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

• Published in: Cancer research (Chicago, Ill.) Ill.), 2018-07, Vol.78 (13_Supplement), p.5102-5102
• Main Authors: Begley, Dale A., Krupke, Debra M., Neuhauser, Steven B., Richardson, Joel E., Sundberg, John P., Bult, Carol J.
• Format: Article
• Language: English
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2018-5102

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 mo