Physical Sciences Oncology Centers (PS-OC)
David K.A. Mordecai, principal scientist/lead investigator of RiskEcon® Lab, and Visiting Scholar at Courant Institute of Mathematical Sciences, was invited to make a presentation to the Physical Sciences Oncology Center (PS-OC) at Princeton University on January 29th, 2014. Dr. Mordecai and his collaborator were subsequently invited to further present related research to the PS-OC Steering Committee on March 19th, 2014.
Both presentations, involving the evolving metabolic heterogeneity of a tumor cell population as an economic phenomenon, are related to joint work with Andrew E. Sundstrom, who had been awarded his Ph.D. in computational biology at NYU Courant Institute of Mathematical Sciences. Dr. Sundstrom’s dissertation focused upon how hypoxia arises in heterogeneous and spatially complex tumor cell populations1, and he was employed (during 2013-2014) as a Senior Research Scientist affiliated with RiskEcon® Lab at Courant Institute of Mathematical Sciences.
The PS-OC is a collaborative network of twelve leading US research institutions to which the National Cancer Institute (NCI) has awarded cooperative agreements. The participating universities include Cornell, Johns Hopkins, MIT, Princeton and Stanford.
The January 29th, 2014 presentation:
- Abstract: Certain branches of economics and ecology each address questions regarding resource allocation in terms of both absolute and relative spatial position. Corresponding and analogous game theoretic strategies of resource competition arise from location and relative proximity across populations of two or more heterogeneous agents. These game theoretic strategies offer what may be relevant and useful implications for modeling growth of normal versus oncogenically transformed cell populations related to their respective locations within the resource landscape. Sub-populations of neighboring cells compete to use locally available resources (oxygen, glucose, glutamine) via metabolic processes of production and exchange involving divergent yields in both productivity and efficiency. The scope versus scale economics of these metabolic tradeoffs, conditioned upon environmental parameters, may be expected to approximate (or at least resemble) certain dynamics of strategic life trajectories driven by tradeoffs between relative net yields in bioenergetics versus biosynthesis.
The March 19th, 2014 presentation:
- Abstract: Allocative econometric analysis of resource competition (in terms of both absolute and relative spatial position), across the evolving metabolic heterogeneity of a tumor cell population, may provide relevant and useful implications for profiling normal versus oncogenically transformed cell populations in accordance with respective metabolomic signatures. Sub-populations of neighboring cells competing for locally available metabolic resources (e.g. glucose, glutamine, oxygen) via processes of production and exchange, exhibit profiles that reflect divergent yields in both productivity and exchange. Measuring and dynamically mapping both the corresponding carrying capacities and adaptive strategies to the respective composition and relative concentrations of characteristic metabolite profiles for divergent cell populations, may further specify the role of metabolic switching mechanisms in triggering proliferative versus homeostatic cell reproduction.
- Note: Dr. Sundstrom’s dissertation coupled simulation, histological image characterization, formal verification, and adaptive high-dimensional spatial mapping, in a computational modeling framework to test certain aspects in silico, related to the inverse problem regarding initial conditions and model parameter values associated with local regions of tumor cell hypoxia.