Abstract

The role of the Center for Small Animal Imaging in the Vanderbilt University Institute of imaging Science in this P50 will be to develop and apply multi-modality imaging technologies for the comprehensive evaluation and characterization of the evolving minor microenvironment in the biological systems used to validate and provide input data for the mathematical models ef cancer. It will tbcus on combining the information from different modalities, including high field (9.4T) magnetic resonance imaging (MRI), bioluminescence, microCT, microPET, and ultrasound, to measure critical morphological, and biophysical features of in vitro and in vivo models of cancer to provide input for the mathematical models, and data with which to test model performance.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA113007-04
Application #
7546198
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2007-09-01
Budget End
2008-08-31
Support Year
4
Fiscal Year
2007
Total Cost
$130,042
Indirect Cost

  Institution

Name
Vanderbilt University Medical Center
Department
Type
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212

  Publications

Hardeman, Keisha N; Peng, Chengwei; Paudel, Bishal B et al. (2017) Dependence On Glycolysis Sensitizes BRAF-mutated Melanomas For Increased Response To Targeted BRAF Inhibition. Sci Rep 7:42604
Udyavar, Akshata R; Wooten, David J; Hoeksema, Megan et al. (2017) Novel Hybrid Phenotype Revealed in Small Cell Lung Cancer by a Transcription Factor Network Model That Can Explain Tumor Heterogeneity. Cancer Res 77:1063-1074
Harris, Leonard A; Frick, Peter L; Garbett, Shawn P et al. (2016) An unbiased metric of antiproliferative drug effect in vitro. Nat Methods 13:497-500
Franco, Omar E; Tyson, Darren R; Konvinse, Katherine C et al. (2016) Altered TGF-?/? signaling drives cooperation between breast cancer cell populations. FASEB J 30:3441-3452
Werner, Benjamin; Scott, Jacob G; Sottoriva, Andrea et al. (2016) The Cancer Stem Cell Fraction in Hierarchically Organized Tumors Can Be Estimated Using Mathematical Modeling and Patient-Specific Treatment Trajectories. Cancer Res 76:1705-13
Gerlee, Philip; Kim, Eunjung; Anderson, Alexander R A (2015) Bridging scales in cancer progression: mapping genotype to phenotype using neural networks. Semin Cancer Biol 30:30-41
Frick, Peter L; Paudel, Bishal B; Tyson, Darren R et al. (2015) Quantifying heterogeneity and dynamics of clonal fitness in response to perturbation. J Cell Physiol 230:1403-12
Nichol, Daniel; Jeavons, Peter; Fletcher, Alexander G et al. (2015) Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance. PLoS Comput Biol 11:e1004493
Broussard, Joshua A; Diggins, Nicole L; Hummel, Stephen et al. (2015) Automated analysis of cell-matrix adhesions in 2D and 3D environments. Sci Rep 5:8124
Enderling, Heiko (2015) Cancer stem cells: small subpopulation or evolving fraction? Integr Biol (Camb) 7:14-23

Showing the most recent 10 out of 88 publications