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论细胞与癌症生物学中的整体方法:动态细胞网络的非线性、复杂性和准确定性

On the holistic approach in cellular and cancer biology: nonlinearity, complexity, and quasi-determinism of the dynamic cellular network.

作者信息

Waliszewski P, Molski M, Konarski J

机构信息

Department of Surgery, University Medical School, Poznan, Poland.

出版信息

J Surg Oncol. 1998 Jun;68(2):70-8. doi: 10.1002/(sici)1096-9098(199806)68:2<70::aid-jso2>3.0.co;2-h.

Abstract

A keystone of the molecular reductionist approach to cellular biology is a specific deductive strategy relating genotype to phenotype-two distinct categories. This relationship is based on the assumption that the intermediary cellular network of actively transcribed genes and their regulatory elements is deterministic (i.e., a link between expression of a gene and a phenotypic trait can always be identified, and evolution of the network in time is predetermined). However, experimental data suggest that the relationship between genotype and phenotype is nonbijective (i.e., a gene can contribute to the emergence of more than just one phenotypic trait or a phenotypic trait can be determined by expression of several genes). This implies nonlinearity (i.e., lack of the proportional relationship between input and the outcome), complexity (i.e. emergence of the hierarchical network of multiple cross-interacting elements that is sensitive to initial conditions, possesses multiple equilibria, organizes spontaneously into different morphological patterns, and is controlled in dispersed rather than centralized manner), and quasi-determinism (i.e., coexistence of deterministic and nondeterministic events) of the network. Nonlinearity within the space of the cellular molecular events underlies the existence of a fractal structure within a number of metabolic processes, and patterns of tissue growth, which is measured experimentally as a fractal dimension. Because of its complexity, the same phenotype can be associated with a number of alternative sequences of cellular events. Moreover, the primary cause initiating phenotypic evolution of cells such as malignant transformation can be favored probabilistically, but not identified unequivocally. Thermodynamic fluctuations of energy rather than gene mutations, the material traits of the fluctuations alter both the molecular and informational structure of the network. Then, the interplay between deterministic chaos, complexity, self-organization, and natural selection drives formation of malignant phenotype. This concept offers a novel perspective for investigation of tumorigenesis without invalidating current molecular findings. The essay integrates the ideas of the sciences of complexity in a biological context.

摘要

细胞生物学分子还原论方法的一个关键是一种将基因型与表型这两个不同类别联系起来的特定演绎策略。这种关系基于这样一种假设,即由活跃转录基因及其调控元件构成的细胞中间网络是确定性的(也就是说,基因表达与表型特征之间的联系总能被识别出来,并且网络随时间的演化是预先确定的)。然而,实验数据表明基因型与表型之间的关系是非双射的(即一个基因可能促成不止一种表型特征的出现,或者一种表型特征可能由多个基因的表达所决定)。这意味着网络具有非线性(即输入与结果之间缺乏比例关系)、复杂性(即出现多个相互交叉作用的元素组成的层次网络,该网络对初始条件敏感,具有多个平衡点,能自发组织成不同的形态模式,且以分散而非集中的方式受到控制)以及准确定性(即确定性和非确定性事件并存)。细胞分子事件空间内的非线性是许多代谢过程以及组织生长模式中存在分形结构的基础,分形结构可通过实验测量为分形维数。由于其复杂性,相同的表型可能与多种细胞事件的替代序列相关联。此外,引发细胞表型进化(如恶性转化)的主要原因可能以概率方式受到青睐,但无法明确确定。能量的热力学波动而非基因突变,这些波动的物质特性改变了网络的分子和信息结构。然后,确定性混沌、复杂性、自组织和自然选择之间的相互作用驱动了恶性表型的形成。这一概念为肿瘤发生的研究提供了一个新的视角,同时又不会使当前的分子研究结果无效。本文在生物学背景下整合了复杂性科学的思想。

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