ISCB-Asia/SCCG 2012, session on cancer genome informatics


Robert Beckman
Daiichi Sankyo Pharmaceutical Company

Next Generation Personalized Medicine Strategies Incorporating Genetic Dynamics and Single Cell Heterogeneity May Lead to Improved Outcomes

Abstract

Introduction: Cancers are heterogeneous and often genetically unstable. Current practice of personalized medicine tailors therapy to heterogeneity between cancers of the same organ type occurring within different individuals. However, it does not yet address heterogeneity at the single cell level within individual cancers or the dynamic nature of cancer, due to heritable genetic and epigenetic change, as well as transient functional changes.

We established methods for evaluating personalized medicine strategies, and compared the current personalized medicine strategy to alternatives. Current personalized medicine matches therapy to a tumor molecular profile at diagnosis and at tumor relapse or progression. This strategy focuses on the average, static, and current properties of the sample. Next-generation strategies also consider minor sub-clones, dynamics, and predicted future tumor states.

Methods: We developed a mathematical model of targeted cancer therapy incorporating genetic evolutionary dynamics and single cell heterogeneity, and examined simulated clinical outcomes (cell numbers of clones and sub-clones, projected survival). We compared the current personalized medicine strategy to 5 alternative personalized strategies. The latter strategies explicitly considered sub-clones, evolutionary dynamics, and likely future sub-clones in addition to the current predominant clone. Particular emphasis was given to the prevention of incurable, multiply resistant sub-clones.

Results: We carried out a computerized virtual clinical trial of over 3 million evaluable cancer “patients”, comparing current personalized medicine and 5 alternative strategies. While the current personalized medicine strategy was equally effective to the alternatives in 2/3 of the cases, in 1/3 of the cases alternative strategies led to improved outcomes. All alternatives tested resulted in an approximate doubling in mean and median survival compared to current personalized medicine and an increase in the apparent cure rate from 0.7% for current personalized medicine to 17-20% for alternatives. In no case was the current personalized medicine strategy superior.

Conclusions: These findings may lead to improved patient outcomes. Further, they suggest global enhancements to translational oncology research paradigms: for example, molecular characterization of incurable, multiply resistant “end states” from autopsy may be equally or more important than characterizing initial diagnostic states.

We have developed methods to evaluate alternative personalized medicine strategies. Next generation strategies may consider sub-clones, evolutionary dynamics, and predicted future states. Application of knowledge from growing molecular and empirical oncology databases may allow more informative therapeutic simulations than previously possible.

Biography

Robert Beckman, M.D. is an oncology clinical researcher and molecular biophysicist, whose goals are to develop cancer therapies and to improve the way cancer therapies are developed. He has played significant leadership roles in the development of new oncology clinical research groups at SmithKline Beecham (now Glaxo SmithKline), Centocor, Inc. (a Johnson and Johnson Company), and Merck Research Laboratories, and in 4 cross-company collaborations (SmithKline Beecham with Immunogen and with Aradigm, Centocor with Alza, and Merck with Ariad). His clinical research career spans small molecule and macromolecular therapeutics and supportive care agents targeting repair, angiogenesis, signal transduction, and developmental pathways, as well as novel technology platforms such as DNA vaccines, antibody-drug conjugates, and immunoliposomes. He has brought 16 molecules into early clinical development, 3 into late clinical development (monoclonal antibodies targeting insulin-like growth factor receptor, alpha-v integrins, and interleukin-6), and 2 to market (Hycamtin® for small cell lung cancer, and Astra Zeneca’s Casodex® for adjuvant therapy of prostate cancer), and pioneered a post-approval clinical research program for Hycamtin® in pediatric cancers, one of the first of its kind. Together with colleagues at Merck Research Laboratories, he has invented novel clinical strategies for proof of concept studies and for early and late biomarker driven clinical development which are being applied to that oncology portfolio. At Merck, he also led an interdisciplinary group to facilitate molecular and clinical data flow from Moffitt Cancer Center to Merck, in turn enabling correlation of clinical outcomes with biomarkers.

Educated at Harvard College and Harvard Medical School, Dr. Beckman did his clinical training at Stanford University and the University of Michigan, and postdoctoral work at Fox Chase Cancer Center and the Bristol Myers Squibb Pharmaceutical Research Institute. He also served on the University of Michigan Biophysics faculty, and was a Visiting Scientist in the Simons Center for Systems Biology, Institute for Advanced Study, Princeton, as well as in the Biomolecular Structure and Drug Design group at Warner Lambert/Parke Davis Pharmaceuticals. His versatile publication record, comprising approximately 90 articles and abstracts, ranges from computational chemistry to clinical oncology, emphasizing quantitative approaches. Dr. Beckman is currently Executive Director, Clinical Research Oncology, Daiichi-Sankyo Pharmaceutical Development.