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不稳定基因扩增的时间连续分支游走模型

Time-continuous branching walk models of unstable gene amplification.

作者信息

Kimmel M, Stivers D N

机构信息

Department of Statistics, Rice University, Houston, TX 77251-1892.

出版信息

Bull Math Biol. 1994 Mar;56(2):337-57. doi: 10.1007/BF02460646.

Abstract

We consider a stochastic mechanism of the loss of resistance of cancer cells to cytotoxic agents, in terms of unstable gene amplification. Two models being different versions of a time-continuous branching random walk are presented. Both models assume strong dependence in replication and segregation of the extrachromosomal elements. The mathematical part of the paper includes the expression for the expected number of cells with a given number of gene copies in terms of modified Bessel functions. This adds to the collection of rare explicit solutions to branching process models. Original asymptotic expansions are also demonstrated. Fitting the model to experimental data yields estimates of the probabilities of gene amplification and deamplification. The thesis of the paper is that purely stochastic mechanisms may explain the dynamics of reversible drug resistance of cancer cells. Various stochastic approaches and their limitations are discussed.

摘要

我们从不稳定基因扩增的角度考虑癌细胞对细胞毒性药物耐药性丧失的随机机制。提出了两个模型,它们是时间连续分支随机游走的不同版本。两个模型都假定染色体外元件在复制和分离过程中存在强依赖性。本文的数学部分包括用修正贝塞尔函数表示具有给定基因拷贝数的细胞预期数量。这增加了分支过程模型罕见显式解的集合。还展示了原始渐近展开。将模型与实验数据拟合可得出基因扩增和去扩增概率的估计值。本文的论点是,纯随机机制可以解释癌细胞可逆耐药性的动态变化。讨论了各种随机方法及其局限性。

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