Pancreatic Neuroendocrine Tumors (PNETs) are a rare but clinically important form of cancer. Because many PNETs grow silently and are therefore frequently diagnosed at a late stage, approximately 65% of patients present with unresectable or metastatic disease. As a result, these patients have a poor prognosis and a median survival time of 24 months with limited treatment options.
Dr. Chester Chamberlain, Assistant Professional Researcher of Diabetes Center at University of California San Francisco, presented the following seminar at last month’s Molecular Med Tri-Conference. He shared how he utilized the Bina secondary and tertiary analysis software to identify potential PNET targets and biomarkers, which can be used to discover novel treatments, predict treatment response and inform disease progression. Dr. Chamberlain also presented his plan for conducting further NGS analysis to identify synthetic lethal interactions in PNET and predict drug efficacy in a patient-derived xenograft model of PNET.