动态网络熵在癌症中的应用
On dynamic network entropy in cancer
摘要：
细胞表型由分子相互作用的复杂网络描述。因此，阐明区分疾病与健康细胞状态的网络特性对于获得对疾病机制的系统级见解并最终开发改进的疗法至关重要。通过将基因表达数据与蛋白质相互作用网络相结合，以诱导网络上的随机动力学，我们在这里证明了癌细胞的特征在于动态网络熵的增加，与正常生理学的细胞相比。利用动力系统的宏观弹性与微观过程中的不确定性（熵）之间的基本关系，我们认为癌细胞对随机基因扰动将更加鲁棒。此外，我们正式证明，正常和癌症组织之间的基因表达差异与局部动态熵变化相关，从而提供了一个系统的节点和它们的局部网络动态之间的基因表达变化的联系。特别是，我们还发现，在癌细胞中驱动细胞增殖的基因和通常编码致癌基因的基因与动态网络熵的减少有关。总之，我们的结果支持这样的观点，即观察到的癌细胞对扰动和治疗的鲁棒性增加可能是由于动态网络熵的增加，使得细胞能够适应新的细胞应激。相反，在癌症中表现出局部通量熵降低的基因可能使癌细胞更容易受到靶向干预，因此可能代表有希望的药物靶点。
英文摘要：
The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.
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