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

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center--Cooperative Agreements (U54)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1-SRLB-9)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Dana-Farber Cancer Institute
United States
Zip Code
Han, Lin; Zi, Xiaoyuan; Garmire, Lana X et al. (2014) Co-detection and sequencing of genes and transcripts from the same single cells facilitated by a microfluidics platform. Sci Rep 4:6485
Dunn, Gavin P; Cheung, Hiu Wing; Agarwalla, Pankaj K et al. (2014) In vivo multiplexed interrogation of amplified genes identifies GAB2 as an ovarian cancer oncogene. Proc Natl Acad Sci U S A 111:1102-7
Singh, Tanya; Kothapalli, Chandrasekhar; Varma, Devika et al. (2014) Carboxymethylcellulose hydrogels support central nervous system-derived tumor-cell chemotactic migration: comparison with conventional extracellular matrix macromolecules. J Biomater Appl 29:433-41
Meador, Catherine B; Micheel, Christine M; Levy, Mia A et al. (2014) Beyond histology: translating tumor genotypes into clinically effective targeted therapies. Clin Cancer Res 20:2264-75
Marusyk, Andriy; Tabassum, Doris P; Altrock, Philipp M et al. (2014) Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature 514:54-8
Foo, Jasmine; Michor, Franziska (2014) Evolution of acquired resistance to anti-cancer therapy. J Theor Biol 355:10-20
Tkach, Karen E; Oyler, Jennifer E; Altan-Bonnet, Grégoire (2014) Cracking the NF-?B code. Sci Signal 7:pe5
Guo, Shangqin; Zi, Xiaoyuan; Schulz, Vincent P et al. (2014) Nonstochastic reprogramming from a privileged somatic cell state. Cell 156:649-62
Leder, Kevin; Pitter, Ken; Laplant, Quincey et al. (2014) Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules. Cell 156:603-16
Elitas, Meltem; Brower, Kara; Lu, Yao et al. (2014) A microchip platform for interrogating tumor-macrophage paracrine signaling at the single-cell level. Lab Chip 14:3582-8

Showing the most recent 10 out of 95 publications