Defining bone ecosystem effects on metastatic prostate cancer evolution and treatment response using an integrated mathematical modeling approach
List of Collaborating Institutions
H. Lee Moffitt Cancer Center & Research Institute
Bone metastatic prostate cancer (mPCa) is currently an incurable disease. While standard of care treatments (androgen deprivation therapy-ADT, chemotherapy) are initially effective, this heterogeneous disease often evolves to become resistant, thus representing a major clinical challenge. Our group also demonstrates that the bone ecosystem contributes to the emergence of resistant mPCa but how the ecosystem in turn, impacts the efficacy of standard of care treatment represents a major gap in our knowledge. Biology driven mathematical models offer a novel and effective means with which to address these complex issues since cancer evolution and bone ecosystem responses to applied therapies can be rapidly tested, optimized for efficacy to delay the onset of resistant disease, and subsequently, validated experimentally. Using empirical data, we will generate an agent-based mathematical model to describe the interactions of heterogeneous mPCa cells with the surrounding bone microenvironment. In silico, we will test the effect of standard of care treatments ADT (Lupron) and chemotherapy (docetaxel) on the growth of cancer over time. The model can identify the impact of these treatments on mPCa cells but also the role of other bone cell types such as, mesenchymal stromal cells (MSCs) in disease progression. Based on this rationale, we hypothesize that experimentally powered HCAs can be used to dissect the bone ecosystem effects on mPCa evolution and optimize treatment strategies so as to prevent the emergence of resistant disease. To test this hypothesis, we propose three interdisciplinary aims. In Aim 1, human prostate cancer cell line (VCaP and LAPC4) growth parameters will power a hybrid cellular automaton (HCA) agent-based mathematical model of heterogeneous mPCa in bone. The response of the model to standard of care therapy (ADT and or docetaxel) will be studied and results validated in vivo. In Aim 2, we will explore the role of the bone ecosystem, specifically MSCs, in controlling the emergence of resistance to standard of care treatments. Human data will be used to assess the clinical applicability of the eco-evolutionary HCA. In Aim 3, evolutionary algorithms (EA) will be used to guide the adaptive application of standard of care therapy. Our innovative studies will; 1) generate a robust mathematical eco-evolutionary model of bone mPCa that can be used to dissect the role of the bone microenvironment in the emergence of resistance, 2) identify the effects of standard of care therapies on heterogeneous cancer cells and the bone ecosystem and, 3) allow for the rapid determination of optimized adaptive therapies that take into account the contributions of the bone ecosystem. We believe the proposed studies will significantly impact the way treatments are applied to men diagnosed with bone mPCa and ultimately improve their overall survival.
Back To Top
Conor C. Lynch, Ph.D.
Conor C. Lynch, Ph.D. is currently an Assoc. Member/Professor in the Tumor Biology Department at the Moffitt Cancer Center. His primary research interest focuses on skeletal malignancies including metastatic prostate cancer. The majority of men that succumb to prostate cancer will have evidence of bone metastatic castrate resistant disease. In collaboration with the clinicians and modelers in Genitourinary Oncology and the Integrated Mathematical Oncology Department at the Moffitt Cancer Center, his interdisciplinary team is focused on identifying the molecular mechanisms governing cancer-bone cross talk. To this end, his lab incorporates a number of pre-clinical animal models that recapitulate the pathophysiology of human prostate to bone metastasis and has extensive experience in bone imaging and in bone histology/histomorphometry. The major focus of this project is understanding how the bone ecosystem, specifically bone marrow mesenchymal stromal cells, contribute to the selection of drug resistant prostate cancer and how mathematical modeling can be integrated and used in a predictive manner to prevent the evolution of castrate resistant disease.
David Basanta, Ph.D.
David Basanta, Ph.D. is an Associate Member/Professor at the Integrated Mathematical Oncology department at the Moffitt Cancer Center. His research focus on the ecological and evolutionary dynamics that drive cancer progression and the emergence of treatment resistance. Together with the Lynch lab, Dr. Basanta and colleagues have developed integrated mathematical models that incorporate key players and molecules involved in bone homeostasis, this capturing the basic elements of bone ecology. This platform that can be used to study how bone metastatic prostate cancer cells can take advantage of the bone environment to grow and evolve. Importantly, it will allow us to understand how different prostate cancer cell phenotypes are selected for under a number of bone environments and thus help us understand the evolutionary dynamics that govern the tumor. In this project we will continue this work with the aim to elucidate mesenchymal stromal cell’s role in this process.
Back To Top