Pancreatic cancer is a challenging disease with 5-year survival rates of ~10%. One contributing factor to these outcomes is that there are few biomarkers to guide chemotherapy decisions. We propose to discover predictive biomarkers of chemotherapy sensitivity by applying (a) first regulatory network and (b) then master regulator analysis to the annotated molecular-clinical dataset in the Pancreatic Cancer Action Network SPARK database. Regulatory network and master regulator analysis are complementary techniques that permit the generation of a reverse-engineered transcriptional network for a given tissue type and then the inference of critical protein signaling nodes – termed master regulators – from that network. 

About the Speaker

Dr. Basil Bakir is a clinical fellow in medical oncology at NewYork-Presbyterian/Columbia University Irving Medical Center. He completed his MSTP at the Perelman School of Medicine at the University of Pennsylvania and then internal medicine residency at The Johns Hopkins Hospital. After starting medical oncology fellowship, he joined the laboratory of Dr. Ken Olive and focuses clinically on gastrointestinal cancers.