The research proposals in this SPORE encompass a broad range of activities, including studies with cell lines, animal models, and clinical trials. These studies will generate different types of data. Properly designing and analyzing such a wide variety of studies will require a variety of statistical and bioinformatics techniques Data and information must flow smoothly between projects. Data quality and integrity must be ensured by using data audit and backup procedures. Also needed is an efficient interface between the computational biology and data storage facilities provided by the SPORE Core C (Pathology and Data Management Core), particularly for the large amounts of microarray and proteomics expression profiling information. To meet these needs, the Biostatistics and Bioinformatics Core brings together several biostatisticians, bioinformaticians and analysts with expertise in a variety of statistical and bioinformatics disciplines. Placing these individuals within the Biostatistics and Bioinformatics Core (rather than in the individual Projects) strengthens the ability of the Projects to interact effectively. This resource also has the flexibility to match personnel to the evolving biostatistics and bioinformatics needs of the SPORE projects. The Biostatistics and Bioinformatics Core will provide expertise in study design and data analysis to all Projects and Cores.
The specific aims of the Biostatistics and Bioinformatics Core are to:
The specific aims of the Biostatistics and Bioinformatics Core are to: 1. Provide guidance in the design and conduct of clinical trials and other experiments arising from the ongoing research of the SPORE. 2. Provide the innovative and tailored statistical modeling, simulation techniques, and data analyses needed by the Projects, Developmental Research and Career Development Projects, and other Cores to achieve their specific aims. 3. Ensure that the results of all Projects are based on well-designed experiments and are appropriately interpreted.
|Lin, Moubin; Zhang, Liren; Hildebrandt, Michelle A T et al. (2017) Common, germline genetic variations in the novel tumor suppressor BAP1 and risk of developing different types of cancer. Oncotarget 8:74936-74946|
|Shore, Neal D; Boorjian, Stephen A; Canter, Daniel J et al. (2017) Intravesical rAd-IFN?/Syn3 for Patients With High-Grade, Bacillus Calmette-Guerin-Refractory or Relapsed Non-Muscle-Invasive Bladder Cancer: A Phase II Randomized Study. J Clin Oncol 35:3410-3416|
|Wang, Gang; Huang, He; Kamat, Ashish M et al. (2017) High-grade neuroendocrine carcinoma of the urachus-report of 3 cases. Hum Pathol 67:126-133|
|Robertson, A Gordon; Kim, Jaegil; Al-Ahmadie, Hikmat et al. (2017) Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. Cell 171:540-556.e25|
|von Rundstedt, Friedrich-Carl; Mata, Douglas A; Kryvenko, Oleksandr N et al. (2017) Utility of Clinical Risk Stratification in the Selection of Muscle-Invasive Bladder Cancer Patients for Neoadjuvant Chemotherapy: A Retrospective Cohort Study. Bladder Cancer 3:35-44|
|Williams, Stephen B; Kamat, Ashish M; Mmeje, Chinedu et al. (2017) Genetic variants in the inflammation pathway as predictors of recurrence and progression in non-muscle invasive bladder cancer treated with Bacillus Calmette-Guérin. Oncotarget 8:88782-88791|
|Mobley, Aaron; Zhang, Shizhen; Bondaruk, Jolanta et al. (2017) Aurora Kinase A is a Biomarker for Bladder Cancer Detection and Contributes to its Aggressive Behavior. Sci Rep 7:40714|
|Roth, Beat; Jayaratna, Isuru; Sundi, Debasish et al. (2017) Employing an orthotopic model to study the role of epithelial-mesenchymal transition in bladder cancer metastasis. Oncotarget 8:34205-34222|
|Metcalfe, Michael J; Ferguson, James E; Li, Roger et al. (2017) Impact of High-risk Features and Effect of Neoadjuvant Chemotherapy in Urothelial Cancer Patients with Invasion into the Lamina Propria on Transurethral Resection in the Absence of Deep Muscle Invasion. Eur Urol Focus :|
|Choi, Woonyoung; Ochoa, Andrea; McConkey, David J et al. (2017) Genetic Alterations in the Molecular Subtypes of Bladder Cancer: Illustration in the Cancer Genome Atlas Dataset. Eur Urol 72:354-365|
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