Mouse tumor biology database (MTB): enhancements and current status

The mouse as a model for understanding chronic diseases of aging: the histopathologic basis of aging in inbred mice

Inbred mice provide a unique tool to study aging populations because of the genetic homogeneity within an inbred strain, their short life span, and the tools for analysis which are available. A large-scale longitudinal and cross-sectional aging study was conducted on 30 inbred strains to determine, using histopathology, the type and diversity of diseases mice develop as they age. These data provide tools that when linked with modern in silico genetic mapping tools, can begin to unravel the complex genetics of many of the common chronic diseases associated with aging in humans and other mammals. In addition, novel disease models were discovered in some strains, such as rhabdomyosarcoma in old A/J mice, to diseases affecting many but not all strains including pseudoxanthoma elasticum, pulmonary adenoma, alopecia areata, and many others. This extensive data set is now available online and provides a useful tool to help better understand strain-specific background diseases that can complicate interpretation of genetically engineered mice and other manipulatable mouse studies that utilize these strains.

Cancer and the web

The applications of functional genomics, proteomics and informatics to cancer research have yielded a tremendous amount of information, which is growing all the time. Much of this information is available publicly on the Internet and ranges from general information about different cancers from a patient or clinical viewpoint, through to databases suitable for cancer researchers of all backgrounds, to very specific sites dedicated to individual genes or molecules. A simple search for 'cancer' from a typical Web browser search engine yields more than half a million hits; an even more specific search for 'leukaemia' (>40 000 hits) or 'p53' (>5700 hits) yields far too many hits to allow one to identify particular sites of interest. This review aims to provide a brief guide to some of the resources and databases that can be used as springboards to home in rapidly on information relevant to many fields of cancer research. As such, this article will not focus on a single website but hopes to illustrate some of the ways that postgenomic biology is revolutionizing cancer research. It will cover genomics and proteomics approaches that have been applied to studying global expression patterns in cancers, in addition to providing links ranging from general information about cancer to specific cancer gene mutation databases.

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.

Cause and Effect Considerations in Diagnostic Pathology and Pathology Phenotyping of Genetically Engineered Mice (GEM)

Over the next several decades, biology is embarking on its most ambitious project yet: to annotate the human genome functionally, prioritizing and focusing on those genes relevant to development and disease. Model systems are fundamental prerequisites for this task, and genetically engineered mice (GEM) are by far the most accessible mammalian system because of their anatomical, physiological, and genetic similarity to humans. The scientific utility of GEM has become commonplace since the technology to produce them was established in the early 1980s. Conceptually, however, an efficiently coordinated high-throughput approach that permits correlation between newly discovered genes, functional properties of their protein products, and biological relevance of these products as drug targets has yet to be established. The discipline of veterinary anatomical pathology (hereafter referred to as pathology) is not immune to this requirement for evolution and adaptation, and to address relationships and tissue consequences between tens of thousands of genes and their cognate proteins, novel interdisciplinary technologies and approaches must emerge. Although many of the techniques of pathology are well established, in the context of pathology's contribution to functional annotation of the genome, several conceptually important and unresolved issues remain to be addressed. While an ever-increasing arsenal of genetic and molecular tool-sets are available to evaluate and understand the function of genes and their pathophysiological mechanisms, pathology will continue to play an essential role in confirming cause and effect relationships of gene function in development and disease. This role will continue to be dependent on keen observation, a systematic but disciplined approach, expert knowledge of strain-dependent anatomical differences and incidental lesions, and relevant tissue-based evidence. Miniaturization and high-throughput adaptation of these methods must also continue so that they can complement parallel phenotyping efforts, provide pathology-based data in pace with concurrent phenotyping efforts, and continue to find new utility in the collective effort of functional annotation.

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 of 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).

The nature of the heterozygous Trp53 knockout model for identification of mutagenic carcinogens

The heterozygous Trp53 null allele C57BL/6 (N5) mouse is susceptible to the rapid development of neoplasia by mutagenic carcinogens relative to control strains. This mouse model of chemical carcinogenesis demonstrates 1) dose-related rapid induction of tumors (26 wks), 2) multiple sites of carcinogen-specific tissue susceptibility, and 3) carcinogen-induced loss of heterozygosity involving the Trp53 wild-type allele or a p53 haploinsufficiency permitting mutation of other critical protooncogenes and/or inactivation of tumor suppressor genes driving tumorigenesis. Demonstration of mutation or loss of heterozygosity involving the Trp53 locus is consistent with a common finding in human cancers and supports extrapolation between rodents and humans. Using diverse experimental protocols, almost all mutagenic rodent carcinogens (including all mutagens that are carcinogenic to humans), but not nonmutagenic rodent carcinogens, induce tumors within 26 weeks of continuous exposure. These characteristics and results indicate that the mouse heterozygous for the Trp53 null allele may be of significant use for the prospective identification of mutagenic carcinogens of potential risk to human health.

Web-based access to mouse models of human cancers: the Mouse Tumor Biology (MTB) Database

The Mouse Tumor Biology (MTB) Database serves as a curated, integrated resource for information about tumor genetics and pathology in genetically defined strains of mice (i.e., inbred, transgenic and targeted mutation strains). Sources of information for the database include the published scientific literature and direct data submissions by the scientific community. Researchers access MTB using Web-based query forms and can use the database to answer such questions as 'What tumors have been reported in transgenic mice created on a C57BL/6J background?', 'What tumors in mice are associated with mutations in the Trp53 gene?' and 'What pathology images are available for tumors of the mammary gland regardless of genetic background?'. MTB has been available on the Web since 1998 from the Mouse Genome Informatics web site (http://www.informatics.jax.org). We have recently implemented a number of enhancements to MTB including new query options, redesigned query forms and results pages for pathology and genetic data, and the addition of an electronic data submission and annotation tool for pathology data.

Analysis of molecular profile data using generative and discriminative methods

A modular framework is proposed for modeling and understanding the relationships between molecular profile data and other domain knowledge using a combination of generative (here, graphical models) and discriminative [Support Vector Machines (SVMs)] methods. As illustration, naive Bayes models, simple graphical models, and SVMs were applied to published transcription profile data for 1,988 genes in 62 colon adenocarcinoma tissue specimens labeled as tumor or nontumor. These unsupervised and supervised learning methods identified three classes or subtypes of specimens, assigned tumor or nontumor labels to new specimens and detected six potentially mislabeled specimens. The probability parameters of the three classes were utilized to develop a novel gene relevance, ranking, and selection method. SVMs trained to discriminate nontumor from tumor specimens using only the 50-200 top-ranked genes had the same or better generalization performance than the full repertoire of 1,988 genes. Approximately 90 marker genes were pinpointed for use in understanding the basic biology of colon adenocarcinoma, defining targets for therapeutic intervention and developing diagnostic tools. These potential markers highlight the importance of tissue biology in the etiology of cancer. Comparative analysis of molecular profile data is proposed as a mechanism for predicting the physiological function of genes in instances when comparative sequence analysis proves uninformative, such as with human and yeast translationally controlled tumour protein. Graphical models and SVMs hold promise as the foundations for developing decision support systems for diagnosis, prognosis, and monitoring as well as inferring biological networks.

Website review: The Jackson Laboratory Mouse Genome Informatics Site: version 2.3.2

Site authors: Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, Maine. Project PI: Janan Eppig. All screen views from the website are reproduced with the kind permission of Janan Eppig.