A Systems Approach to Understanding Tumor Specific Drug Response

Cancer is an individual disease—unique in how it develops and behaves in each patient. The emergence of revolutionary genomic 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. Dr. Pe'er's project elucidates tumor-specific molecular networks, which inappropriately tell a cell to grow and divide. In cancer, these networks go awry in various ways, arming the cancer with the ability to abnormally grow, metastasize, and evade drugs. Treatments based on understanding which components go wrong, and how these go wrong in each individual patient, will improve cancer therapeutics. Dr. Pe'er is using genomic technologies to track how tumors respond to potent drug inhibition of critical pathways. Further, she is developing cutting-edge computational machine learning algorithms to piece these data together, illuminating 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 is then piecing together general principles and patterns in drug responses. These studies are showing what drives cancers and what part of the networks should be targeted for treatment, helping Dr. Pe'er determine the best drug regime for each individual patient, informed by a model that can predict how the tumor will respond to drugs and drug combinations.