The Biostatistics and Medical Informatics Core will be led by Drs. Alan Hutson and Carmelo Gaudioso. Dr. Hutson is Chair of Biostatistics and Bioinformatics at Roswell Park Cancer Institute (RPCI) and Chair of Biostatistics at the University at Buffalo (UB). He has two decades of experience in basic, translational and clinical experimental design and analysis. Dr. Gaudioso is the Director of Medical Informatics, Associate Director of the Clinical Data Network, and Assistant Professor of Oncology at RPCI. His research area is knowledge management and decision support systems. The Biostatistics and Medical Informatics Core will ensure that biostatistics, bioinformatics and medical informatics design and modeling support is available to all RPCI Prostate Cancer SPORE project leaders and core directors and their co-investigators. The Biostatistics and Medical Informatics Core is designed to provide statistical support that considers both institutional proximity and the biostatistical, bioinformatics and medical informatics needs of individual investigators. Specifically, we aim to: To assist basic, translational and clinical researchers of the RPCI Ovarian Cancer SPORE with proper formulation, refinement and execution of study objectives by applying the appropriate biostatistics and bioinformatics analyses, and providing the appropriate interpretation of their results, in terms of both strengths and limitations;To establish a robust data management system to effectively manage the Ovarian Cancer SPORE's informatics needs in supporting multidisciplinary, multi-project, multi-institutional clinical and translational research and facilitating data sharing and information dissemination;and To notify RPCI-UPCI Ovarian Cancer SPORE investigators when data are sufficiently mature to write a manuscript, to write the statistical methods section of manuscripts and to provide expert collaborative guidance in formulating the rest of the manuscript. It is anticipated that the services of the Biostatistics and Medical Informatics Core will be extensively used by all researchers associated with the SPORE. Benefits to the Biostatistics and Medical Informatics Core include providing a consistent team dedicated to efficient and effective collaboration. Benefits towards developing the Biostatistics and Medical Informatics Core include providing a consistent team dedicated to efficient collaboration across three comprehensive cancer centers.

Public Health Relevance

of this application is to develop a biostatistical and informatics resource such that all RPCI-UPCI Ovarian SPORE projects are provided the highest level of biostatistics, bioinformatics and medical informatics support.

National Institute of Health (NIH)
National Cancer Institute (NCI)
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Roswell Park Cancer Institute Corp
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Block, Matthew S; Vierkant, Robert A; Rambau, Peter F et al. (2018) MyD88 and TLR4 Expression in Epithelial Ovarian Cancer. Mayo Clin Proc 93:307-320
Wang, Zehua; Yang, Bo; Zhang, Min et al. (2018) lncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in Cancer. Cancer Cell 33:706-720.e9
Mayor, Paul C; Eng, Kevin H; Singel, Kelly L et al. (2018) Cancer in primary immunodeficiency diseases: Cancer incidence in the United States Immune Deficiency Network Registry. J Allergy Clin Immunol 141:1028-1035
Harris, Holly R; Babic, Ana; Webb, Penelope M et al. (2018) Polycystic Ovary Syndrome, Oligomenorrhea, and Risk of Ovarian Cancer Histotypes: Evidence from the Ovarian Cancer Association Consortium. Cancer Epidemiol Biomarkers Prev 27:174-182
Shenoy, Gautam N; Loyall, Jenni; Berenson, Charles S et al. (2018) Sialic Acid-Dependent Inhibition of T Cells by Exosomal Ganglioside GD3 in Ovarian Tumor Microenvironments. J Immunol 201:3750-3758
Lu, Yingchang; Beeghly-Fadiel, Alicia; Wu, Lang et al. (2018) A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Cancer Res 78:5419-5430
Wang, Yue; Wang, Zehua; Xu, Jieni et al. (2018) Systematic identification of non-coding pharmacogenomic landscape in cancer. Nat Commun 9:3192
Minlikeeva, Albina N; Moysich, Kirsten B; Mayor, Paul C et al. (2018) Anthropometric characteristics and ovarian cancer risk and survival. Cancer Causes Control 29:201-212
Peres, Lauren C; Risch, Harvey; Terry, Kathryn L et al. (2018) Racial/ethnic differences in the epidemiology of ovarian cancer: a pooled analysis of 12 case-control studies. Int J Epidemiol 47:460-472
Szender, J Brian; Kaur, Jasmine; Clayback, Katherine et al. (2018) Breadth of Genetic Testing Selected by Patients at Risk of Hereditary Breast and Ovarian Cancer. Int J Gynecol Cancer 28:26-33

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