Cancer is an individual disease—unique in how it develops and behaves in each patient. The emergence of revolutionary genomics technologies, combined with increased understanding of the molecular basis underlying cancer initiation, has increased the hope that treatment will improve by becoming more targeted and individualized in nature. Pe’er’s project elucidates tumor-specific molecular networks, which are the information processing devices of cells. In cancer, these networks go awry in various ways, arming the cancer with the ability to abnormally grow, metastasize and evade drugs. Treatment that is based on understanding which components go wrong, and also how these go wrong in each individual patient, will improve cancer therapeutics. Pe’er will use genomic technologies to track how tumors respond to potent drug inhibition of critical pathways. She will develop cutting-edge computational machine learning algorithms to piece these data together and illuminate how a cell's regulatory network processes signals, and how this signal processing goes awry in cancer. By utilizing a large panel of diverse tumors in this study, she will begin to piece together general principles and patterns in drug responses. These studies should show what drives cancers and what part of the networks should be targeted for treatment. For each individual patient, she will determine the best drug regime, informed by a model that can predict how the tumor will respond to drugs and drug combinations.
Dana Pe’er, Ph.D., is assistant professor in the biological sciences department at Columbia University in New York.
Updated: April 4, 2011