The Research Resource Core A will perform quantitative single-cell assays and assist the investigators of the Physical Science - Oncology Center (PS-OC) to perform the research proposed in Projects 1, 2 and 3. This core facility addresses the need for new technologies that enable the monitoring ofthe functional response of primary tumor cells in their native context. To achieve this, we will rely on recent developments in flow cj/tometry that multiplex measurements of phenotypic variability, functional state of activation and/or the response to drugs in heterogeneous populations of cells. Specifically, this core will focus on measuring phospho-profiles of drugsensitive pathways (e.g. EGFR), downstream signaling cascades (e.g. AKT and MAPK pathways), cell-cycle phases, and apoptotic response at the single cell level. Special emphasis will be given to quantification of parameters for the djmamics of tumor cell proliferation and death (e.g. during drug treatment with varying concentration). This core will contribute to the PS-OC by providing quantitative measurements that parameterize

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA143798-04
Application #
8555278
Study Section
Special Emphasis Panel (ZCA1-SRLB-9 (O1))
Project Start
2009-09-30
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
4
Fiscal Year
2012
Total Cost
$336,386
Indirect Cost
$53,416
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
02215
Wala, Jeremiah A; Bandopadhayay, Pratiti; Greenwald, Noah F et al. (2018) SvABA: genome-wide detection of structural variants and indels by local assembly. Genome Res 28:581-591
Chakrabarti, Shaon; Michor, Franziska (2017) Pharmacokinetics and Drug Interactions Determine Optimum Combination Strategies in Computational Models of Cancer Evolution. Cancer Res 77:3908-3921
Wala, Jeremiah; Beroukhim, Rameen (2017) SeqLib: a C?++ API for rapid BAM manipulation, sequence alignment and sequence assembly. Bioinformatics 33:751-753
Amankulor, Nduka M; Kim, Youngmi; Arora, Sonali et al. (2017) Mutant IDH1 regulates the tumor-associated immune system in gliomas. Genes Dev 31:774-786
Garvey, Colleen M; Gerhart, Torin A; Mumenthaler, Shannon M (2017) Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques. J Vis Exp :
Badri, H; Pitter, K; Holland, E C et al. (2016) Optimization of radiation dosing schedules for proneural glioblastoma. J Math Biol 72:1301-36
Wee, Boyoung; Pietras, Alexander; Ozawa, Tatsuya et al. (2016) ABCG2 regulates self-renewal and stem cell marker expression but not tumorigenicity or radiation resistance of glioma cells. Sci Rep 6:25956
Pitter, Kenneth L; Tamagno, Ilaria; Alikhanyan, Kristina et al. (2016) Corticosteroids compromise survival in glioblastoma. Brain 139:1458-71
Garvey, Colleen M; Spiller, Erin; Lindsay, Danika et al. (2016) A high-content image-based method for quantitatively studying context-dependent cell population dynamics. Sci Rep 6:29752
Bolouri, Hamid; Zhao, Lue Ping; Holland, Eric C (2016) Big data visualization identifies the multidimensional molecular landscape of human gliomas. Proc Natl Acad Sci U S A 113:5394-9

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