Center Director: Vito Quaranta, MD

Professor of Cancer Biology,

Vanderbilt University School of Medicine

vito.quaranta@vanderbilt.edu

Go here for an interactive Program Browser.

CANCER SYSTEMS BIOLOGY

Systems Biology of Cancer is the definition of our mixed experimental and theoretical approach to studying many aspects of cancer progression, including invasion, metastasis, resistance to drugs, effects of mutations. Rather than focusing on clarifying details of a molecular or genetic pathway, or specific effects of growth or differentiation factors or proteases or drugs, we try and combine these details into a global picture that specifies overall trends in growth and progression of specific cancer cells under distinct microenvironmental conditions. Thus, we build quantitative hypotheses that translate experimental observations or datasets into computer simulations based of several mathematical modeling techniques, including ordinary or partial differential equations, cellular automata, neural networks, immersed boundary method. To test the hypotheses, we populate these models with datasets from in vitro or animal experiments, or from clinical material. The simulations make theoretical predictions on specific ways experimental variables may affect cancer progression. We then design and perform experiments to validate these predictions, and the outcome of the experimentation is used to evaluate the realism of computer simulations and possibly modify their underlying mathematics. Our group is comprised of an interdisciplinary collection of scientists, including cell and molecular biologists, mathematicians, engineers, bioengineers, bioinformaticians and computational biologists. We thrive on continued personal exchange and looking at cancer research problems through the eyes of different disciplines.

NEWS

Method may refine personalized trials for cancer therapy

Vanderbilt Universty Medical Center, REPORTER

by Melissa Stamm | Posted on Thursday, Aug. 16, 2012

      

A new tool to observe cell behavior has revealed surprising clues about how cancer cells respond to therapy, and may offer a way to further refine personalized cancer treatments. The approach, developed by investigators at Vanderbilt-Ingram Cancer Center, shows that erlotinib — a targeted therapy that acts on a growth factor receptor mutated in some lung, brain and other cancers — doesn’t simply kill tumor cells as was previously assumed. The drug also causes some tumor cells to go into a non-dividing (quiescent) state or to slow down their rate of division. This variability in cell response to the drug may be involved in cancer recurrence and drug resistance, the authors suggest. The new tool, reported Aug. 12 in Nature Methods, may offer ways to improve personalized cancer therapy by predicting tumor response and testing combinations of targeted therapies in an individual patient’s tumor. Read Full Story

  

Tyson DR, Garbett SP, Frick PL, Quaranta V. Fractional proliferation: a method to deconvolve cell population dynamics from single-cell data. Nat Methods. 2012 Aug 12. doi: 10.1038/nmeth.2138. [Epub ahead of print]

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Vanderbilt Researchers Win National Library of Medicine Award

The National Library of Medicine (NLM) has named a software program developed by Vanderbilt researchers as one of the most innovative uses of the Library’s resources.  In the national competition, the Library selected GLAD4U—Gene List Automatically Derived for You—as one of five winners.  Jerome Jourquin, Bing Zhang, and Dexter Duncan, from the Department of Biomedical Informatics, developed the free, web-based software, which helps users answer such questions as “Which genes are related to breast cancer?”  The winners of the challenge,  “Show off Your Apps: Innovative Uses of NLM Information,” presented their findings in Washington, D.C., at an awards ceremony where White House Chief Technology Officer Aneesh Chopra presented the award.  The presentations were broadcast live and can be viewed at http://videocast.nih.gov/Summary.asp?File=16948.

Contacts:

NLM: Shana Potash, NLM Office of Communications and Public Liaison, potashs@mail.nlm.nih.gov or (301) 594-7526.

Vanderbilt: Dr. Bing Zhang, Department of Biomedical Informatics, bing.zhang@vanderbilt.edu or (615) 936-0090.

National Library of Medicine (NLM):

www.nlm.nih.gov/

GLAD4U:

http://bioinfo.vanderbilt.edu/glad4u

Zhang Lab:

http://bioinfo.vanderbilt.edu/zhanglab/