Speaker Bio

David Odde is the Medtronic Professor of Engineering in Medicine at the University of Minnesota. Trained as a chemical engineer at the University of Minnesota and Rutgers University, Odde joined the newly created Department of Biomedical Engineering at the University of Minnesota in 1999 where he is a professor and Associate Director for Strategic Research Initiatives in the Institute for Engineering in Medicine. In his research, Odde’s group builds computer models of cellular and molecular self-assembly and force-generation-dissipation dynamics, and tests the models experimentally using digital microscopic imaging of living cells ex vivo and in engineered microenvironments. His group seeks to bring an engineering approach that uses physics-based modeling and analysis to understand, predict, and control disease outcomes (oddelab.umn.edu). Dr. Odde is an elected Fellow of the American Institute for Medical and Biological Engineering (AIMBE), the Biomedical Engineering Society (BMES), the International Academy of Medical and Biological Engineering (IAMBE), and the American Association for the Advancement of Science (AAAS) and is the Director of the Physical Sciences in Oncology Center at the University of Minnesota (psoc.umn.edu), which is focused on modeling the mechanics of cancer cell migration in biologically relevant contexts.

David Odde是美国明尼苏达大学医学工程研究所教授。他在明尼苏达大学和罗格斯大学接受过化学工程师培训，于1999年加入明尼苏达大学新成立的生物医学工程学院，担任医学工程研究所战略研究计划副主任和教授。他的团队建立了细胞和分子的自组装和力生成-耗散动力学计算模型，并使用数字显微成像技术、工程化细胞微环境、体外细胞实验等手段对模型计算结果进行了实验验证。他的团队试图建立一种基于数理模型的理解、预测和控制疾病的工程化方法。David Odde博士是美国医学与生物工程研究院（AIMBE）、生物医学工程学会（BMES）、国际医学与生物工程学学会（IAMBE）和美国科学促进协会（AAAS）等学术机构的院士或会士，也是明尼苏达大学肿瘤学中心的物理科学主任。

Abstract

Glioblastoma remains a deadly cancer driven by invasion of tumor cells into the brain. Transcriptomic analyses have revealed distinct molecular subtypes, but mechanistic and targetable differences that explain clinical differences are not clear. Using a state-of-the-art immunocompetent mouse model for glioblastoma – where tumors are induced by injection of plasmids containing human glioblastoma subtype-defining genetic drivers in a wild-type background – we found that, as predicted by the motor-clutch model for cell migration (Klank et al., Cell Rep, 2017), mesenchymal glioma cells are more spread, generate larger traction forces, and migrate faster in brain tissue compared to proneural cells. Despite their fast migration and comparable proliferation rate in vitro, mice with mesenchymal tumors live longer than mice with proneural tumors, which was correlated with an immune response in the mesenchymal mice that included T cell-mediated killing of cancer cells, similar to human tumors. Thus, mesenchymal tumors have aggressive migration, but are relatively immunologically ‘hot’ which suppresses net proliferation, features which are captured by our Brownian Dynamics tumor simulator (Klank et al., Conv Sci Phys Oncol, 2018). These two features counteract each other and may explain the lack of a strong survival difference between subtypes clinically, while also opening up new opportunities for subtype-specific therapies.