We propose to establish an Automation and Imaging Core to provide reagents, instruments, and expertise for protein analysis, image analysis, high throughput screening, and lab automation for the Projects in this program. The Core will leverage staff, lab automation, small molecule screening, RNAi screening, and computational resources from the Harvard Medical School (HMS) ICCB-Longwood Screening Facility. Core B will also provide education and outreach to the Boston scientific community on new assay technologies and best practices in running small molecule and RNAi screens.
Specific Aims for this Core are: 1. Develop standardized methods for quantitative analysis of proteins, including multiplexed bead-based detection methods, in-cell Western assays, and protein antibody arrays. 2. Support high throughput screening of compound libraries and of genome-scale siRNA libraries by the Projects. This includes liquid handling, assay readout, statistical analysis of data, and informatics support. 3. Provide expertise and resources for imaging and image analysis, including support for automated microscopy, obtaining/testing image analysis software, training investigators in the use of analysis software, and development of new image analysis algorithms. 4. Provide lab automation resources and expertise for cell-based and pure protein assays.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Program Projects (P01)
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Special Emphasis Panel (ZCA1-RPRB-O)
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Harvard University
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Lee, Robin E C; Qasaimeh, Mohammad A; Xia, Xianfang et al. (2016) NF-κB signalling and cell fate decisions in response to a short pulse of tumour necrosis factor. Sci Rep 6:39519
Sarosiek, Kristopher A; Letai, Anthony (2016) Directly targeting the mitochondrial pathway of apoptosis for cancer therapy using BH3 mimetics - recent successes, current challenges and future promise. FEBS J 283:3523-3533
Giedt, Randy J; Fumene Feruglio, Paolo; Pathania, Divya et al. (2016) Computational imaging reveals mitochondrial morphology as a biomarker of cancer phenotype and drug response. Sci Rep 6:32985
Bhola, Patrick D; Mar, Brenton G; Lindsley, R Coleman et al. (2016) Functionally identifiable apoptosis-insensitive subpopulations determine chemoresistance in acute myeloid leukemia. J Clin Invest 126:3827-3836
Roux, Jérémie; Hafner, Marc; Bandara, Samuel et al. (2015) Fractional killing arises from cell-to-cell variability in overcoming a caspase activity threshold. Mol Syst Biol 11:803
Fallahi-Sichani, Mohammad; Moerke, Nathan J; Niepel, Mario et al. (2015) Systematic analysis of BRAF(V600E) melanomas reveals a role for JNK/c-Jun pathway in adaptive resistance to drug-induced apoptosis. Mol Syst Biol 11:797
Chittajallu, Deepak R; Florian, Stefan; Kohler, Rainer H et al. (2015) In vivo cell-cycle profiling in xenograft tumors by quantitative intravital microscopy. Nat Methods 12:577-85
Montero, Joan; Sarosiek, Kristopher A; DeAngelo, Joseph D et al. (2015) Drug-induced death signaling strategy rapidly predicts cancer response to chemotherapy. Cell 160:977-89
Miller, Miles A; Zheng, Yao-Rong; Gadde, Suresh et al. (2015) Tumour-associated macrophages act as a slow-release reservoir of nano-therapeutic Pt(IV) pro-drug. Nat Commun 6:8692
Flusberg, Deborah A; Sorger, Peter K (2015) Surviving apoptosis: life-death signaling in single cells. Trends Cell Biol 25:446-58

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