Department of Biotechnology, Laboratory of Bioinformatics and Control of Bioprocesses, Institute of Biological Sciences, University of Zielona Góra, Szafrana 1, 65-516 Zielona Góra, Poland.
Center for Molecular Medicine and Genetics, Department of Pathology, Wayne State University School of Medicine, Detroit, MI 48201, USA.
Int J Mol Sci. 2024 Aug 23;25(17):9163. doi: 10.3390/ijms25179163.
If one must prioritize among the vast array of contributing factors to cancer evolution, environmental-stress-mediated chromosome instability (CIN) should easily surpass individual gene mutations. CIN leads to the emergence of genomically unstable life forms, enabling them to grow dominantly within the stable life form of the host. In contrast, stochastic gene mutations play a role in aiding the growth of the cancer population, with their importance depending on the initial emergence of the new system. Furthermore, many specific gene mutations among the many available can perform this function, decreasing the clinical value of any specific gene mutation. Since these unstable life forms can respond to treatment differently than stable ones, cancer often escapes from drug treatment by forming new systems, which leads to problems during the treatment for patients. To understand how diverse factors impact CIN-mediated macroevolution and genome integrity-ensured microevolution, the concept of two-phased cancer evolution is used to reconcile some major characteristics of cancer, such as bioenergetic, unicellular, and multicellular evolution. Specifically, the spiral of life function model is proposed, which integrates major historical evolutionary innovations and conservation with information management. Unlike normal organismal evolution in the microevolutionary phase, where a given species occupies a specific location within the spiral, cancer populations are highly heterogenous at multiple levels, including epigenetic levels. Individual cells occupy different levels and positions within the spiral, leading to supersystems of mixed cellular populations that exhibit both macro and microevolution. This analysis, utilizing karyotype to define the genetic networks of the cellular system and CIN to determine the instability of the system, as well as considering gene mutation and epigenetics as modifiers of the system for information amplification and usage, explores the high evolutionary potential of cancer. It provides a new, unified understanding of cancer as a supersystem, encouraging efforts to leverage the dynamics of CIN to develop improved treatment options. Moreover, it offers a historically contingent model for organismal evolution that reconciles the roles of both evolutionary innovation and conservation through macroevolution and microevolution, respectively.
如果必须在癌症进化的众多因素中进行优先级排序，那么环境应激介导的染色体不稳定性（CIN）应该很容易超过单个基因突变。CIN 导致基因组不稳定的生命形式出现，使它们能够在宿主的稳定生命形式中占主导地位。相比之下，随机基因突变在促进癌症群体生长方面发挥作用，其重要性取决于新系统的初始出现。此外，在众多可用的特定基因突变中，许多都可以发挥这种作用，从而降低任何特定基因突变的临床价值。由于这些不稳定的生命形式对治疗的反应可能与稳定的生命形式不同，癌症经常通过形成新的系统来逃避药物治疗，这导致患者在治疗过程中出现问题。为了了解多种因素如何影响 CIN 介导的宏观进化和基因组完整性保证的微观进化，使用两阶段癌症进化的概念来调和癌症的一些主要特征，如生物能量、单细胞和多细胞进化。具体来说，提出了生命功能螺旋模型，该模型将主要的历史进化创新和保护与信息管理相结合。与微观进化阶段中给定物种占据螺旋内特定位置的正常生物体进化不同，癌症群体在多个层次上高度异质，包括表观遗传水平。单个细胞在螺旋内占据不同的层次和位置，导致混合细胞群体的超系统表现出宏观和微观进化。该分析利用核型定义细胞系统的遗传网络，利用 CIN 确定系统的不稳定性，并考虑基因突变和表观遗传学作为系统的修饰物，以放大和使用信息，探索了癌症的高进化潜力。它提供了一种新的、统一的理解癌症作为超系统的方法，鼓励利用 CIN 的动态开发改进的治疗方案。此外，它还提供了一个具有历史偶然性的生物体进化模型，通过宏观进化和微观进化分别协调进化创新和保护的作用。
