Mouse Tumor Biology Database Research Articles

Abstract 435: Mouse models of human cancer

Abstract Mouse models play a crucial role in understanding the genetic and genomic basis of cancer and for the development of novel cancer therapies. Because data and information about these models are distributed and heterogeneous, gaining an appreciation for which models have been developed and what their characteristics are presents a major challenge for cancer researchers. The Mouse Models of Human Cancer Database (MMHCdb; http://tumor.informatics.jax.org) solves this challenge by providing a comprehensive, expertly curated on-line information resource about genetically engineered (GEMMs) and inbred mouse models of human cancer. In partnership with the European Bioinformatics Institute (EMBL/EBI), MMHCdb has also developed and implemented PDX Finder, a global catalog of Patient Derived Xenograft models (https://www.pdxfinder.org). Both MMHCdb and PDX Finder employ metadata standards to simplify the process of searching for relevant mouse models by diverse criteria including cancer type, type of strain, and genetic alteration. MMHCdb contains more than100,000 records on tumor frequency data for over 7,600 different mouse strains. These data are linked to over 4,700 references, 2,900 pathology reports, and 6,900 images. PDX Finder provides researchers with one stop access to information about more than 2,800 PDX models in repositories from around the world. MMHCdb and PDX Finder are supported, in part, by NIH/NCI CA089713. MMHCdb was formerly called the Mouse Tumor Biology database (MTB). Citation Format: Carol J. Bult, Debra M. Krupke, Steven B. Neuhauser, Joel E. Richardson, John P. Sundberg. Mouse models of human cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 435.

Abstract 1064: PDX Like Me: A molecular profile-based search tool

Abstract Patient Derived Xenografts (PDXs) are generated through the engraftment of human tumor tissue into a specialized (usually, immunodeficient) mouse host strain. PDXs are a useful pre-clinical platform for evaluating the efficacy of single agent and combination therapies that are targeted to specific genomic characteristics of a patient’s tumor. We have implemented the PDX Like Me search tool to assist researchers in identifying PDX models whose tumors match - or are similar to - molecular profiles comprised of one or more genes and one or more genomic characteristics (e.g., copy number status, mutation, and expression). The PDX Like Me interface uses a search syntax similar to the Onco Query Language used by the popular cBioPortal resource. PDX Like Me is one of several search interfaces supported by the Mouse Models of Human Cancer database (formerly, the Mouse Tumor Biology database). MMHCdb (http://tumor.informatics.jax.org) is a comprehensive resource of information on both genetically engineered mouse models (GEMMs) and PDX models of human cancer that has been expertly curated from peer-reviewed scientific publications and direct data submissions from individual investigators and large-scale programs. MMHCdb provides an easy-to-use search interface as well as tools for visualizing associated data from these models. Information in the database is standardized using controlled vocabularies and official gene and mouse strain nomenclature. MMHCdb contains data from spontaneous or endogenously induced tumors from genetically defined mice. MMHCdb holds data on over 7,500 different strains including over 93,000 tumor frequencies and over 2,250 pathology reports with over 6,300 images from over 4,600 references. MMHCdb provides access to clinical, pathology, dosing study results, and genomics data from over 450 PDX models distributed by The Jackson Laboratory. MMHCdb in collaboration with EMBL-EBI has also co-developed the PDX Finder resource to provide a comprehensive global catalog of PDX models available for researchers. 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. PDX Like Me: A molecular profile-based search tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1064.

Abstract 5102: Identifying relevant mouse models of human cancer using the mouse tumor biology database (MTB)

Abstract Mouse models of human cancer have provided important insights into the genetic and molecular basis of human cancer and have been used to identify promising new treatment options for human patients. Genetically engineered mouse models (GEMMS) have been used to identify and characterize the basis of cancer susceptibility, tumor suppressor and oncogene function, and increasingly co-clinical studies of proposed therapeutic treatments. In recent years patient derived xenograft (PDX) models created by implanting human tumor tissue into immune deficient mouse hosts have become a major in vivo pre-clinical research platform for evaluating novel cancer therapies tailored to genomic properties of a patient's tumor. The diversity and distributed nature of GEMM and PDX mouse models, and the data generated from these models, present a significant challenge to researchers who are searching for mouse models relevant to their research. The Mouse Tumor Biology database (http://tumor.informatics.jax.org) is a comprehensive resource of information on both GEMM and PDX models of human cancer that has been expertly curated from peer-reviewed scientific publications and direct data submissions from individual investigators. MTB provides an easy to use search interface and tools for visualizing associated data from mouse models of human cancer. Standardized annotations using controlled vocabularies and official gene and mouse strain nomenclature ensures that researchers get accurate and comprehensive results to their searches. For GEMMs, MTB contains data from over 24,000 different spontaneous or endogenously induced tumors from genetically defined mice obtained from over 4,400 published manuscripts. Annotations include 88,000 tumor frequency records, over 2,200 pathology reports, and over 6,100 images. MTB also provides access to detailed clinical, pathological, expression and genomics data from over 450 PDX models with over 990 histology images. Information in MTB is cross-reference to cancer models data from other bioinformatics resources including PathBase, the Mouse Phenome Database (MPD), the Gene Expression Omnibus and ArrayExpress. Recent enhancements to MTB include the interactive cancer model summary table linking the most common fatal human cancers to relevant mouse models and interactive plots for dosing studies performed using PDX models. MTB has co-developed the PDX Finder resource in collaboration with EMBL-EBI to provide a comprehensive global catalogue of PDX models available for researchers. 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. Identifying relevant mouse models of human cancer using the mouse tumor biology database (MTB) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5102.

Abstract B50: Mouse Tumor Biology (MTB) database–An integrated data resource for GEM, inbred strains, and PDX models of human cancer

Abstract 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.

The Mouse Tumor Biology Database: A Comprehensive Resource for Mouse Models of Human Cancer

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.

Abstract 2804: Identifying therapeutically relevant mouse and patient-derived xenograft (PDX) models of human cancer using the mouse tumor biology database (MTB) data resource

Abstract 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

Abstract 631: The mouse tumor biology database (MTB): An integrated data resource for mouse and patient derived xenograft (PDX) models of human cancer

Abstract 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.

Approaches to Investigating Complex Genetic Traits in a Large-Scale Inbred Mouse Aging Study.

Inbred mice are a unique model system for studying aging because of the genetic homogeneity within inbred strains, the short life span of mice relative to humans, and the rich array of analytic tools that are available. A large-scale aging study was conducted on 28 inbred strains representing great genetic diversity to determine, via histopathology, the type and diversity of spontaneous diseases that aging mice develop. A total of 20 885 different diagnoses were made, with an average of 12 diagnoses per mouse in the study. Eighteen inbred strains have had their genomes sequenced, and many others have been partially sequenced to provide large repositories of data on genetic variation among the strains. This vast amount of genomic information can be utilized in genome-wide association studies to find candidate genes that are involved in the pathogenesis of spontaneous diseases. As an illustration, this article presents a genome-wide association study of the genetic associations of age-related intestinal amyloidosis, which implicated 3 candidate genes: translocating chain-associated membrane protein 1 (Tram1); splicing factor 3b, subunit 5 (Sf3b5); and syntaxin 11 (Stx11). Representative photomicrographs are available on the Mouse Tumor Biology Database and Pathbase to serve as a reference when evaluating inbred mice used in other genetic or experimental studies to rule out strain background lesions. Many of the age-related mouse diseases are similar, if not identical, to human diseases; therefore, the genetic discoveries have direct translational benefit.

Finding mouse models of human lymphomas and leukemia's using the Jackson laboratory mouse tumor biology database

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.

Abstract P6-06-02: Molecular characterization of a patient-derived xenograft (PDX) resource for triple negative breast cancer

Abstract The Jackson Laboratory (JAX) has developed a resource of human tumors implanted into immune deficient mice (patient derived xenografts; PDX) as a platform for testing standard of care and novel therapeutic options for Triple Negative Breast Cancer. PDX models provide an advantage over cell culture based models for testing therapeutic interventions because they retain properties such as tumor cell heterogeneity that are critical to the biological properties of a patient’s tumor and response to treatment. Tumor material acquired from biopsy or surgical resection was implanted subcutaneously into the flank of immune deficient NOD-scid IL2r gamma-chain null (NSG) mice. The PDX resource currently contains 21 established breast cancer PDX models (12 TNBC) with 24 additional models currently in development. Two of the established TNBC PDX models have BRCA1 mutations. The median age of the patients from whom tumor material was obtained for all breast models is 53 (45-89). Tumors that successfully engrafted were characterized for somatic mutations using the new JAX Clinical Cancer Panel, Copy Number Variants using the Affymetrix human 6.0 SNP array, and gene expression using both Affymetrix U133 plus v2 and RNA-Seq. Normalized gene expression was analyzed for characteristic patterns in a pan-cancer approach across all PDX models and further compared with the previously identified TNBC molecular subtypes (Lehmann et al. 2011. JCI 121:2750-2767). The combination of principal components analysis and classification via expression pattern resulted in putative matches of models to most of the known molecularly defined subtypes of TNBC tumors. Tumor bearing mice for the TNBC PDX models have been treated with docetaxel, cisplatin, cyclophosphamide and doxorubicin. Preliminary studies of tumor response to these treatment regimes revealed systematic differences that can be correlated with features of the genomic analysis, including expression subtype characterization. The JAX collection of TNBC cancer PDX models is a well-annotated, publically available resource of models with deep genomic characterization and standard of care therapy response data for use in the development of advanced therapeutic options. Genomically defined subgroups within the collection suggest strategies to refine patient selection and treatment algorithms. Information about the models along with summarized genomic data is publicly available at the Mouse Tumor Biology database PDX web portal (http://tumor.informatics.jax.org). Citation Format: Joel H Graber, James G Keck, Susan D Airhart, Carol J Bult, Edison T Liu. Molecular characterization of a patient-derived xenograft (PDX) resource for triple negative breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-06-02.

Abstract A05: The Mouse Tumor Biology (MTB) Database: An electronic tool for identifying and evaluating mouse and PDX models of human cancer

Abstract 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.

Mouse Tumor Biology (MTB): a database of mouse models for human cancer.

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.

Abstract C18: Interpreting the cancer genome using the Mouse Tumor Biology (MTB) Database

Abstract For over a century cancer biologists have utilized the laboratory mouse in the study of cancer biology. Many mouse models recapitulate the genetic abnormalities observed in human cancers. The Mouse Tumor Biology Database (MTB; http://tumor.informatics.jax.org) provides multiple tools to explore and interpret the cancer genome. These tools include the ability to search MTB using mouse or human gene symbols, a mouse cancer quantitative trait loci (QTL) viewer, links to gene expression data for a variety of mouse models of human cancer, and access to public genomic data from the emerging Jackson Laboratory (JAX; http://www.jax.org) Patient-Derived Xenograft (PDX) program. MTB was established in 1997 and provides freely available access to data on spontaneous and induced tumors from genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains). These data include standardized tumor names and classifications, pathology reports and images, mouse genes and QTL associated with cancers, genomic and cytogenetic changes occurring in the tumor, strain names, tumor frequency and latency, and literature citations. Although the primary source for data represented in MTB is peer-reviewed scientific literature an increasing amount of data are derived from large systematic programs (e.g. JAX Aging Resource, PDX Program) and laboratory or consortia contributions. MTB includes annotated histopathology images and cytogenetic assay images for mouse tumors where these data are available. 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. 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, Janan T. Eppig. Interpreting the cancer genome using the Mouse Tumor Biology (MTB) Database. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr C18.

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as ‘GO’ or ‘homology’ or ‘phenotype’. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as ‘papers selected for GO that refer to genes with NO GO annotation’. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications.

The Mouse Tumor Biology Database (MTB)

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.

Literature Triage and Indexing in the Mouse Genome Informatics (MGI) Group

AbstractThe Mouse Genome Informatics (MGI; "http://www.informatics.jax.org":http://www.informatics.jax.org) group is comprised of several collaborating projects including the Mouse Genome Database (MGD) Project, the Gene Expression Database (GXD) Project, the Mouse Tumor Biology (MTB) Database Project, and the Gene Ontology (GO) Project. Literature identification and collection is performed cooperatively amongst the groups.In recent years many institutional libraries have transitioned from a focus largely on print holdings to one of electronic access to journals. This change has necessitated adaptation on the part of the MGI curatorial group. Whereas the majority of journals covered by the group used to be surveyed in paper form, those journals are now surveyed electronically. Approximately 160 journals have been identified as those most relevant to the various database groups. Each curator in the group has the responsibility of scanning several journals for articles relevant to any of the database projects. Articles chosen via this process are marked as to their potential significance for various projects. Each article is catalogued in a Master Bibliography section of the MGI database system and annotated to the database sections for which it has been identified as relevant. A secondary triage process allows curators from each group to scan the chosen articles and mark ones desired for their project if such annotation has been missed on the initial scan.Once articles have been identified for each database project a variety of processes are implemented to further categorize and index data from those articles. For example, the Alleles and Phenotype section of the MGD database indexes each article marked for MGD and in this indexing process they identify each mouse gene and allele examined in the article. The GXD database indexing process has a different focus. In this case articles are indexed with regard to the stage of development used in the study as well as the assay technique used. In each case the indexing gives an overview of the data held in the article and assists in the more extensive curation performed in the following step of the curation process. Indexing also provides each group with valuable information used to prioritize and streamline the overall curation process.The MGI projects are supported by NHGRI grants HG000330, HG00273, and HG003622, NICHD grant HD033745, and NCI grant CA089713.

Cancer Biology Data Curation at the Mouse Tumor Biology Database (MTB)

AbstractMany 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 Mouse Tumor Biology database

The laboratory mouse has long been an important tool in the study of the biology and genetics of human cancer. With the advent of genetic engineering techniques, DNA microarray analyses, tissue arrays and other large-scale, high-throughput data generating methods, the amount of data available for mouse models of cancer is growing exponentially. Tools to integrate, locate and visualize these data are crucial to aid researchers in their investigations. The Mouse Tumor Biology database (http://tumor.informatics.jax.org) seeks to address that need.

Mouse Tumor Biology Database (MTB): status update and future directions

The Mouse Tumor Biology (MTB) database provides access to data about endogenously arising tumors (both spontaneous and induced) in genetically defined mice (inbred, hybrid, mutant and genetically engineered mice). Data include information on the frequency and latency of mouse tumors, pathology reports and images, genomic changes occurring in the tumors, genetic (strain) background and literature or contributor citations. Data are curated from the primary literature or submitted directly from researchers. MTB is accessed via the Mouse Genome Informatics web site (). Integrated searches of MTB are enabled through use of multiple controlled vocabularies and by adherence to standardized nomenclature, when available. Recently MTB has been redesigned and its database infrastructure replaced with a robust relational database management system (RDMS). Web interface improvements include a new advanced query form and enhancements to already existing search capabilities. The Tumor Frequency Grid has been revised to enhance interactivity, providing an overview of reported tumor incidence across mouse strains and an entrée into the database. A new pathology data submission tool allows users to submit, edit and release data to the MTB system.

THE MOUSE TUMOR BIOLOGY DATABASE: INTEGRATED ACCESS TO MOUSE CANCER BIOLOGY DATA

Mice have long been used as models for the study of human cancer. The National Cancer Institute has included among its research areas of extraordinary opportunity the development of new mouse genetic models of human cancer and the exploration of cancer imaging as a research tool. Because of the volume and interconnectedness of relevant data, the creation and maintenance of bioinformatics resources for mouse tumor biology is necessary to facilitate current and future cancer research. The Mouse Tumor Biology (MTB) Database provides electronic access to data generated through the study of spontaneous and induced tumors in genetically defined mice (inbred, hybrid, spontaneous and induced mutant, and genetically engineered strains of mice).