Abstract

Novel Targets in Endocrine Responsiveness. While Project 1 takes a focused analysis of specific signaling around cellular stress and cell fate decisions. Project 2 will take a functional genomics approach and study cell cycle progression in endocrine sensifive and resistant cells. Drs. Weiner and Golemis will lead the team in Project 2 and apply a powerful synthetic lethal screen approach that we have previously used to study EGFR-mediated signaling. Using a focused siRNA library targeting known ER-driven genes implicated in endocrine responsiveness, we will determine which genes, when their expression is inhibited, affect the ability of E2, TAM, and ICI to regulate cell cycle progression. Importanfiy. the siRNA library will be applied to the same cell models used in Proiect 1. The team will validate candidate genes that primarily affect cell proliferation {i.e., cell cycle), whereas candidate genes associated with specific cellular stress pathways and cell survival {e.g., apoptosis, autophagy, necrosis) will be studied in Project 1.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA149147-04
Application #
8517447
Study Section
Special Emphasis Panel (ZCA1-SRLB-C)
Project Start
Project End
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
4
Fiscal Year
2013
Total Cost
$163,651
Indirect Cost

  Institution

Name
Georgetown University
Department
Type
DUNS #
049515844
City
Washington
State
DC
Country
United States
Zip Code
20057

  Publications

Stires, Hillary; Heckler, Mary M; Fu, Xiaoyong et al. (2018) Integrated molecular analysis of Tamoxifen-resistant invasive lobular breast cancer cells identifies MAPK and GRM/mGluR signaling as therapeutic vulnerabilities. Mol Cell Endocrinol 471:105-117
Wärri, Anni; Cook, Katherine L; Hu, Rong et al. (2018) Autophagy and unfolded protein response (UPR) regulate mammary gland involution by restraining apoptosis-driven irreversible changes. Cell Death Discov 4:40
Shi, Xu; Wang, Xiao; Wang, Tian-Li et al. (2018) SparseIso: a novel Bayesian approach to identify alternatively spliced isoforms from RNA-seq data. Bioinformatics 34:56-63
Beck, Tim N; Smith, Chad H; Flieder, Douglas B et al. (2017) Head and neck squamous cell carcinoma: Ambiguous human papillomavirus status, elevated p16, and deleted retinoblastoma 1. Head Neck 39:E34-E39
Chen, Xi; Shi, Xu; Hilakivi-Clarke, Leena et al. (2017) PSSV: a novel pattern-based probabilistic approach for somatic structural variation identification. Bioinformatics 33:177-183
Varghese, Rency S; Zuo, Yiming; Zhao, Yi et al. (2017) Protein network construction using reverse phase protein array data. Methods 124:89-99
Zhang, Xiyuan; Cook, Katherine L; Warri, Anni et al. (2017) Lifetime Genistein Intake Increases the Response of Mammary Tumors to Tamoxifen in Rats. Clin Cancer Res 23:814-824
Zhang, Yong-Wei; Nasto, Rochelle E; Jablonski, Sandra A et al. (2017) RNA Interference Screening to Identify Proliferation Determinants in Breast Cancer Cells. Bio Protoc 7:
Bhuvaneshwar, Krithika; Belouali, Anas; Singh, Varun et al. (2016) G-DOC Plus - an integrative bioinformatics platform for precision medicine. BMC Bioinformatics 17:193
Sumis, Allison; Cook, Katherine L; Andrade, Fabia O et al. (2016) Social isolation induces autophagy in the mouse mammary gland: link to increased mammary cancer risk. Endocr Relat Cancer 23:839-56

Showing the most recent 10 out of 107 publications