Systems Biology (Methods in Molecular Biology)

(Tina Sui) #1
by Prigogine. As Prigogine states, “classical thermodynamics is an
admirable but fragmentary doctrine” [6].
This fragmentary character results from the fact that it is appli-
cable only to states of equilibrium in closed systems. It is necessary,
therefore, to establish a broader theory, comprising states of non--
equilibrium as well as those of equilibrium. Thermodynamics of
irreversible processes and open systems leads to the solution of
many problems where, as in electrochemistry, osmotic pressure,
thermodiffusion, Thomson and Peltier effects, etc., classical theory
proved to be insufficient [6].
A living complex system is thermodynamically open and is
characterized by a nonlinear dynamics, allowing it to have a history:
this means that the present behavior of the system is in part deter-
mined by its past behavior. Such a system displays both sensitivity
and resilience (robustness) with respect to the perturbations
exerted by internal and/or external stimuli. In addition, living
systems are characterized by both local and long-range interactions
(non-locality), as well as by complex interactions between mole-
cules and structures that make their determination “non-separable”
(i.e., “entangled”), according to an analogy remnant of quantum
mechanics [3].
A systems biology approach using new modeling techniques
and nonlinear mathematics is needed to investigate gene-
environment interactions and improve treatment efficacy. A
broader array of study designs will also be required, including
prospective molecular epidemiology, immune competent animal
models, and in vitro/in vivo translational research that more accu-
rately reflects the complex process of tumor initiation and
progression [7].
Systems biology approaches are helping to understand the
mechanisms of tumor progression and design more effective cancer
therapies [4].
Cancer is a disease based on malfunctioning of the system
properties of parts of biology. We hence identify it as a Systems
Biology disease. Indeed, progress in cancer research toward cancer
therapy may develop faster if cancer is not researched only in terms
of Molecular Biology but rather in terms of Systems Biology [8].
Cancer is a heterogeneous and highly robust disease that repre-
sents the worst-case scenario of entire system failure: a fail-on fault
where malfunction components are protected by mechanisms that
support robustness in normal physiology [1, 2]. It involves hijack-
ing the robustness mechanisms of the host. The survival and prolif-
eration capability of tumor cells are robustly maintained against a
range of therapies, due to intra-tumor genetic diversity, feedback
loops for multidrug resistance, tumor–host interactions [9].
What is needed is to provide a conceptual framework able to
integrate some entrenched aspects, such as complexity, hierarchical
structured levels of observation, geometrical relationships,

128 Sheyla Montero et al.

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