Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

Molecular signaling network complexity is correlated with cancer patient survivability

Dylan Breitkreutz, Lynn Hlatky, Edward Rietman and Jack A. Tuszynski
Proceedings of the National Academy of Sciences of the United States of America
Vol. 109, No. 23 (June 5, 2012), pp. 9209-9212
Stable URL: http://www.jstor.org/stable/41603076
Page Count: 4
  • Read Online (Free)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
Preview not available

Abstract

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 (R² = 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.

Page Thumbnails

  • Thumbnail: Page 
[9209]
    [9209]
  • Thumbnail: Page 
9210
    9210
  • Thumbnail: Page 
9211
    9211
  • Thumbnail: Page 
9212
    9212