Endogenous Molecular-cellular Network Theory And Its Application In Hepatocellular Carcinoma (HCC)

One of the most important tasks and challenges in molecular biology is to reveal the underlying molecular basis of biological observations.This thesis studies the underlying molecular basis of hepatocellular carcinoma(HCC)from a quantitative and systematic point of view.In particular,this thesis explores some key features of genetic mutations in HCC and the potential strategy to cure or relieve HCC.Endogenous molecular-cellular network theory has been used in this thesis to address these issues.Firstly,a core endogenous network for hepatocyte was established according to the theory and accumulated knowledge of molecular biology.Then,the core network was quantified and analyzed using a nonlinear dynamical system.The results show that two robust stable states of the network reproduce the main known features of normal hepatocyte and cancerous hepatocyte at both modular and molecular levels.Therefore,the genesis and development of HCC can be viewed as transitions from normal cell state to cancer cell state,which provide a new perspective to understand cancer.In light of the present theory and model,probable genetic mutations in HCC were predicted,which explain a few key features of genetic mutation patterns in HCC.Moreover,as most of the proteins and interactions in the network are evolutionarily conserved,the logical inference that the genetic mutation pattern in HCC can be applied to other cancers was validated.A further testable prediction that there are non-random genetic mutations in normal tissue was obtained.These results indicated that the present theory and model provide a way to understand and predict genetic mutations in cancers.Then,we address the issue of the molecular basis to maintain normal hepatocyte and cancerous hepatocyte,and the issue of the potential strategy to cure or relieve HCC.The model reveals that specific positive feedback loops are responsible for the maintenance of normal hepatocyte and cancerous hepatocyte.Regulating the positive feedback loops directly or indirectly provides potential strategies to cure or relieve HCC.Specifically,inhibiting proliferation and inflammation related positive feedback loops,and simultaneously inducing liver-specific positive feedback loop is predicated as the potential strategy.And continuous inhibition and induction are not required to maintain normal hepatocyte.In addition,the model can be used to design specific cure strategies according to the specific genetic mutations in individual.Other issues,such as cancer epidemiology,cancer prevention and diagnosis can also be discussed in the present theory and model.In conclusion,the application of endogenous network theory on cancer provides a new perspective to understand cancer,a set of new insights on understanding cancer genesis,and on strategies for cancer cure was provided.The novelty of this thesis includes that we provided a new framework to understand cancer and studied the dynamical process of hepatocarcinogenesis from the point of view of systems biology and quantitative biology.According to the established model,we provided a new method to predict the mutation regularity in normal hepatocyte and cancerous hepatocyte.We also establshed a computational framework to predict potential targets to regress or relieve HCC.