Effect of dedifferentiation on time to mutation acquisition in stem cell-driven cancers.
Effect of dedifferentiation on time to mutation acquisition in stem cell-driven cancers.
复制标题
去分化对干细胞驱动癌症突变获取时间的时间的影响。
DOI：
10.1371/journal.pcbi.1003481
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发表时间：
2014-03
影响因子：
4.3
通讯作者：
Gutenkunst RN
中科院分区：
文献类型：
--
作者：
Jilkine A;Gutenkunst RN
越来越多的证据表明，许多肿瘤具有分层组织，肿瘤的大部分由相对分化的短寿命祖细胞组成，这些祖细胞由一小群未分化的长寿命癌症干细胞维持。然而，目前尚不清楚癌症干细胞是起源于正常干细胞还是起源于去分化祖细胞。为了解决这个问题，我们数学建模的影响去分化的致癌作用。我们考虑了干细胞和祖细胞突变累积的混合随机-确定性模型，包括祖细胞向干细胞样状态的去分化。我们进行了精确的计算机模拟两个突变的肿瘤亚群的出现，我们推导出半分析估计的等待时间分布固定。我们的研究结果表明，去分化可能在癌变过程中发挥重要作用，这取决于干细胞的稳态是如何维持的。如果干细胞群体的大小保持严格恒定（由于所有分裂都是不对称的），我们发现去分化在干细胞群体中起着积极的选择力的作用，从而加速了致癌作用。如果允许干细胞群体的大小随机变化与密度依赖性繁殖率（允许对称和不对称分裂），我们发现，去分化超过一个临界阈值导致干细胞群体的指数增长。因此，去分化可能起着至关重要的作用，恒定的干细胞群体大小的共同建模假设可能是不够的，进一步了解致癌需要一个更详细的机制理解干细胞稳态。最近的证据表明，像许多正常组织一样，许多癌症是由一小群永生干细胞维持的，这些干细胞无限分裂，产生许多分化的细胞。癌症干细胞可能直接来自正常干细胞的突变，但这一途径需要高突变率，因为正常干细胞很少。然而，有许多分化的细胞，突变可以导致这些细胞“去分化”成干细胞样状态。我们使用数学建模来研究去分化对癌症发作时间的影响。我们发现，去分化的效果关键取决于身体如何控制干细胞数量。如果体内平衡非常紧密（由于所有分裂都是不对称的），那么去分化几乎没有影响，但是如果体内平衡控制较松（允许对称和不对称分裂），那么去分化可以显著加速癌症发作并导致癌症干细胞群体的指数增长。我们的研究结果表明，去分化可能是一个非常重要的因素，在癌症和更多的研究去分化和干细胞控制是必要的，以了解和预防癌症的发病。
Accumulating evidence suggests that many tumors have a hierarchical organization, with the bulk of the tumor composed of relatively differentiated short-lived progenitor cells that are maintained by a small population of undifferentiated long-lived cancer stem cells. It is unclear, however, whether cancer stem cells originate from normal stem cells or from dedifferentiated progenitor cells. To address this, we mathematically modeled the effect of dedifferentiation on carcinogenesis. We considered a hybrid stochastic-deterministic model of mutation accumulation in both stem cells and progenitors, including dedifferentiation of progenitor cells to a stem cell-like state. We performed exact computer simulations of the emergence of tumor subpopulations with two mutations, and we derived semi-analytical estimates for the waiting time distribution to fixation. Our results suggest that dedifferentiation may play an important role in carcinogenesis, depending on how stem cell homeostasis is maintained. If the stem cell population size is held strictly constant (due to all divisions being asymmetric), we found that dedifferentiation acts like a positive selective force in the stem cell population and thus speeds carcinogenesis. If the stem cell population size is allowed to vary stochastically with density-dependent reproduction rates (allowing both symmetric and asymmetric divisions), we found that dedifferentiation beyond a critical threshold leads to exponential growth of the stem cell population. Thus, dedifferentiation may play a crucial role, the common modeling assumption of constant stem cell population size may not be adequate, and further progress in understanding carcinogenesis demands a more detailed mechanistic understanding of stem cell homeostasis. Recent evidence suggests that, like many normal tissues, many cancers are maintained by a small population of immortal stem cells that divide indefinitely to produce many differentiated cells. Cancer stem cells may come directly from mutation of normal stem cells, but this route demands high mutation rates, because there are few normal stem cells. There are, however, many differentiated cells, and mutations can cause such cells to “dedifferentiate” into a stem-like state. We used mathematical modeling to study the effects of dedifferentiation on the time to cancer onset. We found that the effect of dedifferentiation depends critically on how stem cell numbers are controlled by the body. If homeostasis is very tight (due to all divisions being asymmetric), then dedifferentiation has little effect, but if homeostatic control is looser (allowing both symmetric and asymmetric divisions), then dedifferentiation can dramatically hasten cancer onset and lead to exponential growth of the cancer stem cell population. Our results suggest that dedifferentiation may be a very important factor in cancer and that more study of dedifferentiation and stem cell control is necessary to understand and prevent cancer onset.
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影响因子：
4.3
作者：
Dingli D;Traulsen A;Michor F
通讯作者：
Michor F
DOI：
10.1073/pnas.0802749105
发表时间：
2008-11-25
影响因子：
11.1
作者：
Dingli, David;Luzzatto, Lucio;Pacheco, Jorge M.
通讯作者：
Pacheco, Jorge M.
影响因子：
3.3
作者：
Haeno, Hiroshi;Iwasa, Yoh;Michor, Franziska
通讯作者：
Michor, Franziska
肿瘤前期进展 人类干细胞群体的克隆进化
影响因子：
6
作者：
Calabrese, P;Tavaré, S;Shibata, D
通讯作者：
Shibata, D
DOI：
10.1111/j.1749-6632.2009.04880.x
发表时间：
2009-01-01
期刊：
YEAR IN EVOLUTIONARY BIOLOGY 2009
影响因子：
--
作者：
Attolini, Camille Stephan-Otto;Michor, Franziska
通讯作者：
Michor, Franziska