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Evolutionary Dynamics in Cancer Therapy

Overview | Executive Summary | Agenda

Overview

meeting report

Download Workshop Executive Summary, Agenda, and Participants List

NCI Physical Sciences-Oncology Centers (PS-OC) Strategic Workshop

May 22, 2012

Bethesda North Marriott Hotel & Conference Center
North Bethesda, Maryland

Office of Physical Sciences-Oncology
National Cancer Institute
National Institutes of Health
U.S. Department of Health and Human Services

Executive Summary

The National Cancer Institute (NCI) Office of Physical Sciences – Oncology (OPSO) launched the Physical Sciences – Oncology Centers (PS-OC) Program in 2009. The premise of the PS-OC Program is to bring a novel “physical sciences perspective” to cancer by forming teams of physical scientists and cancer researchers to work closely together to advance our understanding of cancer. In May 2012, the OPSO convened a series of two workshops to reflect on progress made applying perspectives from evolution and evolutionary theory to the understanding of cancer and identify problems in cancer research that would benefit new or continued scientific efforts from these approaches. The second Strategic Workshop in the series – “Evolutionary Dynamics in Cancer Therapy” – aimed to exploit physical sciences and evolutionary dynamics perspectives from evolutionary biology, computational biology, and control engineering to identify new tools and therapeutic approaches to advance the treatment and control of cancer.

Participants of this Strategic Workshop included experts from oncology, evolutionary biology, and physical sciences to explore the view that cancer is a heterogeneous and adaptive disease that must be examined as a dynamic system across all length and time scales. Presentations focused on physical sciences tools and approaches that use evolutionary dynamics to model and predict the response of dynamic systems to perturbations. Key highlights included predictive models and optimization control theory tools that may aid in understanding the heterogeneity and dynamics of tumor cells or patient response during cancer progression and treatment. Advances in these approaches have potential to impact design of drug dosing schedules and inform adaptive clinical trials. Roundtable discussions identified both challenges limiting convergence of evolutionary dynamics, physical sciences, and oncology as well as areas in cancer research that can benefit from physical sciences approaches using evolutionary dynamics.

Key findings and ideas generated by workshop participants included:

Use optimal control theory and predictive models to apply concepts from evolutionary dynamics to treat and control cancer

  • Control theory models derived from mathematical descriptions of patient response to treatments can potentially be used to design therapy schedules to minimize the development of drug resistance.
  • Personalization for individual patients could be achieved by the application of adaptive therapy that predicts future doses based on real-time measurements resulting in a more controlled patient response.
  • Model quality is increased by information such as drug toxicity, pharmacokinetics, and evolutionary dynamics of the cell population.
  • Virtual patient models derived from medical imaging techniques could be used in combination with these control theory models to monitor patient specific response to therapy.

Control of “phenotypic equilibrium” in cancer

  • Results from single cell analysis suggest that tumors can display phenotypic equilibrium, where tumor cells switch between two phenotypes to reach a steady-state equilibrium of population heterogeneity after a perturbation.
  • How phenotypic equilibrium is established remains unclear. Preliminary results suggest that glioblastoma multiforme cell phenotype conversions restore equilibrium faster than the cell cycle (1-3 days), indicating an intracellular mechanism that recognizes the heterogeneity of the population.
  • Information about phenotypic equilibrium could be used to predict efficacy for therapeutic dosing schedules.

Development of therapeutic methods based on evolutionary dynamics – metronomics and double bind therapies

  • Drug resistance in cancer cells results from the stepwise acquisition of adaptive diversity in response to selection pressure applied by drug therapy. From this basic tenet of Darwinian evolution, it should be possible to develop therapies that anticipate this evolution and create double bind situations that are lethal to evolving populations of cells.
  • Low-dose, high-frequency metronomic therapy, rather than today’s standard high-dose, low-frequency therapies, may represent a new approach to more effectively treat cancer without triggering the development of resistance. Measurements of the kinetics of phenotype switching between resistant and sensitive phenotypes can be used to predict the efficacy of a given metronomic dosing regimen.

Challenges limiting convergence of physical sciences and evolutionary dynamics with cancer research

  • Lack of methods to characterize heterogeneity in real-time that could be incorporated into predictive models.
  • Require improved integration of imaging tools and biomarkers with control theory models to determine categorization of patient response.
  • Lack of awareness of different predictive control theory modeling techniques within the clinical community.

 

Agenda

Meeting Objectives

The NCI’s goal in this strategic workshop is to explore the research opportunities at the intersection of the physical sciences and cancer biology by bringing physical sciences perspectives from evolutionary dynamics, computational biology, and control engineering to enhance knowledge of cancer therapy and advance physical sciences tools and approaches for adaptive clinical trial design.

From the perspective of both the physical and biological sciences, the strategic workshop aims are to:

  • Determine the “state of science” of applying evolutionary dynamics to cancer therapy in terms of our current understanding of cancer at all length and time scales.
  • Identify specific critical questions in cancer therapy and clinical trial design that can be addressed by looking at cancer as a complex adaptive system using an evolutionary perspective and physical sciences tools and approaches.
  • Identify new tools and advancing technologies from evolutionary biology, physical sciences, and engineering that if available will provide new insights in the development of adaptive clinical trials.
  • Offer guidance on how, through leadership and utilization of existing and new research support mechanisms, the NCI can best engage the broader communities of physical scientists to address key questions in cancer.

Outcomes

The conversations that comprise this strategic workshop, including brainstorming sessions, presentations, and roundtable discussions will be captured in a report that will be available on the NCI Office of Physical Sciences – Oncology website. In addition, input from the meeting will be used to inform new research directions and mechanisms that will hopefully energize and advance this critical field.

Synopsis

Cancer is a heterogeneous and adaptive disease that must be examined as a dynamic system across all length and time scales. New physical sciences tool and approaches use evolutionary dynamics to model the response of tumor cells to therapy and predict dose schedules to prevent the onset of resistance. Continued advances in these techniques have potential to impact design of drug dosing and schedules in clinical trials and inform adaptive clinical trials of patient response to treatment. The mission of NCI’s Office of Physical Sciences-Oncology is to explore new and innovative approaches to better understand and control cancer by enabling the convergence of the physical sciences with cancer biology. To determine the “state of science” in applying physical sciences tools and approaches to cancer therapy, the NCI Office of Physical Sciences – Oncology will convene a meeting of experts from multiple disciplines, including evolutionary biology, physical sciences, and cancer biology, at this strategic workshop to identify key questions and approaches that could open new avenues in cancer research.

8:00 a.m. - 8:15 a.m. Opening Remarks and Introductions
Nicole M. Moore, Sc.D.
Office of Physical Sciences-Oncology
Center for Strategic Scientific Initiatives
National Cancer Institute, NIH
8:15 a.m. - 8:30 a.m. A Clinical Perspective: Integrating Physical Sciences Approaches and
Evolutionary Dynamics With Cancer Therapy
Louis M. Weiner, M.D. Director
Lombardi Comprehensive Cancer Center
Georgetown University Medical Center
8:30 a.m. - 9:00 a.m. Introduction to the Current State-of-the-Art Clinical Trials
Donald A. Berry, Ph.D. Professor
Department of Biostatistics
The University of Texas MD Anderson Cancer Center
9:00 a.m. - 9:40 a.m. Keynote Presentation: Engineering Drug Dosing in Dynamic Biological
Systems
David J. Balaban, Ph.D. Vice President
Research and Development Informatics
Amgen Inc.
9:40 a.m. - 10:00 a.m. Break
10:00 a.m. - 10:45 a.m. Panel: Using Physical Sciences Approaches to Understand Therapeutic
Delivery and Resistance in Cancer (15 minutes per speaker) Franziska Michor, Ph.D.
Associate Professor
Dana-Farber Cancer Institute
Harvard School of Public Health

Thea D. Tlsty, Ph.D.
Professor of Pathology
University of California, San Francisco

Jessie L-S Au, Pharm.D., Ph.D.
Distinguished University Professor College of Pharmacy
The Ohio State University

David J. Balaban, Ph.D.*
Vice President
Research and Development Informatics
Amgen Inc.
10:45 a.m. - 11:15 a.m. Q&A and Discussion With Panel
Moderator: Barton A. Kamen, M.D., Ph.D.
American Cancer Society Professor
Robert Wood Johnson Medical School (volunteer)
11:15 a.m. - 11:55 a.m. Keynote Presentation: Quantifying the Time Scale of Patient Response With
Physical Sciences Approaches
James R. Heath, Ph.D. Elizabeth W. Gilloon Professor
Professor of Chemistry
California Institute of Technology
11:55 a.m. - 12:25 p.m. Lunch Break
12:25 p.m. - 12:55 p.m. Panel: Quantifying and Predicting Patient Response With Physical Sciences and Evolutionary Approaches (15 minutes per speaker)

Antonio Tito Fojo, M.D., Ph.D.
Head
Experimental Therapeutics Section
Senior Investigator
National Cancer Institute, NIH

Kristin R. Swanson, Ph.D.
James D. Murray Endowed Chair of Applied Mathematics in Neuropathology
Department of Pathology
University of Washington

James R. Heath, Ph.D.* Elizabeth W. Gilloon
Professor
Professor of Chemistry
California Institute of Technology
12:55 p.m. - 1:25 p.m. Q&A and Discussion With Panel
Moderator:   Shelley Hwang, M.D., M.P.H.
Chief, Breast Surgery-Surgical Oncology
Professor of Surgery
Duke University Medical Center
1:25 p.m. - 1:55 p.m. Roundtable Discussion: What advances in physical science approaches should be the focus of future research? What are the barriers to translating physical sciences approaches?
1:55 p.m. - 2:20 p.m. Report Out From Roundtables
2:20 p.m. - 2:40 p.m. Break
2:40 p.m. - 3:25 p.m. Panel: Control Theory and Bioinformatics of Adaptive or Evolving Systems
(15 minutes per speaker)

Robert Clarke, Ph.D., D.Sc.
Dean for Research
Georgetown University Medical Center

Stuart Horswell, M.Math.
Bioinformatics and Biostatistics Group Cancer Research UK
London Research Institute

Robert S. Parker, Ph.D.
Associate Professor and Graduate Coordinator
Department of Chemical and Petroleum Engineering
University of Pittsburgh
3:25 p.m. - 3:55 p.m. Q&A and Discussion With Panel
Moderator: Jonathan D. Licht, M.D.
Johanna Dobe Professor and Chief
Division of Hematology and Oncology
Feinberg School of Medicine
Northwestern University
3:55 p.m. - 4:40 p.m. Roundtable Discussions: Identify “Big” questions in cancer therapy that could be addressed using physical sciences and evolutionary dynamics approaches and discuss ways to integrate physical sciences approaches into cancer therapy.
4:40 p.m. - 5:00 p.m. Report Out From Roundtables
5:00 p.m. - 5:10 p.m. Concluding Remarks
Nicole M. Moore, Sc.D.
Office of Physical Sciences-Oncology Center for Strategic Scientific Initiatives
National Cancer Institute, NIH