Systems Biology (Methods in Molecular Biology)

among the agents was summarized from the well-documented gene

regulatory network and signaling transduction pathway that sug-

gest that the interactions have a solid biochemical basis

[46, 47]. We assume that the agents and interactions among the

agents form autonomous and decision-making network, which

suggests that the transmission of information is not one way and

there is no privileged causality in the network. To emphasize the

network is formed by the interactions of the endogenous cellular-

molecular agents shaped by evolution, we name the network as an

endogenous molecular-cellular network. The aim to establish a liver

endogenous network is to reveal the core regulatory mechanisms of

liver at the systemic level. Working endogenous network of HCC

has been established according to the hypothesis (Fig.1). As the

key molecular-cellular agents to regulate functional modules status

and their interactions have been documented and proved to be

conserved, it seems that the working endogenous network is repro-

ducible according to the hypothesis.

It is necessary to discuss the gaps between the working endog-

enous network of the liver and the real liver. There is no doubt that

the real liver has been greatly simplified with these assumptions

above. For example, the functional modules are far more than the

selected modules here; other molecular-cellular agents such as

microRNA, metabolites, and other proteins are not considered

explicitly in the network. Thus, the simplified and incomplete

working endogenous network is by no means the only realization,

and is open to further expansion and revision. However, we will

show later that it is one of the simplest variants which may repro-

duce the main features of normal liver tissue and HCC tissue at

both the modular and molecular levels. Moreover, we will show

that solid predications can be reached by careful analysis even in this

case of partial knowledge.

2.3 Quantification
of Endogenous
Network

The quantitative description of the core endogenous molecular-

cellular network consists of a set of coupled differential equations

[48, 49]. In Fig.1, we use CyclinD-CDK4/6 as an example to show

how to obtain the differentiation equations. Cyclin D-CDK4/6 was

upregulated by transcription factor E2F and Myc, while it was down-

regulatedbyC/EBPα,p21,andGSK-3β. First, we assume the

dynamical equation for the concentration or activity of CyclinD-

CDK4/6 under the influence of the protein E2F, Myc, C/EBPα,

p21, and GSK-3βtakes the form in Eq.1 [48–51]:

dCyclinD‐CDK4= 6 ðÞt

dt

¼fðÞE2F;Myc;C=EBPα;p21;GSK‐ 3 β



CyclinD‐CDK4= 6

τcyclinD‐CDK4= 6

ð 1 Þ

222 Gaowei Wang et al.