Glioblastoma Multiforme (GBM), the most malignant human tumour, can be defined by the evolution of growing bio-nanomachine networks within an interplay between self-renewal (Grow) and invasion (Go) potential of mutually exclusive phenotypes of transmitter and receiver cells. Herein, we present a mathematical model for the growth of GBM tumour driven by molecule-mediated inter-cellular communication between two populations of evolutionary bio-nanomachines representing the Glioma Stem Cells (GSCs) and Glioma Cells (GCs). The contribution of each subpopulation to tumour growth is quantified by a voxel model representing the end to end inter-cellular communication models for GSCs and progressively evolving invasiveness levels of glioma cells within a network of diverse cell configurations. Mutual information, information propagation speed and the impact of cell numbers and phenotypes on the communication output and GBM growth are studied by using analysis from information theory. The numerical simulations show that the progression of GBM is directly related to higher mutual information and higher input information flow of molecules between the GSCs and GCs, resulting in an increased tumour growth rate. These fundamental findings contribute to deciphering the mechanisms of tumour growth and are expected to provide new knowledge towards the development of future bio-nanomachine-based therapeutic approaches for GBM.

中文翻译：

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解释分子通讯在多形性胶质母细胞瘤生长中的作用的体素模型。

多形性胶质母细胞瘤（GBM）是人类最恶性的肿瘤，可以通过发射器和接收器细胞互斥表型的自我更新（Grow）和入侵（Go）势之间的相互作用来发展不断发展的生物纳米机械网络来定义。在这里，我们提出了由代表胶质瘤干细胞（GSCs）和胶质瘤细胞（GCs）的两个进化生物纳米机种群之间的分子介导的细胞间通讯驱动的GBM肿瘤生长的数学模型。每个亚群对肿瘤生长的贡献通过体素模型来量化，该体素模型代表了GSC的端到端细胞间通讯模型，并且在不同细胞配置的网络中神经胶质瘤细胞的侵袭性水平不断发展。相互信息，运用信息论的分析方法研究了信息的传播速度以及细胞数目和表型对通信输出和GBM生长的影响。数值模拟表明，GBM的进展与GSC和GC之间分子的更高的互信息和更高的输入信息流直接相关，从而导致肿瘤的生长速率增加。这些基本发现有助于破译肿瘤生长的机制，并有望为GBM的未来基于生物纳米机的治疗方法的开发提供新的知识。数值模拟表明，GBM的进展与GSC和GC之间分子的更高的互信息和更高的输入信息流直接相关，从而导致肿瘤的生长速率增加。这些基本发现有助于破译肿瘤生长的机制，并有望为GBM的未来基于生物纳米机的治疗方法的开发提供新的知识。数值模拟表明，GBM的进展与GSC和GC之间分子的更高的互信息和更高的输入信息流直接相关，从而导致肿瘤的生长速率增加。这些基本发现有助于破译肿瘤生长的机制，并有望为GBM的未来基于生物纳米机的治疗方法的开发提供新的知识。