Derbal Youcef
Ted Rogers School of Information Technology Management, Toronto Metropolitan University, Toronto, ON, Canada.
Cancer Inform. 2023 Feb 23;22:11769351231154679. doi: 10.1177/11769351231154679. eCollection 2023.
Genome instability of cancer cells translates into increased entropy and lower information processing capacity, leading to metabolic reprograming toward higher energy states, presumed to be aligned with a cancer growth imperative. Dubbed as the cell adaptive fitness, the proposition postulates that the coupling between cell signaling and metabolism constrains cancer evolutionary dynamics along trajectories privileged by the maintenance of metabolic sufficiency for survival. In particular, the conjecture postulates that clonal expansion becomes restricted when genetic alterations induce a sufficiently high level of disorder, that is, high entropy, in the regulatory signaling network, abrogating as a result the ability of cancer cells to successfully replicate, leading to a stage of clonal stagnation. The proposition is analyzed in the context of an in-silico model of tumor evolutionary dynamics to illustrate how cell-inherent adaptive fitness may predictably constrain clonal evolution of tumors, which would have significant implications for the design of adaptive cancer therapies.
癌细胞的基因组不稳定性转化为熵增加和信息处理能力降低，导致代谢重编程向更高能量状态发展，推测这与癌症生长的必要性相一致。该命题被称为细胞适应性适应性，假设细胞信号传导与代谢之间的耦合沿着通过维持生存所需的代谢充足性而优先的轨迹限制癌症进化动力学。特别是，该猜想假设当基因改变在调节信号网络中诱导足够高的无序水平，即高熵时，克隆扩增会受到限制，从而导致癌细胞成功复制的能力丧失，导致克隆停滞阶段。在肿瘤进化动力学的计算机模拟模型的背景下分析该命题，以说明细胞固有的适应性适应性如何可预测地限制肿瘤的克隆进化，这将对适应性癌症治疗的设计产生重大影响。
