Sang Mengmeng, Rice Shawn, Jiang Libo, Liu Xin, Gragnoli Claudia, Belani Chandra P, Wu Rongling
Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
Penn State Hershey Cancer Institute, Penn College of Medicine, Hershey, PA 17033 USA.
Comput Struct Biotechnol J. 2019 Nov 30;18:45-51. doi: 10.1016/j.csbj.2019.11.009. eCollection 2020.
Intratumoral heterogeneity (ITH) has been regarded as a key cause of the failure and resistance of cancer therapy, but how it behaves and functions remains unclear. Advances in single-cell analysis have facilitated the collection of a massive amount of data about genetic and molecular states of individual cancer cells, providing a fuel to dissect the mechanistic organization of ITH at the molecular, metabolic and positional level. Taking advantage of these data, we propose a computational model to rewire up a topological network of cell-cell interdependences and interactions that operate within a tumor mass. The model is grounded on the premise of game theory that each interactive cell (player) strives to maximize its fitness by pursuing a "rational self-interest" strategy, war or peace, in a way that senses and alters other cells to respond properly. By integrating this idea with genome-wide association studies for intratumoral cells, the model is equipped with a capacity to visualize, annotate and quantify how somatic mutations mediate ITH and the network of intratumoral interactions. Taken together, the model provides a topological flow by which cancer cells within a tumor cooperate or compete with each other to downstream pathogenesis. This topological flow can be potentially used as a blueprint for genetically intervening the pattern and strength of cell-cell interactions towards cancer control.
肿瘤内异质性（ITH）被认为是癌症治疗失败和耐药的关键原因，但其表现和功能仍不清楚。单细胞分析的进展促进了关于单个癌细胞遗传和分子状态的大量数据的收集，为在分子、代谢和位置水平剖析ITH的机制组织提供了助力。利用这些数据，我们提出了一个计算模型，以重新构建肿瘤块内细胞间相互依存和相互作用的拓扑网络。该模型基于博弈论的前提，即每个相互作用的细胞（参与者）通过追求“理性自利”策略（战争或和平）来努力最大化其适应性，以一种感知并改变其他细胞以做出适当反应的方式。通过将这一理念与肿瘤内细胞的全基因组关联研究相结合，该模型具备了可视化、注释和量化体细胞突变如何介导ITH以及肿瘤内相互作用网络的能力。综上所述，该模型提供了一种拓扑流程，肿瘤内的癌细胞通过这种流程相互协作或竞争，进而导致下游发病机制。这种拓扑流程有可能被用作一种蓝图，用于对细胞间相互作用的模式和强度进行基因干预以实现癌症控制。
