Our overall goal is to develop an informatics infrastructure essential for supporting basic cancer genetics research using the mouse as a model system for human cancer. The Mouse Tumor Biology (MTB) Database (http://tumor.informatics.jax.org) is a primary resource for researchers seeking integrated information on the frequency, incidence, genetics, and pathology of neoplastic disorders in mice. In addition, selected data from MTB make up the vast majority of data available via the animal models of cancer database (caMOD) that is a core component of NCI's cancer biomedical informatics grid (caBIG) project. MTB emphasizes data on tumors that develop characteristically in different genetically defined strains of mice (inbred, mutant, and genetically engineered) that serve as disease models for human cancers. MTB provides data to assist in selection of strains for experimentation and is a platform for mining data on tumor development and patterns of metastases. We now propose to build on this resource. Specifically: ? We will continue to populate MTB with data on strain-specific patterns of tumorigenesis in inbred, mutant, and genetically engineered mice, including data on tumor diagnoses and pathology images. ? We will integrate new data types into MTB that further contribute to characterization of mouse models for human cancer, including indexing data from gene expression arrays, incorporating data sets from large mouse cohort studies, and including results from large-scale human cancer genomics, such as the NIH Cancer Genome Atlas Project. ? We will enhance access to MTB data using interactive graphical tools, and provide new genome-wide views of specific genetic changes and quantitative trait loci (QTL) associated with tumorigenesis and sequence-based genome views that are integrated with cancer-biology information. ? We will develop a new paradigm for MTB that matches common user workflows to select and refine data sets. ?We will support the infrastructure of MTB through database maintenance, development of new software components, user support services, and community outreach activities and provide new tools for programmatic access to MTB and SQL access for computational users. Our objective is to provide the user with current data about mouse models for human cancer and provide tools for exploring and exploiting MTB data to inspire new hypotheses that may provide novel insights into the process of cancer initiation and progression.

Public Health Relevance

to Public Health Virtually all advances in human medicine rely on the use of animal models, and chief among these model systems is the laboratory mouse. As the primary integrated database of mouse tumor biology, the Mouse Tumor Biology Database (MTB) plays a vital role in the conduct of biomedical research. MTB is designed to facilitate the selection of experimental models for cancer research, the evaluation of mouse genetic models of human cancer, the review of patterns of mutations in specific cancers, and the identification of genes that are commonly mutated across a spectrum of cancers. The expansion and visualization tools planned for MTB will further enhance the value of the mouse as a model system for understanding human biology and cancer processes.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Genomics, Computational Biology and Technology Study Section (GCAT)
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Li, Jerry
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Jackson Laboratory
Bar Harbor
United States
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Dadras, Soheil S; Silva, Kathleen A; King Jr, Lloyd E et al. (2014) Transplantable malignant melanoma in LT.B6 congenic mice resembling pigmented epithelioid melanocytoma in humans. J Invest Dermatol 134:1772-5
Begley, Dale A; Krupke, Debra M; Neuhauser, Steven B et al. (2014) Identifying mouse models for skin cancer using the Mouse Tumor Biology Database. Exp Dermatol 23:761-3
Schofield, Paul N; Vogel, Peter; Gkoutos, Georgios V et al. (2012) Exploring the elephant: histopathology in high-throughput phenotyping of mutant mice. Dis Model Mech 5:19-25
Sher, Roger B; Cox, Gregory A; Mills, Kevin D et al. (2011) Rhabdomyosarcomas in aging A/J mice. PLoS One 6:e23498
Schofield, Paul N; Sundberg, John P; Hoehndorf, Robert et al. (2011) New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models. Brief Funct Genomics 10:258-65
Berndt, Annerose; Cario, Clinton L; Silva, Kathleen A et al. (2011) Identification of fat4 and tsc22d1 as novel candidate genes for spontaneous pulmonary adenomas. Cancer Res 71:5779-91
Schofield, P N; Gruenberger, M; Sundberg, J P (2010) Pathbase and the MPATH ontology. Community resources for mouse histopathology. Vet Pathol 47:1016-20
Schofield, Paul N; Gkoutos, Georgios V; Gruenberger, Michael et al. (2010) Phenotype ontologies for mouse and man: bridging the semantic gap. Dis Model Mech 3:281-9
Sundberg, J P; Schofield, P N (2010) Commentary: mouse genetic nomenclature. Standardization of strain, gene, and protein symbols. Vet Pathol 47:1100-4
Sundberg, J P; Ward, J M; Schofield, P (2009) Where's the mouse info? Vet Pathol 46:1241-4

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