The overall role of the Bioinformatics Core is to provide SPORE investigators with bioinformatics support services. These services include high-throughput data (microarray and sequence) processing and analysis, often involving statistical and probabilistic analyses, developing ad hoc software and databases, and performing computer simulations. Analyses not involving high-throughput data (e.g., clinical correlations) will be performed by the SPORE Biostatistics Core.
The specific aims of the Bioinformatics Core are 1. To generate gene expression signatures from global lllumina and Affymetrix gene expression microarrays. 2. To describe the biological characteristics and prognostic ability of gene expression signatures through a wide range of functional and pathway analyses. 3. To generate copy number alteration (CNA) profiles from global ahd targeted Agilent array comparative genomic hybridization (aCGH) microarrays. 4. To design custom Agilent aCGH arrays that target specific cancer-associated genes and pathways.

Public Health Relevance

The Bioinformatics Core forms an integral part of the SPORE in Prostate Cancer as it directly supports the timely conduct of research in 3 RPs. The centralization of various bioinformatics services is designed to streamline requests of SPORE investigators to Core personnel with particular areas of expertise, therefore ensuring that services are provided in an efficient manner and with the highest quality.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center (P50)
Project #
5P50CA092629-13
Application #
8567067
Study Section
Special Emphasis Panel (ZCA1-RPRB-M)
Project Start
Project End
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
13
Fiscal Year
2013
Total Cost
$88,163
Indirect Cost
$39,960
Name
Sloan-Kettering Institute for Cancer Research
Department
Type
DUNS #
064931884
City
New York
State
NY
Country
United States
Zip Code
10065
Aras, Omer; Pearce, Gillian; Watkins, Adam J et al. (2018) An in-vivo pilot study into the effects of FDG-mNP in cancer in mice. PLoS One 13:e0202482
Sjoberg, Daniel D; Vickers, Andrew J; Assel, Melissa et al. (2018) Twenty-year Risk of Prostate Cancer Death by Midlife Prostate-specific Antigen and a Panel of Four Kallikrein Markers in a Large Population-based Cohort of Healthy Men. Eur Urol 73:941-948
Vickers, Andrew J; Young-Afat, Danny A; Ehdaie, Behfar et al. (2018) Just-in-time consent: The ethical case for an alternative to traditional informed consent in randomized trials comparing an experimental intervention with usual care. Clin Trials 15:3-8
Assel, Melissa; Dahlin, Anders; Ulmert, David et al. (2018) Association Between Lead Time and Prostate Cancer Grade: Evidence of Grade Progression from Long-term Follow-up of Large Population-based Cohorts Not Subject to Prostate-specific Antigen Screening. Eur Urol 73:961-967
Han, SoHyun; Stoyanova, Radka; Lee, Hansol et al. (2018) Automation of pattern recognition analysis of dynamic contrast-enhanced MRI data to characterize intratumoral vascular heterogeneity. Magn Reson Med 79:1736-1744
Vickers, Andrew J; Steineck, Gunnar (2018) Prognosis, Effect Modification, and Mediation. Eur Urol 74:243-245
Kinsella, Netty; Helleman, Jozien; Bruinsma, Sophie et al. (2018) Active surveillance for prostate cancer: a systematic review of contemporary worldwide practices. Transl Androl Urol 7:83-97
Hieronymus, Haley; Murali, Rajmohan; Tin, Amy et al. (2018) Tumor copy number alteration burden is a pan-cancer prognostic factor associated with recurrence and death. Elife 7:
Scher, Howard I; Graf, Ryon P; Schreiber, Nicole A et al. (2018) Assessment of the Validity of Nuclear-Localized Androgen Receptor Splice Variant 7 in Circulating Tumor Cells as a Predictive Biomarker for Castration-Resistant Prostate Cancer. JAMA Oncol 4:1179-1186
Bielski, Craig M; Zehir, Ahmet; Penson, Alexander V et al. (2018) Genome doubling shapes the evolution and prognosis of advanced cancers. Nat Genet 50:1189-1195

Showing the most recent 10 out of 505 publications