Molecular signaling network complexity is correlated with cancer patient survivability

  • Dylan Breitkreutz
    Department of Physics, University of Alberta, Edmonton, AB, CanadaT6G 2E1;
  • Lynn Hlatky
    Center of Cancer Systems Biology, St. Elizabeth’s Medical Center, Tufts University School of Medicine, Boston, MA 02135
  • Edward Rietman
    Center of Cancer Systems Biology, St. Elizabeth’s Medical Center, Tufts University School of Medicine, Boston, MA 02135
  • Jack A. Tuszynski
    Department of Physics, University of Alberta, Edmonton, AB, CanadaT6G 2E1;

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<jats:p> The 5-y survival for cancer patients after diagnosis and treatment is strongly dependent on tumor type. Prostate cancer patients have a >99% chance of survival past 5 y after diagnosis, and pancreatic patients have <6% chance of survival past 5 y. Because each cancer type has its own molecular signaling network, we asked if there are “signatures” embedded in these networks that inform us as to the 5-y survival. In other words, are there statistical metrics of the network that correlate with survival? Furthermore, if there are, can such signatures provide clues to selecting new therapeutic targets? From the Kyoto Encyclopedia of Genes and Genomes Cancer Pathway database we computed several conventional and some less conventional network statistics. In particular we found a correlation ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.7) between degree-entropy and 5-y survival based on the Surveillance Epidemiology and End Results database. This correlation suggests that cancers that have a more complex molecular pathway are more refractory than those with less complex molecular pathway. We also found potential new molecular targets for drugs by computing the betweenness—a statistical metric of the centrality of a node—for the molecular networks. </jats:p>

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