

摘要

In this paper, first of all, we present a stochastic tumor-immune model with adoptive cell transfer therapy. Then, we derive a threshold parameter \(\lambda \) λ that classifies the long-term dynamical behavior of tumor cells. When \(\lambda <0\) λ < 0 , the tumor cells are extinct, while \(\lambda >0\) λ > 0 , the tumor cells are persistent and the model has a unique invariant probability measure. Finally, we find that the mathematical expectation of tumor cell population and the stochastic perturbation intensity have a non-monotonic relationship while the threshold \(\lambda \) λ and the stochastic perturbation intensity have a monotonic relationship. These results further deepen understanding to stochasticity in tumor therapy.