Biology Reference
In-Depth Information
Reorganizing these findings under the coherent view of
cancer robustness will provide us with a guideline for
further research.
THEORETICALLY MOTIVATED THERAPY
STRATEGIES
Given the highly complex control systems and genetic
heterogeneity of tumors, random trials of potential targets
are not as effective as one would wish. There is a need for
theoretically motivated approaches that guide us to thera-
pies that best counter the disease. The implication of cancer
robustness is that there are specific patterns of behavior and
weakness in robust systems as well as a rational way of
controlling and fixing systems, and such general principles
also apply to cancer. Thus, there must be theoretically
motivated approaches for the prevention and treatment of
cancer.
Strategies for cancer therapy may depend upon the level
of robustness of tumors in specific patients. When robust-
ness is low and genetic heterogeneity is low, then there is
a good chance that the use of drugs with specific molecular
targets may be effective by causing a common mode
failure: a type of failure where all redundant subsystems
fail for the same reason. The example of chronic myeloid
leukemia (CML) therapy using imatinib metylate may
provide us with some insights
[47,48]
. Although this is
speculative, the dramatic effect of imatinib metylate on
early-stage CML may be due to a common mode failure,
but resistance in advanced stages may be due to heteroge-
neity. For this strategy to be effective, there must be proper
means of diagnosing the degree of intratumoral genetic
variations. Also, the most effective molecule for a target
needs to be recognized in ways that lead to identification
and optimization processes.
However, for patients with an advanced-stage cancer,
intratumoral genetic heterogeneity may be already high and
various feedback controls may be significantly upregulated.
In these cases, drugs that are effective in the early stage
may not work as expected, owing to the heterogeneous
response of tumor cells and feedbacks to compensate for
perturbations. For these cases, therapy and drug design
need a drastic shift from a single target-oriented approach
to a systems-oriented approach. Then, the question is what
approach shall be taken to target the system? There seem to
be only a few theoretically motivated countermeasures.
First, the robustness/fragility trade-off implies that
cancer cells that have gained increased robustness against
various therapies may have a point of extreme fragility.
Targeting such a point of fragility may provide dramatic
effects against the disease. The major challenge is to find
such a point of fragility. When it turns out that a cancer is
tolerant to a specific drug after its provision but is fragile to
another drug, the therapeutic strategy may be to use a series
of regimens that continue to attack the point of fragility. For
example, cancer cells that survived via evolution to
increased robustness to the first drug may have fragility to
another drug. Eventually,
ROBUSTNESS TRADE-OFFS
Systems that acquire robustness against certain perturba-
tions through either design or evolution have intrinsic
trade-offs between robustness, fragility, performance, and
resource demands. Carlson and Doyle, using simple
examples from physics and forest fires, argued that systems
which are optimized for specific perturbations are
extremely fragile against unexpected perturbations
[43,
44]
. Ceste and Doyle further argued that robustness is
a conserved quantity
[45]
. This means when robustness is
enhanced against a range of perturbations, it must then be
compensated for by fragility elsewhere, as well as
compromised
performance
and
increased
resource
demands.
Robust yet fragile trade-offs can be understood intui-
tively using the airplane example. Modern commercial
airplanes are by a great magnitude more robust against
atmospheric perturbations than the Wright flyer, which is
attributable to a sophisticated flight control system.
However, such a flight control system relies completely on
electricity. In the unthinkable event of total power failure in
which all electricity in the airplane is lost, it cannot be
controlled at all. Obviously, airplane manufacturers are
well aware of this and take all possible measures to mini-
mize such a risk. On the other hand, despite its vulnerability
against atmospheric perturbations, the Wright Flyer will
never be affected by power failure, because there is no
reliance on electricity. This extreme example illustrates
systems that are optimized for certain perturbations could
be extremely fragile against unusual perturbations. Trade-
offs are expected to exist not only between robustness and
fragility, but also between robustness and performance, and
robustness and resource demands (
Figure 24.3
). At the
same time, it should be noted that such trade-offs may hold
only under a certain condition that a system is sufficiently
optimized and has no room for optimization without trade-
offs
[46]
.
Robustness
Fragility
Performance
Resource Demands
the cancer cell clusters that
FIGURE 24.3
Robustness trade-offs.
