Evolutionary dynamics of cancer in response to targeted combination therapy

Author:

Bozic Ivana12,Reiter Johannes G3,Allen Benjamin14,Antal Tibor5,Chatterjee Krishnendu3,Shah Preya6,Moon Yo Sup6,Yaqubie Amin7,Kelly Nicole7,Le Dung T8,Lipson Evan J8,Chapman Paul B7,Diaz Luis A9,Vogelstein Bert9,Nowak Martin A1210

Affiliation:

1. Program for Evolutionary Dynamics, Harvard University, Cambridge, United States

2. Department of Mathematics, Harvard University, Cambridge, United States

3. Institute of Science and Technology Austria, Klosterneuburg, Austria

4. Department of Mathematics, Emmanuel College, Boston, United States

5. School of Mathematics, Edinburgh University, Edinburgh, United Kingdom

6. Harvard College, Cambridge, United States

7. Memorial Sloan-Kettering Cancer Center, New York, United States

8. Department of Medical Oncology, Johns Hopkins University School of Medicine; The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, United States

9. Ludwig Center for Cancer Genetics and Therapeutics, Howard Hughes Medical Institute, Johns Hopkins Kimmel Cancer Center, Baltimore, United States

10. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States

Abstract

In solid tumors, targeted treatments can lead to dramatic regressions, but responses are often short-lived because resistant cancer cells arise. The major strategy proposed for overcoming resistance is combination therapy. We present a mathematical model describing the evolutionary dynamics of lesions in response to treatment. We first studied 20 melanoma patients receiving vemurafenib. We then applied our model to an independent set of pancreatic, colorectal, and melanoma cancer patients with metastatic disease. We find that dual therapy results in long-term disease control for most patients, if there are no single mutations that cause cross-resistance to both drugs; in patients with large disease burden, triple therapy is needed. We also find that simultaneous therapy with two drugs is much more effective than sequential therapy. Our results provide realistic expectations for the efficacy of new drug combinations and inform the design of trials for new cancer therapeutics.

Funder

Foundational Questions in Evolutionary Biology Fund

European Research Council Start Grant

FWF (The Austrian Science Fund) Grant

Microsoft Faculty Fellow Award

The John Templeton Foundation

The Danny Federici Melanoma Fund

John Figge Melanoma Fund

The Virginia and D. K. Ludwig Fund for Cancer Research

National Cancer Institute

National Institutes of Health

National Colorectal Cancer Research Alliance

European Research Council

Austrian Science Fund

Microsoft Research

John Templeton Foundation

Virginia and D.K. Ludwig Fund for Cancer Research

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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