COMPLEXITY OF MOLECULAR SIGNALING NETWORKS FOR VARIOUS TYPES OF CANCER AND NEUROLOGICAL DISEASES CORRELATES WITH PATIENT SURVIVABILITY

摘要

As the population ages, the number of those affected by both cancer and neurode-generative diseases will continue to increase. In order to offset the social, economic, and personal destruction that these diseases cause new methods of analyzing the disease states and identifying potential drug targets are becoming imperative for the treatment of these diseases. We had previously studied the correlation between cancer survival statistics and cancer pathway network properties, specifically the degree-entropy, and found that there was a correlation between degree-entropy and 5-year survival statistics. Additionally, we used the betweenness centrality measure to identify potential protein targets for new drugs. Recently, we examined other network properties for the cancer pathways, specifically relative automorphism group size and cyclomatic number. Furthermore, we extended the same strategy of network analysis to neurodegenerative conditions. As with the cancer pathways, we observed a correlation between the complexity of the networks with the mortality of patients after diagnosis, and identified potential target proteins.