  Molecular signaling networks are believed to determine cancer robustness.
Although cancer patient survivability was reported to correlate with the
heterogeneous connectivity of the signaling networks inspired by theoretical
studies on the increase of network robustness due to the heterogeneous
connectivity, other theoretical and data analytic studies suggest an
alternative explanation: the impact of modular organization of networks on
biological robustness or adaptation to changing environments. In this study,
thus, we evaluate whether the modularity--robustness hypothesis is applicable
to cancer using network analysis. We focus on 14 specific cancer types whose
molecular signaling networks are available in databases, and show that modular
organization of cancer signaling networks is associated with the patient
survival rate. In particular, the cancers with less modular signaling networks
are more curable. This result is consistent with a prediction from the
modularity--robustness hypothesis. Furthermore, we show that the network
modularity is a better descriptor of the patient survival rate than the
heterogeneous connectivity. However, these results do not contradict the
importance of the heterogeneous connectivity. Rather, they provide new and
different insights into the relationship between cellular networks and cancer
behaviors. Despite several limitations of data analysis, these findings enhance
our understanding of adaptive and evolutionary mechanisms of cancer cells.
