Rational Design of Anticancer Drug Combinations - Stand Up To Cancer

Convergence Teams

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SU2C–National Science Foundation Drug Combinations Convergence Research Team:
Rational Design of Anticancer Drug Combinations with Dynamic Multi-Dimensional Input

Grant Term: September 2015–August 2019

This SU2C–National Science Foundation (NSF) Drug Combinations Convergence Research Team is focused on understanding cancer mutations that can be key to developing therapeutic responses. Normal cells have mechanisms for determining whether they will divide or not and whether they will die or not, and these mechanisms depend on the interaction of many different proteins. In cancer cells, however, the communications pathways among some of these proteins are distorted. This research project engages five biological and computational laboratories to identify how cancer cells distort this communication and how we can use combinations of drugs to help restore proper function.

Supported by:


Decades of cancer research and therapeutic development have made it clear that achieving durable control of metastatic solid tumors will usually require complex therapeutic combinations. Unfortunately, there are far too many possible combinations to test in clinical trials. Instead, new conceptual frameworks and approaches are needed to design and deliver high-order therapeutic strategies.

To address this urgent need, a collaborative team has been assembled from a broad swath of disciplines. Researchers include theoretical physicists and clinical investigators who are integrating dynamic network modeling and evolutionary analyses with systematic cell death and therapeutic resistance data. The goal is to predict the impact of complex drug combinations and to determine safe and effective dosing including how the doses should be scheduled.

More specifically, the SU2C–NSF Drug Combinations Convergence Research Team is constructing dynamic models for estrogen-receptor positive breast cancer, testing the robustness of these models, and using molecular data obtained from breast cancer patients to characterize and interpret how sensitivity and resistance to treatment evolve over time.


The top scientists and researchers on the SU2C–NSF Drug Combinations Convergence Research Team come from a variety of backgrounds and disciplines, which leads them to great insights upon collaboration. Learn more about the SU2C–NSF Drug Combinations Convergence Research Team.

Convergence Team Members

Anthony Letai, MD, PhD
Dana-Farber Cancer Institute

Reka Z. Albert, PhD
Pennsylvania State University

Raul Rabadan, PhD
Columbia University

Maurizio Scaltriti, PhD
Memorial Sloan Kettering Cancer Center

Nikhil Wagle, MD
Dana-Farber Cancer Institute/Harvard Cancer Center

Alice Lustig
Stand Up To Cancer
Project Manager


Stand Up To Cancer’s research projects are designed to foster collaborative, swift translational research. The hallmarks of these efforts include rigorous application and selection procedures, sufficient funding to allow scientists to focus on the objectives of the grant, and six-monthly reviews by senior scientists. These reviews help the investigators capitalize on the latest findings, address potential roadblocks, and collaboratively evolve as the science requires. Please click on the link to see summaries of research results so far for the SU2C–NSF Drug Combinations Convergence Research Team.



Structure-Based Control of Complex Networks With Nonlinear Dynamics
Zanudo JGT, Yang G, Albert R (2017)
PNAS Proceedings of the National Academy of Sciences of the USA 2017 114(28):7234-7239.
Systematic Functional Characterization of Resistance to P13K Inhibition in Breast Cancer
Le X, Antony R, Razavi P, et al. (2017)
Cancer Discovery 6(10):1134-1147.
P13K Pathway Regulates ER-Dependent Transcription in Breast Cancer Through the Epigenetic Regulator KMT2D
Toska E, Osmanbcyoghi HU, Castel P, et al. (2017)
Science 355(6331):1324-1330.
The Genomic Landscape of Endocrine-Resistant Advanced Breast Cancers
Cancer Cell. 2018 Sep 10;34(3):427-438.e6.
Target Control in Logical Models Using the Domain of Influence of Nodes
Yang G, Gómez Tejeda Zañudo J, Albert R. (2018)
Front Physiol. 2018 May 8;9:454.
Immune and Genomic Correlates of Response to Anti-PD-1 Immunotherapy in Glioblastoma
Zhao J, Chen AX, Gartrell RD, et al (2019)
Nat Med. 2019 Mar;25(3):462-469.
See MoreLess Publications


Cancer clinical trials allow researchers to study innovative and potentially life-saving new treatments. The goal is to find treatments that are better than what’s currently available; in fact, the therapies offered to today’s cancer patients were almost all studied and made possible by people participating in clinical trials. But many cancer clinical trials aren’t completed because not enough people take part.

At StandUpToCancer.org/ClinicalTrials, you’ll find information and answers to common questions about clinical trials. Learn more and talk to your doctor to see if a clinical trial may be the best choice for you.



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