The Mouse Models of Human Cancer database (MMHCdb)

Abstract

The laboratory mouse has served for decades as an informative animal model system for investigating the genetic and genomic basis of cancer in humans. Although thousands of mouse models have been generated, compiling and aggregating relevant data and knowledge about these models is hampered by a general lack of compliance, in the published literature, with nomenclature and annotation standards for genes, alleles, mouse strains and cancer types. The Mouse Models of Human Cancer database (MMHCdb) is an expertly curated, comprehensive knowledgebase of diverse types of mouse models of human cancer, including inbred mouse strains, genetically engineered mouse models, patient-derived xenografts, and mouse genetic diversity panels such as the Collaborative Cross. The MMHCdb is a FAIR-compliant knowledgebase that enforces nomenclature and annotation standards, and supports the completeness and accuracy of searches for mouse models of human cancer and associated data. The resource facilitates the analysis of the impact of genetic background on the incidence and presentation of different tumor types, and aids in the assessment of different mouse strains as models of human cancer biology and treatment response.

Keywords: Cancer; Database; Genetic background; Mouse models; Nomenclature.

Fig. 1.

The Mouse Models of Human Cancer database (MMHCdb). The MMHCdb home page features a summary of different mouse strains associated with the top 20 human cancers, other database search options and a resource news feed. (A) Model summary table. (B) Menu access to search forms and data pages. (C) Quick search window.

Fig. 2.

Screenshot showing the faceted search function on the MMHCdb Advanced Search form for spontaneous lung adenocarcinoma models for which pathology images are available. (A) The selected facets are shown in the left column, highlighted in light blue with a checkmark. (B) Search results summary with links to additional details about the strain, associated publications and model.

Fig. 3.

Genetic background influences cancer phenotypes. (A) A graphical summary of spontaneous tumor frequency in inbred strains is available from the Searches/Tools menu. (B) A summary of variation in types and frequency of tumor types among F1 hybrids heterozygous for the Trp53^Tm3.1Glo allele. Color coding highlights the differences in cancer phenotypes for the same allele on different genetic backgrounds. Data from Chan et al. (2021).

Fig. 4.

MMHCdb-generated summary of cancer profiles for Collaborative Cross mice reported in Wang et al. (2019) (Stedman et al., 1990). Wang et al. (2019) identified a novel Collaborative Cross line with increased susceptibility to gastric cancer (CC036/Unc).

Fig. 5.

Screenshots from the patient-derived xenograft (PDX) Portal. (A) The PDX search form allows searching for PDX models using criteria such as tumor type, diagnosis, treatment response and genomic property. (B) The PDX Like Me query language finds models that match one or more molecular genomic criteria. PDX Like Me is modeled after the Onco Query Language in cBioPortal (Cerami et al., 2012).