The major goals ofthe Core B (Bioinformatics) are to provide the Program with the computational tools and expertise needed to process, analyze, integrate and interpret complex ChlP-Seq and gene expression profiling datasets obtained from normal and malignant T cell progenitors. To date, programmatic needs in these areas have been provided on an ad hoc basis. Creating this Core will provide the Program with dedicated longitudinal informatics and biostatistical support, which is important for the Program's overall success. The facility is headed by Dr. X. Shirley Liu, an experienced, highly productive computational biologist and biostatistician with a track record of innovation in computational analysis of cancer cell epigenetics and gene regulation. Its principle responsibilities will include analysis of ChlP-Seq data obtained from human and murine T-ALL cell lines, human and murine pnmary T-ALLs, and nonnal human and murine thymocyte subsets;analysis of gene expression profiles and/or RNASeq obtained from these cells; and integrative modeling ofthese ChlP-Seq and gene expression datasets.
The specific aims of Core B in the next project period are as follows:
Aim 1. To process, analyze, and integrate ChlP-Seq and gene expression datasets from normal and malignant T cell progenitors Aim 2. To characterize and quantify epigenetic changes associated with T cell differentiation or perturbation of transcription factors in T-ALL cells Aim 3. To advise Program Pis on study design and computational/technological advances Aim 4. To serve as a data repository and resource center for the program and the biomedical research community as a whole
The Bioinformatics Core provides services that are needed forthe Program to meet its overall scientific goals, which are focused on understanding how Notch receptors are activated and turn on the expression of genes that drive the growth and survival of cancer cells. This shared resource provides sophisticated computational biology tools and expertise that allow Program to reach these goals in an expeditious, cost-effective fashion, and in doing contributes to elucidation of fundamental aspects of Notch signaling in cancer.
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|Arnett, Kelly L; Blacklow, Stephen C (2014) Analyzing the nuclear complexes of Notch signaling by electrophoretic mobility shift assay. Methods Mol Biol 1187:231-45|
|Wang, Hongfang; Zang, Chongzhi; Taing, Len et al. (2014) NOTCH1-RBPJ complexes drive target gene expression through dynamic interactions with superenhancers. Proc Natl Acad Sci U S A 111:705-10|
|Dail, Monique; Wong, Jason; Lawrence, Jessica et al. (2014) Loss of oncogenic Notch1 with resistance to a PI3K inhibitor in T-cell leukaemia. Nature 513:512-6|
|Gerhardt, Dawson M; Pajcini, Kostandin V; D'altri, Teresa et al. (2014) The Notch1 transcriptional activation domain is required for development and reveals a novel role for Notch1 signaling in fetal hematopoietic stem cells. Genes Dev 28:576-93|
|Stoeck, Alexander; Lejnine, Serguei; Truong, Andrew et al. (2014) Discovery of biomarkers predictive of GSI response in triple-negative breast cancer and adenoid cystic carcinoma. Cancer Discov 4:1154-67|
|Tiyanont, Kittichoat; Wales, Thomas E; Siebel, Christian W et al. (2013) Insights into Notch3 activation and inhibition mediated by antibodies directed against its negative regulatory region. J Mol Biol 425:3192-204|
|Andrawes, Marie Blanke; Xu, Xiang; Liu, Hong et al. (2013) Intrinsic selectivity of Notch 1 for Delta-like 4 over Delta-like 1. J Biol Chem 288:25477-89|
|Chiang, Mark Y; Shestova, Olga; Xu, Lanwei et al. (2013) Divergent effects of supraphysiologic Notch signals on leukemia stem cells and hematopoietic stem cells. Blood 121:905-17|
|Blacklow, Stephen C (2013) Refining a Jagged edge. Structure 21:2100-1|
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