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 #
5U54CA143798-05
Application #
8566844
Study Section
Special Emphasis Panel (ZCA1-SRLB-9)
Project Start
Project End
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
5
Fiscal Year
2013
Total Cost
$317,975
Indirect Cost
$49,945
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
02215
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
Badri, H; Pitter, K; Holland, E C et al. (2016) Optimization of radiation dosing schedules for proneural glioblastoma. J Math Biol 72:1301-36
Amato, Katherine R; Wang, Shan; Tan, Li et al. (2016) EPHA2 Blockade Overcomes Acquired Resistance to EGFR Kinase Inhibitors in Lung Cancer. Cancer Res 76:305-18
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
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
Xue, Qiong; Lu, Yao; Eisele, Markus R et al. (2015) Analysis of single-cell cytokine secretion reveals a role for paracrine signaling in coordinating macrophage responses to TLR4 stimulation. Sci Signal 8:ra59
Kleppe, Maria; Kwak, Minsuk; Koppikar, Priya et al. (2015) JAK-STAT pathway activation in malignant and nonmalignant cells contributes to MPN pathogenesis and therapeutic response. Cancer Discov 5:316-31
Meador, Catherine B; Jin, Hailing; de Stanchina, Elisa et al. (2015) Optimizing the sequence of anti-EGFR-targeted therapy in EGFR-mutant lung cancer. Mol Cancer Ther 14:542-52
Foo, Jasmine; Liu, Lin L; Leder, Kevin et al. (2015) An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. PLoS Comput Biol 11:e1004350
Michor, Franziska; Beal, Kathryn (2015) Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort. Cell 163:1059-63

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