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Research using laboratory mice has led to fundamental insights into the molecular genetic processes that govern cancer initiation, progression, and treatment response. Although thousands of scientific articles have been published about mouse models of human cancer, collating information and data for a specific model is hampered by the fact that many authors do not adhere to existing annotation standards when describing models. The interpretation of experimental results in mouse models can also be confounded when researchers do not factor in the effect of genetic background on tumor biology. The Mouse Tumor Biology (MTB) database is an expertly curated, comprehensive compendium of mouse models of human cancer. Through the enforcement of nomenclature and related annotation standards, MTB supports aggregation of data about a cancer model from diverse sources and assessment of how genetic background of a mouse strain influences the biological properties of a specific tumor type and model utility. Cancer Res; 77(21); e67–70. ©2017 AACR.

The Mouse Tumor Biology Database (MTB) is designed to provide an electronic data storage, search, and analysis system for information on mouse models of human cancer. The MTB includes data on tumor frequency and latency, strain, germ line, and somatic genetics, pathologic notations, and photomicrographs. The MTB collects data from the primary literature, other public databases, and direct submissions from the scientific community. The MTB is a community resource that provides integrated access to mouse tumor data from different scientific research areas and facilitates integration of molecular, genetic, and pathologic data. Current status of MTB, search capabilities, data types, and future enhancements are described in this article.

The number and types of mouse models of human cancer and the volume and heterogeneity of information related to the characterization of these models is diverse and large. The distributed nature of the information and lack of conformance to terminology standards complicates integrated searches of these data and the identification of relevant mouse models for a particular study or application. The Mouse Tumor Biology database (MTB) (http://tumor.informatics.jax.org) provides online query tools to facilitate cohesive searches and visualization of these varied data, thus enabling the identification of appropriate mouse models of human cancer and potential therapeutic treatments. MTB is an expertly curated resource for information and data about genetically engineered mouse (GEM) strains, inbred strains, and patient-derived xenograft (PDX) models of human cancer. Enforcement of standard gene and strain nomenclature and use of controlled vocabularies within MTB enables complete and accurate searching of the published literature for relevant mouse models. Information in MTB is obtained from curation of peer-reviewed scientific publications and from direct data submissions from individual investigators and large-scale programs. MTB has a primary focus on the cancer predisposition of inbred strains of mice and the spectrum of cancers observed in GEM models. Additionally, the breadth of MTB's data coverage has expanded to encompass PDX models. Recent enhancements to MTB include an interactive mouse model chart that summarizes the number of traditional mouse models and PDXs organized by the top 20 cancer types for human mortality as reported by the American Cancer Society. The traditional mouse models listed are restricted to those in which the frequency of the tumor type is very high (reported colony size greater than or equal to twenty; reported tumor frequency greater than or equal to 80%). For PDX models, all the publicly available models from The Jackson Laboratory PDX repository are listed. MTB currently contains more than 87,000 tumor frequencies, 7,000+ mouse strain cohorts, and over 6,700 images from over 4,300 references. MTB also provides access to detailed clinical, pathologic, expression, and genomics data from over 400 PDX models. Information in MTB is integrated with cancer models data from other bioinformatics resources including PathBase, the Gene Expression Omnibus (GEO), and ArrayExpress. MTB is supported by NCI grant CA089713. Citation Format: Debra M. Krupke, Dale A. Begley, Steven B. Neuhauser, Joel E. Richardson, John P. Sundberg, Carol J. Bult. Mouse Tumor Biology (MTB) database–An integrated data resource for GEM, inbred strains, and PDX models of human cancer [abstract]. In: Proceedings of the AACR Special Conference: Advances in Modeling Cancer in Mice: Technology, Biology, and Beyond; 2017 Sep 24-27; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(10 Suppl):Abstract nr B50.

Many mouse models have been created to study hematopoietic cancer types. There are over thirty hematopoietic tumor types and subtypes, both human and mouse, with various origins, characteristics and clinical prognoses. Determining the specific type of hematopoietic lesion produced in a mouse model and identifying mouse models that correspond to the human subtypes of these lesions has been a continuing challenge for the scientific community. The Mouse Tumor Biology Database (MTB; http://tumor.informatics.jax.org) is designed to facilitate use of mouse models of human cancer by providing detailed histopathologic and molecular information on lymphoma subtypes, including expertly annotated, on line, whole slide scans, and providing a repository for storing information on and querying these data for specific lymphoma models.

The laboratory mouse is the foremost model organism for interrogating the genetic and molecular basis of human cancer and is a powerful platform for identifying therapeutically effective targets for prevention and treatment of cancer. Research using genetically engineered mouse models (GEMMs) have led to important advances in our understanding of the genetic basis of cancer susceptibility, the function of tumor suppressors and oncogenes, and therapy responses in preclinical and co-clinical studies. Patient Derived Xenograft (PDX) models are an increasingly important model system for in vivo studies of human cancer. These models are created by implanting patient tumors into immunodeficient or humanized mouse hosts and are a powerful translational research platform for preclinical and co-clinical studies. The number of GEMM and PDX mouse models increases significantly every year and the diverse cancer-related data about human cancer models tend to be distributed in ways that makes it difficult for researchers to integrate and interpret the information to find the most relevant model for their research. The Mouse Tumor Biology database (http://tumor.informatics.jax.org) is an expertly curated resource for information and data about genetically defined mouse strains and PDX models of human cancer. MTB provides query tools to enable integrated searches and visualization of these varied data, thus facilitating the assessment of novel mouse models of human cancer and potential preventative and therapeutic treatments. Enforcement of controlled vocabularies and standard gene, allele and strain nomenclature within MTB facilitates precise and comprehensive queries of MTB for pertinent mouse models. MTB contains data from spontaneous or endogenously induced tumors from genetically defined mice including tumor classification, incidence, Quantitative Trait Loci, pathology reports, images and genetic changes in the tumor (somatic) and background strain (germline) genomes. The PDX resource enables queries based on tumor type, cancer diagnosis and genomic properties of the engrafted tumors. Information in MTB is obtained from curation of peer-reviewed scientific publications and direct data submissions from individual investigators and large-scale programs. New features in MTB include the Faceted Tumor Search Form and a Reported Mouse Models table linking the most common fatal human cancers to reported equivalent mouse models. MTB contains over 77,000 Tumor Frequencies and over 2,200 Pathology Reports with over 6,600 images from over 4,200 references. MTB provides access to detailed clinical, pathological, expression and genomics data from over 400 PDX models. Information in MTB is integrated with cancer models data from other bioinformatics resources including PathBase, the Gene Expression Omnibus and ArrayExpress. MTB is supported by NCI grant CA089713. Citation Format: Dale A. Begley, Debra M. Krupke, Steven B. Neuhauser, Joel E. Richardson, John P. Sundberg, Janan T. Eppig, Carol J. Bult. Identifying therapeutically relevant mouse and patient-derived xenograft (PDX) models of human cancer using the mouse tumor biology database (MTB) data resource [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2804. doi:10.1158/1538-7445.AM2017-2804

The Mouse Tumor Biology (MTB; http://tumor.informatics.jax.org) database is a unique online compendium of mouse models for human cancer. MTB provides online access to expertly curated information on diverse mouse models for human cancer and interfaces for searching and visualizing data associated with these models. The information in MTB is designed to facilitate the selection of strains for cancer research and is a platform for mining data on tumor development and patterns of metastases. MTB curators acquire data through manual curation of peer-reviewed scientific literature and from direct submissions by researchers. Data in MTB are also obtained from other bioinformatics resources including PathBase, the Gene Expression Omnibus and ArrayExpress. Recent enhancements to MTB improve the association between mouse models and human genes commonly mutated in a variety of cancers as identified in large-scale cancer genomics studies, provide new interfaces for exploring regions of the mouse genome associated with cancer phenotypes and incorporate data and information related to Patient-Derived Xenograft models of human cancers.

In recent years, the scientific community has generated an ever-increasing amount of data from a growing number of animal models of human cancers. Much of these data come from genetically engineered mouse models. Identifying appropriate models for skin cancer and related relevant genetic data sets from an expanding pool of widely disseminated data can be a daunting task. The Mouse Tumor Biology Database (MTB) provides an electronic archive, search and analysis system that can be used to identify dermatological mouse models of cancer, retrieve model-specific data and analyse these data. In this report, we detail MTB's contents and capabilities, together with instructions on how to use MTB to search for skin-related tumor models and associated data.

The laboratory mouse is the premier model organism for understanding the genetic basis of human cancer and is a powerful platform for investigating novel targets for therapeutic intervention. Research using genetically engineered mouse models has led to key insights into the genetics of cancer susceptibility, the function of tumor suppressors and oncogenes, and therapy responses in pre-clinical and co-clinical studies. Patient Derived Xenografts (PDX) models are another model system for in vivo cancer studies. PDX models are created by implanting patient tumors into immunodeficient or humanized mouse hosts. PDX models are a powerful translational research platform for pre-clinical and co-clinical studies. The number of mouse models and the volume and heterogeneity of data related to the characterization of these models has increased dramatically in recent years, making integrated searches of these data and identifying relevant models a significant barrier to their effective use. The Mouse Tumor Biology database (MTB) (http://tumor.informatics.jax.org) provides on-line query tools to facilitate cohesive searches and visualization of these varied data, thus enabling the identification of novel mouse models of human cancer and potential therapeutic treatments. The Mouse Tumor Biology database is an expertly curated resource for information and data about genetically modified mouse strains and PDX models of human cancer. Enforcement of standard gene and strain nomenclature and use of controlled vocabularies within MTB enables complete and accurate searching of the published literature for relevant mouse models. MTB contains data from spontaneous or endogenously induced tumors from genetically defined mice including tumor classification, incidence and latency, tumor associated QTLs, pathology reports, images and genetic changes in the tumor (somatic) and background strain (germline) genomes. The PDX resource enables searches based on tumor type, cancer diagnosis, and genomic properties of the engrafted tumors. Information in MTB is obtained from curation of peer-reviewed scientific publications and from direct data submissions from individual investigators and large-scale programs. MTB contains over 71,000 Tumor Frequencies, and over 2,080 Pathology Reports with over 5,800 images from over 3,600 references. MTB also provides access to detailed clinical, pathological, expression and genomics data from over 450 PDX models. Information in MTB is integrated with cancer models data from other bioinformatics resources including PathBase, the Gene Expression Omnibus (GEO), and ArrayExpress. MTB is supported by NCI grant CA089713. Citation Format: Dale A. Begley, Debbie M. Krupke, Steven B. Neuhauser, Joel E. Richardson, John P. Sundberg, Janan T. Eppig, Carol J. Bult. The mouse tumor biology database (MTB): An integrated data resource for mouse and patient derived xenograft (PDX) models of human cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 631.

Many advances in the field of cancer biology have been made using mouse models of human cancer. The Mouse Tumor Biology (MTB, "http://tumor.informatics.jax.org":http://tumor.informatics.jax.org) database provides web-based access to data on spontaneous and induced tumors from genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice). These data include standardized tumor names and classifications, pathology reports and images, mouse genetics, genomic and cytogenetic changes occurring in the tumor, strain names, tumor frequency and latency, and literature citations.Although primary source for the data represented in MTB is peer-reviewed scientific literature an increasing amount of data is derived from disparate sources. MTB includes annotated histopathology images and cytogenetic assay images for mouse tumors where these data are available from The Jackson Laboratory’s mouse colonies and from outside contributors. MTB encourages direct submission of mouse tumor data and images from the cancer research community and provides investigators with a web-accessible tool for image submission and annotation. Integrated searches of the data in MTB are facilitated by the use of several controlled vocabularies and by adherence to standard nomenclature. MTB also provides links to other related online resources such as the Mouse Genome Database, Mouse Phenome Database, the Biology of the Mammary Gland Web Site, Festing's Listing of Inbred Strains of Mice, the JAX® Mice Web Site, and the Mouse Models of Human Cancers Consortium's Mouse Repository. MTB provides access to data on mouse models of cancer via the internet and has been 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.MTB is supported by NCI grant CA089713.

The increasing number and diversity of available mouse models of human cancer and their growing importance in scientific research have resulted in an enormous increase in the amount and types of data generated from these models. These models represent powerful tools for studying biological and genetic mechanisms of cancer and for translation into potential clinical therapeutics. However, the amount of available data makes it challenging to identify and evaluate specific models and data important for an individual laboratory's research. Placing these data in their proper genetic context is crucial to understanding the biochemical and molecular mechanisms of initiation, progression, and metastasis of different cancers. In addition, the ability of the immunodeficient NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mouse strain to host patient derived xenograft (PDX) models only increases the number of available models and the data produced from them. The Mouse Tumor Biology (MTB) Database provides access to data from mouse and PDX models of human tumors and the tools to analyze these data, facilitating the discovery and evaluation of novel mouse and PDX models of human cancers (http://tumor.informatics.jax.org). MTB includes data on endogenously arising tumors (both spontaneous and induced) in genetically defined mice (inbred, hybrid, mutant, and genetically engineered mice) and information from PDX models of human tumors and provides freely available web access to these data. MTB integrates data from peer-reviewed literature, laboratories studying mouse models of human cancer, production mouse colonies at The Jackson Laboratory (JAX), colonies of aging mice from the Jackson Aging Center, and PDX data from the Jackson Laboratory Patient-derived xenograft resource. MTB also incorporates data from PathBase, and mouse gene expression data sets from NCBI's Gene Expression Omnibus (GEO) and the Array Express Database. Data include tumor classification, incidence and latency, tumor associated quantitative trait loci (QTL), pathology reports, images and genetic changes in tumors (somatic) and background strain (germline). Data type specific query forms (tumor, genetic etc.) allow detailed searches. MTB also can be searched using human gene symbols for orthologous mouse genes and associated data. Pathology images are submitted by the scientific community, from primary literature (with publisher permission), and from JAX colonies. MTB also includes immunohistochemistry data on over 500 antibodies with accompanying images of positive control samples and links to the respective vendors. MTB encourages direct submission of mouse tumor data and images from the cancer research community and has developed a web-based system to facilitate submission of data. Standard nomenclature, controlled vocabularies and literature citations facilitate data integration and robust searches. MTB is integrated with the Mouse Genome Informatics resource (MGI, http://www.informatics.jax.org) and provides links to other related online resources such as the Mouse Phenome Database (MPD), the Biology of the Mammary Gland Web Site, and the NCI Mouse Repository. MTB is supported by NCI grant CA089713. Citation Format: Dale A. Begley, Debra M. Krupke, Steven B. Neuhauser, Joel E. Richardson, John P. Sundberg, Carol J. Bult, Janan T. Eppig. The Mouse Tumor Biology (MTB) Database: An electronic tool for identifying and evaluating mouse and PDX models of human cancer. [abstract]. In: Proceedings of the AACR Special Conference: The Translational Impact of Model Organisms in Cancer; Nov 5-8, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2014;12(11 Suppl):Abstract nr A05.