Research Project

Optimal control models of epithelial-mesenchymal transition for the design of pancreas cancer combination therapy


Project Name

Optimal control models of epithelial-mesenchymal transition for the design of pancreas cancer combination therapy

List of Collaborating Institutions

University of Virginia
University of Pennsylvania
University of Delaware

Project Websites

Project Description

It is increasingly clear that combination therapies are needed to improve durable response rates for recalcitrant cancers. Engineering successful combination therapy approaches may not be straightforward, however, due to a need to balance the design constraints of: i. maximally targeting the right proteins or cellular processes, and ii. minimizing drug toxicities. The goal of our Cancer Systems Biology Consortium U01 project is to develop and test a new approach for engineering combination therapy that relies on data-driven modeling to identify appropriate drug targets and process control modeling to predict drug schedules that meet the design criteria. We will deploy our approach in the context of pancreatic ductal adenocarcinoma (PDAC), which has one of the worst prognoses of any major cancer. Numerous observations suggest that the de-differentiation of epithelial-derived tumor cells to a mesenchymal state, sometimes in direct response to therapy, promotes PDAC chemoresistance. This raises the question of whether combining drugs that target the epithelial-mesenchymal transition (EMT) with conventional chemotherapy can promote overall response. Based on our preliminary data, we hypothesize that a practical number of targeted therapeutics (as few as two) can be scheduled in combination with chemotherapy to achieve this goal. The project aims are to: 1. measure the multivariate signaling dynamics that accompany transitions between the epithelial and mesenchymal states in PDAC cells in settings that recapitulate aspects of the tumor microenvironment; 2. leverage data-driven and process control modeling approaches to predict optimal scheduled combination therapy approaches for PDAC; and 3. test the effectiveness of model-predicted schedules of combination therapies. With promising preliminary data already in hand, we are able to pursue these aims in parallel. Validation of this basic approach will provide the cancer systems biology community with a new tool for designing combination therapies that can be applied in numerous oncology settings.


Matthew Lazzara, Ph.D.

Matthew Lazzara is Associate Professor of Chemical Engineering and Biomedical Engineering at the University of Virginia. Dr. Lazzara received a B.S. in Chemical Engineering with highest honors from the University of Florida and a Ph.D. in Chemical Engineering from the Massachusetts Institute of Technology, where he trained in the lab of William Deen. He remained at MIT for postdoctoral studies with Douglas Lauffenburger and was the recipient of an NIH Ruth L. Kirschstein National Research Service Award Postdoctoral Fellowship. Work in the Lazzara Lab focuses on development and application of systems biology models for the rational design of combination therapies for cancer and on fundamental studies of the spatiotemporal regulation of cell signaling. The lab’s work is funded by the NIH/National Cancer Institute, American Cancer Society, and National Science Foundation. Dr. Lazzara is a member of the editorial board of Cellular and Molecular Bioengineering and a member of the Cancer Drug Discovery peer review group for the American Cancer Society.

Ben Stanger, M.D., Ph.D.

Ben Stanger is the Hanna Wise Professor of Cancer Research and Professor of Medicine and Cell and Developmental Biology at the Perelman School of Medicine at the University of Pennsylvania, where he is also an Investigator in the Abramson Family Cancer Research Institute. Dr. Stanger earned his S.B. in Life Sciences from the Massachusetts Institute of Technology in 1988 and a combined M.D. and Ph.D. from Harvard Medical School, where he worked on mechanisms of apoptosis with Dr. Philip Leder. He then went on to complete a residency in Internal Medicine at UCSF and a fellowship in Gastroenterology at the Massachusetts General Hospital, where his postdoctoral fellowship with Dr. Douglas Melton focused on mechanisms of pancreatic development and growth. He was Instructor at Harvard Medical School from 2003-2006 until his move to the University of Pennsylvania, where his laboratory now studies cellular plasticity in the context of pancreatic cancer, liver regeneration, and diabetes.

Babatunde Ogunnaike, Ph.D.

Babatunde A. (“Tunde”) Ogunnaike is the William L. Friend Professor of Chemical Engineering at the University of Delaware. He received the B.Sc. degree in Chemical Engineering from the University of Lagos, Nigeria; the M.S. degree, in Statistics and the Ph.D. degree in Chemical Engineering both from the University of Wisconsin–Madison. He is the author or co-author of four books, including Process Dynamics, Modeling and Control, and Random Phenomena: Fundamentals of Probability and Statistics for Engineers. He is Associate Editor of Industrial and Engineering Chemistry Research. His awards include the American Institute of Chemical Engineers 1998 CAST Computing Practice Award, the 2004 University of Delaware’s College of Engineering Excellence in Teaching award, the 2007 ISA Eckman Award, and the 2008 AACC Control Engineering Practice award. He was named a fellow of the American Institute of Chemical Engineers in 2009, and elected to fellowship of the Nigerian Academy of Engineering and the US National Academy of Engineering in 2012.

Todd Bauer, M.D.

Todd Bauer is Professor of Surgery and Chief of Surgical Oncology at the University of Virginia. He received his undergraduate degree and M.D. from the University of Pennsylvania. He completed his General Surgery residency and a post-doctoral research fellowship at the Hospital of the University of Pennsylvania, followed by a fellowship in Surgical Oncology and a post-doctoral research fellowship at the University of Texas MD Anderson Cancer Center. Dr. Bauer’s clinical focus is in pancreatic, liver and biliary cancers, and he is the Leader of the UVA Cancer Center GI Translational Research Team. His laboratory has developed a human pancreatic cancer tissue bank and sophisticated mouse models using patient-derived xenografts (PDXs). The Bauer Lab has exploited these PDX models to investigate the drivers of pancreatic cancer growth, metastasis, and therapy resistance.