Past Event: Oden Institute Seminar

Mathematical modeling of cancer: Integrating mathematical models of tumor growth, statistical methods and experimental and clinical data to provide insight on progression and improve treatment outcomes

John Lowengrub, Chancellor's Professor of Mathematics, Biomedical Engineering, Chemical Engineering & Materials Science Director, Interdisciplinary Graduate Program in Mathematical, Computational & Systems Biology, University of California, Irvine

Abstract

In this talk, we will show through two examples how mathematical and statistical modeling can provide insight on tumor progression that can be leveraged to improve treatment outcomes and design new therapy strategies. In the first example, we focus on chronic myeloid leukemia— a blood cancer in which there is dysregulation of maturing myeloid cells driven by a chromosomal mutation which creates the fusion gene, BCR-ABL1. Although there has been much progress in the treatment of CML by the application of tyrosine kinase inhibitors (TKI), there are still unmet clinical needs, e.g. (i) 10-15% of patients exhibit primary resistance and (ii) nearly all patients experience remission upon stopping treatment. Here, we explore how more physiologically accurate, data-driven mathematical models of CML hematopoiesis that incorporate feedback control and lineage branching can address these needs and improve treatment outcomes. In the process, we develop Bayesian methods for optimal experimental design for parameter inference. In the second example, we focus on glioblastoma (GBM), which is the most aggressive brain tumor in humans. Here, we develop highly efficient Bayesian probabilistic methods to calibrate mechanistic mathematical models using data from multimodal medical scans (MRI, FET-PET) at a single, pre-operative time point. We demonstrate how these can be used to aid in the rational design of personalized radiotherapy plans that can more efficiently target infiltrative GBM cells and provide guidance for personalized dose escalation. This is a Joint Seminar: Oden Institute for Computational Engineering and Science / Livestrong Cancer Institute / Dell Medical School (Department of Oncology) BIO John Lowengrub is a Chancellor's Professor at the University of California at Irvine with appointments in the departments of Mathematics and Biomedical Engineering. He is the inaugural director of the interdisciplinary graduate program in Mathematical, Computational and Systems Biology. Prof. Lowengrub is also a co-leader of the Systems, Pathways and Targets program at the Chao Family Comprehensive Cancer Center at UC Irvine. Prof. Lowengrub’s research interests include applied and computational mathematics, mathematical and computational biology, mathematical oncology, complex fluids and materials science. Prof. Lowengrub has published over 150 journal articles, several book chapters, and a book on multiscale modeling of cancer. Among his awards are a Sloan Fellowship, the Francois Frenkiel award by the American Physical Society, the Chancellor's award for excellence in fostering undergraduate research at UCI, and he was recently elected a fellow of the AAAS. Prof. Lowengrub holds a B.A. from Cornell University (1985) and a Ph.D. from the Courant Institute of Mathematical Sciences at New York University (1988). Note: Please join this Zoom seminar online with the "Audio Only" function (no video)