面向肿瘤治疗的基因调控网络与其动力学模型

【作者】 齐金鹏；

【导师】 邵世煌；

【作者基本信息】 东华大学 ， 模式识别与智能系统， 2008， 博士

【摘要】 生命体是一个复杂系统。系统控制论等信息科学学者正把生命体看作又一类新的复杂系统与智能系统的研究目标。存储生命信息的各基因并不是孤立地发挥作用,而是通过形成“基因调控网络”这样一个复杂的系统来推动生命演化。基因调控网络期望从系统角度全面揭示基因组的功能和行为,有助于从基因组层次对生命过程进行详细的解释,并与分子层次的解释紧密联系,从而达到能系统地理解细胞功能、生命活动、解释疾病与治疗的机理等目标。作为复杂的生物系统之一,肿瘤可看作与其密切相关的P53与MDM2等基因及其信号通路所组成的复杂网络系统与运动。本文依托于生物医学相关研究,以P53等基因及其信号通路为主线,主要对肿瘤相关的基因调控网络模型及其动力学等问题进行了研究,并取得了以下方面的创新成果:完善了P53基因调控网络概念模型在已有研究工作基础上,进一步完善了P53基因调控网络概念模型。根据生物学研究,提出了删减P53-MDM2反馈调控网络等已有模型中的冗余基因节点及其调控通路,并将与肿瘤密切相关的因素添加到模型中。提出了DNA损伤下的P53基因调控网络模型基于改进的概念模型,提出了DNA损伤下的P53基因调控网络模型,给出了单细胞内部的P53等基因及其信号通路响应DNA损伤传导而产生的复杂作用关系以及动态调控过程。提出了持续离子辐射下的P53基因调控网络模型依据最新生物学研究,首次提出持续离子辐射下的P53基因调控网络模型。在持续强离子条件下,实现了单细胞内部DNA损伤生成与修复、ATM激活以及P53-MDM2反馈调控等模块。展现了细胞响应外部强刺激以及基因组损伤信号传导而启动自身抵御机制的动力学过程。给出了不同强度辐射下单细胞响应DNA损伤的动力学分析根据已有模型以及生物学相关研究,将细胞中参与动扰响应与网络调控的更多关键因素融入到模型中,进一步完善了持续离子辐射下的P53基因调控网络模型。在多剂量离子辐射下实现了更为复杂的细胞响应DNA损伤动力学过程。同时,通过仿真对不同干扰条件下细胞响应DNA损伤的能力进行了分析与动态预测,进一步阐述了复杂环境下细胞响应外部动扰的自抵御机制。提出基于肿瘤放疗的P53损伤响应网络模型基于生物医学最新研究,提出了基于肿瘤放疗的P53损伤响应网络模型,将有关肿瘤治疗的Oncogenes、ARF、Toxins等关键因素加入到模型中。模拟了在持续的强离子辐射下单细胞内部的基因组损伤随机生成、修复与传导,ATM与ARF活化,P53-MDM2反馈调控环的动态调控机制激活,以及细胞毒素凋亡等动力学过程。给出细胞响应不同强度放疗过程的动力学分析与预测完善了基于放疗的P53损伤响应网络模型,其中包括ATM与ARF协同活化模块以及基于P53-MDM2反馈调控环等部分。同时,我们通过仿真平台对肿瘤治疗的整个动力学过程进行模拟,在不同强度离子辐射以及治疗时间等条件下对细胞响应放疗作用的能力以及放疗效果进行了初步分析与动态预测。本文研究的面向肿瘤治疗的基因调控网络与动力学模型旨在揭示与肿瘤密切相关基因及其信号通路间复杂的调控关系,在基因层次上建立单细胞响应肿瘤治疗的动力学模型,为肿瘤治疗研究提供一种理论框架与系统仿真平台。我们开展了基于肿瘤治疗的基因调控网络模型研究,不但能对肿瘤相关的P53等基因组间复杂的调控信息以及肿瘤治疗过程进行解析,而且能对不同放疗强度与治疗时间下的细胞响应DNA损伤能力进行分析与预测。通过多角度展现肿瘤放疗的动态效果,在理论上对细胞响应肿瘤放疗的复杂过程进行一种抽象与简化,为肿瘤治疗相关的建模与仿真等理论研究提供一种新视角和新思路。更多还原

【Abstract】 Life is one of the most complicated system.Researchers in the fields of information and control are trying to study these organisms as a new kind of the complex system and intelligent system.All kinds of genes storing life information prompt the evolement of life through a complex network system,a gene regulatory network.The researches of the gene regulatory network are expetcted to discover the funtions and behavior of genome through systematic point of view,explain the complicated life processes at gene level in detail,and combine tightly together with the interprets at molecule level,and subsequently approach the targets for systematically explaining the cellular functions,life behaviours,and the mechanisms of illness and their therapy.As one of the complex biological system,tumor might be considered as one of the complicated network system.In this study,according to the recent biology studies related with tumor,we have made the scientific researches mainly on the modeling of gene regulatory network and their kinetics based on P53 and MDM2 genes and their signal pathways etc.The innovatitive research contributions mainly include the following contents:Improving the notional mode of P53 gene regluatory networkBased on the existing researches,we improved the notional model of P53 gene regulatory network.We cut out the redundant nodes and their regulatory pathways, and add more vital elements related tightly with tumor into our model according to the latest biology studies.Proposing a model of P53 gene regulatory network under DNA damageBased on the improved notional model,we propsed a model of P53 gene regulatory network under DNA damage,and investigated the complicated interactions and regulating kinetics among P53 genes and their signal pathways in cellular responding DNA damage.We simulated the dynamic processes of cellular self-defense mechanisms in response to the acute stimulations and genome stresses.Proposing a model of P53 gene regulatory network under continuous Ion Radiation(IR)According to the latest biology researches,we firstly proposed a model of P53 gene regulatory network under continuous IR.Under continous acute radiation,we implemented the modules of DNA damage generating and their repair,ATM activating,and P53-MDM2 feedback looper.Investigaing the abilities of cellular responding DNA damage under different IRWe improved the model of model of P53 gene regulatory network under continuous IR by adding much more elements related cellular response and network regulation.Under different IR dose domains,we realized the complicated kinentcis of cellular response DNA damage.Meanwhile,we analyzed the capabilities of cellular respons in fighting against different IR dose domains,and further investigate the self-defense mechanisms under complex circumstances. Proposing a model of P53 stress response network under radiotherapy Based on the latest biomedical researches,we proposed a model of P53 stress response network under radiotherapy,adding Oncogenes,ARE,Toxins into this model.Under continous radiation,we simulated the processes of genome damage generating,repairing and transducting,ATM and ARF activating,P53-MDM2 feedback regulating,as well as the toxins eliminating.Investigating the analyse and prediction of the cellular responding radiotherapy under different IR dose domainsWe improved the model of P53 stress response network under radiotherapy, including the cooperated activation of ATM and ARF,and the feedback looper formed by P53 and MDM2.Meanwhile,we simulated the whole process of tumor therapy under continuous IR,and further analyed the capabilities of cellular responding under different radiation time and different IR dose domains,further predicted the outcomes of tumor radiotherapy as well.In this research,we aimed to investigate the complicated regulating relationships among genes and their signal pathways related tightly with tumor therapy based on the modelling of gene regulatory network and their kinetics,build the dynamic model of cellular responding tumor therapy at sigle cell level,and to provide a theoretic framwork and simulating platform for the studies of tumor therapy further.Our researches can not only try to explain the complicated regulations among genes and their signal pathways,but also analy and predict the capabilities of cellular responding DNA damage under different circumstances.By multi-point of view,we can make a simplification for the complex process of tumor radiotherapy,and provide a novel way for theoretical research on modeling and simulating the tumor therapy.更多还原