Successful translational research depends of the flow of information not only from the laboratory to the clinic but also from the clinic to the laboratory and back. The objectives of the Clinical Core are: 1. To provide clinical support for specific Projects (2, 3, and 4) within the SPORE. Such support will include identification and acquisition of clinical samples from patients with specific stages of prostate cancer as well as obtaining consent for tissue donation post-mortem for the Tissue Acquisition at Necropsy program. In addition the Clinical Core will run the neoadjuvant chemotherapy trial and obtain extra prostate tissue to be snap frozen before chemotherapy and at radical prostatectomy. It will also conduct the proposed phase I/II trial of anti-sense clusterin for Project 3. 2. To establish a unified clinical database. The goal will be to bring established databases already in existence in different disciplines into a unified format that will permit entry of real-time patient data on all consenting patients with prostate cancer. This will permit rapid identification of specific populations of patients for clinical trials or other analyses. Methods for linking the clinical data to the specimen database will be established in collaboration with the Tissue and Statistical Cores. 3. To support a translational research infrastructure. Members of Core E will play an active role in the Translational Working Teams (TWT) which will meet every other month. The ultimate goal of these teams is to bring promising research findings into the clinic as quickly as possible. Core E will design and conduct clinical trials which grow out of TWT meetings. The multi-disciplinary, translational approach will also be used as a model to train fellows in clinical research, specifically in prostate cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center (P50)
Project #
1P50CA097186-01
Application #
6671841
Study Section
Special Emphasis Panel (ZCA1)
Project Start
2002-09-19
Project End
2007-04-30
Budget Start
Budget End
Support Year
1
Fiscal Year
2002
Total Cost
Indirect Cost
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
075524595
City
Seattle
State
WA
Country
United States
Zip Code
98109
Cheng, Heather H; Plets, Melissa; Li, Hongli et al. (2018) Circulating microRNAs and treatment response in the Phase II SWOG S0925 study for patients with new metastatic hormone-sensitive prostate cancer. Prostate 78:121-127
Levesque, Christine; Nelson, Peter S (2018) Cellular Constituents of the Prostate Stroma: Key Contributors to Prostate Cancer Progression and Therapy Resistance. Cold Spring Harb Perspect Med 8:
Barnard, Monique; Quanson, Jonathan L; Mostaghel, Elahe et al. (2018) 11-Oxygenated androgen precursors are the preferred substrates for aldo-keto reductase 1C3 (AKR1C3): Implications for castration resistant prostate cancer. J Steroid Biochem Mol Biol 183:192-201
Ganaie, Arsheed A; Beigh, Firdous H; Astone, Matteo et al. (2018) BMI1 Drives Metastasis of Prostate Cancer in Caucasian and African-American Men and Is A Potential Therapeutic Target: Hypothesis Tested in Race-specific Models. Clin Cancer Res 24:6421-6432
Schweizer, Michael T; Haugk, Kathleen; McKiernan, Jožefa S et al. (2018) A phase I study of niclosamide in combination with enzalutamide in men with castration-resistant prostate cancer. PLoS One 13:e0198389
Peacock, James W; Takeuchi, Ario; Hayashi, Norihiro et al. (2018) SEMA3C drives cancer growth by transactivating multiple receptor tyrosine kinases via Plexin B1. EMBO Mol Med 10:219-238
Pollan, Sara G; Huang, Fangjin; Sperger, Jamie M et al. (2018) Regulation of inside-out ?1-integrin activation by CDCP1. Oncogene 37:2817-2836
Wu, Yi-Mi; Cie?lik, Marcin; Lonigro, Robert J et al. (2018) Inactivation of CDK12 Delineates a Distinct Immunogenic Class of Advanced Prostate Cancer. Cell 173:1770-1782.e14
Schweizer, Michael T; Hancock, Michael L; Getzenberg, Robert H et al. (2018) Hormone levels following surgical and medical castration: defining optimal androgen suppression. Asian J Androl 20:405-406
Yan, Qingxiang; Bantis, Leonidas E; Stanford, Janet L et al. (2018) Combining multiple biomarkers linearly to maximize the partial area under the ROC curve. Stat Med 37:627-642

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