Analyzing, managing, and interpreting data accumulated in the age of accessible genomics involves tremendous challenges. A shared resource consisting of informatics and computational scientists, a group of specially trained professionals who understand both biomedical and computer science methodologies, fills the collaboration gap between members, IT professionals, and computational scientists. The overall goal of the Cancer Informatics Core (CIC) is to facilitate the biomedical and translational research of Moffitt Cancer Center (MCC) members through implementation and development of methods and tools to record, integrate, manage, analyze, visualize, and share biomedical, behavioral, and clinical data. To accomplish its goal, the CIC's Specific Aims are to: 1) Support members' 'omics projects with bioinformatics project design, analysis, biological interpretation, and visualizations: The CIC provides bioinformatics and big data analysis and collaborates closely with the Biostatistics Core (BC) to provide seamless analytical services for member projects involving expression profiling, next-generation sequencing, and proteomics. Services include QC, normalization, batch correction, phenotypic analysis, and biological pathway enrichment. 2) Support members' data management and reporting needs with study-specific informatics tools: Complex, study-specific data are collected for member biomedical research studies, including large multi- project studies such as SPOREs. 3) Provide educational opportunities to train members and staff on the use of bioinformatics resources and tools: Public resources are available for members and staff to extract biomedical data and knowledge, leveraging work of the entire scientific community. The CIC provides training for members for awareness of and access to these resources directly. The CIC includes three faculty members, a core facility manager, five staff scientists, and three software developers. CIC bioinformatics faculty devote 50-70% effort to MCC collaborative research activities, supported by CCSG, other grant, and institutional funding. Staff scientists and software developers are dedicated 100% to the CIC, supported by CCSG funding, chargebacks, and institutional support. CIC faculty and staff members are involved in all stages of scientific research, from supporting experimental design (with the Biostatistics Core) to publication of research findings. The CIC has provided significant impact in member research studies through bioinformatics analysis in genomics, proteomics, and expression profiling resulting in high-impact publications in journals such as Nature Genetics and Cancer Research. Over the past five years, the CIC has supported scientific projects of members of all programs, resulting in 62 publications. In the most recent fiscal year, the CIC supported 35 members, with 84% of usage by peer-review-funded members.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA076292-20
Application #
9419794
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2018-02-01
Budget End
2019-01-31
Support Year
20
Fiscal Year
2018
Total Cost
Indirect Cost
Name
H. Lee Moffitt Cancer Center & Research Institute
Department
Type
DUNS #
139301956
City
Tampa
State
FL
Country
United States
Zip Code
33612
Karolak, Aleksandra; Rejniak, Katarzyna A (2018) Micropharmacology: An In Silico Approach for Assessing Drug Efficacy Within a Tumor Tissue. Bull Math Biol :
Karolak, Aleksandra; Estrella, Veronica C; Huynh, Amanda S et al. (2018) Targeting Ligand Specificity Linked to Tumor Tissue Topological Heterogeneity via Single-Cell Micro-Pharmacological Modeling. Sci Rep 8:3638
Barata, Anna; Gonzalez, Brian D; Sutton, Steven K et al. (2018) Coping strategies modify risk of depression associated with hematopoietic cell transplant symptomatology. J Health Psychol 23:1028-1037
Li, Qian; Balagurunathan, Yoganand; Liu, Ying et al. (2018) Comparison Between Radiological Semantic Features and Lung-RADS in Predicting Malignancy of Screen-Detected Lung Nodules in the National Lung Screening Trial. Clin Lung Cancer 19:148-156.e3
Kazi, Aslamuzzaman; Xiang, Shengyan; Yang, Hua et al. (2018) GSK3 suppression upregulates ?-catenin and c-Myc to abrogate KRas-dependent tumors. Nat Commun 9:5154
McWilliams, Robert R; Wieben, Eric D; Chaffee, Kari G et al. (2018) CDKN2A Germline Rare Coding Variants and Risk of Pancreatic Cancer in Minority Populations. Cancer Epidemiol Biomarkers Prev 27:1364-1370
Ctortecka, Claudia; Palve, Vinayak; Kuenzi, Brent M et al. (2018) Functional Proteomics and Deep Network Interrogation Reveal a Complex Mechanism of Action of Midostaurin in Lung Cancer Cells. Mol Cell Proteomics 17:2434-2447
Ferreiro-Iglesias, Aida; Lesseur, Corina; McKay, James et al. (2018) Fine mapping of MHC region in lung cancer highlights independent susceptibility loci by ethnicity. Nat Commun 9:3927
Schmit, Stephanie L; Edlund, Christopher K; Schumacher, Fredrick R et al. (2018) Novel Common Genetic Susceptibility Loci for Colorectal Cancer. J Natl Cancer Inst :
Kang, Sokbom; Thompson, Zachary; McClung, E Claire et al. (2018) Gene Expression Signature-Based Prediction of Lymph Node Metastasis in Patients With Endometrioid Endometrial Cancer. Int J Gynecol Cancer 28:260-266

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