The overarching theme of this proposal is """"""""Impact of Tumor Heterogeneity on Cancer Progression"""""""". The Experimental Component is therefore geared to quantifying cancer cell heterogeneity with respect to hallmark traits of cancer progression, such as proliferation, metabolism and motility. We will quantify this trait heterogeneity in model cultured cell lines, under several mE perturbation, as average and distribution measurements performed at the single-cell level by high-content automated microscopy and image processing. Trait distributions will also be resolved as statistical subpopulations, in order to uncover common trends between cell lines. Several In vivo tumor experimental systems will complement in vitro assays for the purpose of theoretical model validation. We have assembled a team of talented experimentalists that cover all specific skills needed for this Component, as shown by their distinguished publication records. Staff scientists will assure continuity of Component technology.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA113007-10
Application #
8628755
Study Section
Special Emphasis Panel (ZCA1-SRLB-C)
Project Start
Project End
Budget Start
2014-03-01
Budget End
2015-02-28
Support Year
10
Fiscal Year
2014
Total Cost
$170,230
Indirect Cost
$29,863
Name
Vanderbilt University Medical Center
Department
Type
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
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
Wooten, David J; Quaranta, Vito (2017) Mathematical models of cell phenotype regulation and reprogramming: Make cancer cells sensitive again! Biochim Biophys Acta 1867:167-175
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

Showing the most recent 10 out of 89 publications