Systems Biology (Methods in Molecular Biology)

(Tina Sui) #1
from high-throughput data by statistics, the endogenous molecular-
cellular network, quantified by dynamical system, is a more ideal
framework that reveals the regulatory mechanism of cancer genesis
and progression.
Theories and hypotheses similar to the endogenous network
hypothesis have been also proposed by others. The cracks in the
cancer genetic mutation theory were also noticed and a similar
theory predicting the intrinsic inevitability of cancer was proposed
[92]. They have also been pushing along a similar qualification road
[93]. In a different study it was proposed that ionizing radiation
can give rise to similar effects through two distinct and independent
routes, genetic, and epigenetic and that phenotype is represented
by a stable attractor [94]. From the biological perspective all those
theories share the same set of considerations. One major difference
may be in quantitative formulations: To the best knowledge of the
present authors a complete and consistent framework has been
developed for the endogenous network theory. In addition, along
our quantitative development the outstanding controversy on the
adaptive landscape in evolutionary biology has been resolved [41].
More specific and related theories have also been proposed. It
was proposed that cancer is an atavistic condition that occurs when
genetic or epigenetic malfunction unlocks an ancient ‘toolkit’ of
pre-existing adaptations [95, 96]. Such a theory is clearly consistent
with the evolutionary dynamics structure embedded in the present
endogenous network theory. During last few decades there has
been a consistent effort to reveal the regulatory mechanism of
developmental process in sea urchin [36]. Such a study is another
important support to the construction of endogenous network. It
should be pointed out after many years of theoretical and experi-
mental studies, the key concepts of the endogenous network the-
ory, such as landscape and states, start to get into mainstream
biological and medical research [40, 97–100].

3.3 Quantitative
Analysis
of Endogenous
Molecular-Cellular
Network


The endogenous molecular-cellular network should be quantified
by a stochastic nonlinear dynamical system [54, 101], recent prog-
ress allows us to ignore the stochastic effects at the first step
[102, 103]. Characteristic properties of nonlinear dynamical sys-
tems declare that a distinct positive feedback loop must be existed
to maintain normal liver and HCC, in light of the assumption that
normal liver and HCC are distinct attractors of the endogenous
molecular-cellular network of liver. A vivid and graphical descrip-
tion of the dynamical system is adaptive landscape which can depict
the robustness of these attractors and the transition between the
attractors intuitively [11]. Recent progress allows us to construct
the adaptive landscape based on the endogenous molecular-cellular
network [103, 104]. A quantitative description of the endogenous
molecular-cellular network consists of a set of coupled stochastic
differential equations [54, 101], despite that we have not explicitly

238 Gaowei Wang et al.

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