A genomic analysis of mouse models of breast cancer reveals molecular features ofmouse models and relationships to human breast cancer

Genomic variability limits the efficacy of breast cancer therapy. To simplify thestudy of the molecular complexity of breast cancer, researchers have used mousemammary tumor models. However, the degree to which mouse models model human breastcancer and are reflective of the human heterogeneity has yet to be demonstratedwith gene expression studies on a large scale.

To this end, we have built a database consisting of 1,172 mouse mammary tumorsamples from 26 different major oncogenic mouse mammary tumor models.

In this dataset we identified heterogeneity within mouse models and noted asurprising amount of interrelatedness between models, despite differences in thetumor initiating oncogene. Making comparisons between models, we identifieddifferentially expressed genes with alteration correlating with initiating eventsin each model. Using annotation tools, we identified transcription factors with ahigh likelihood of activity within these models. Gene signatures predictedactivation of major cell signaling pathways in each model, predictions thatcorrelated with previous genetic studies. Finally, we noted relationships betweenmouse models and human breast cancer at both the level of gene expression andpredicted signal pathway activity. Importantly, we identified individual mousemodels that recapitulate human breast cancer heterogeneity at the level of geneexpression.

This work underscores the importance of fully characterizing mouse tumor biologyat molecular, histological and genomic levels before a valid comparison to humanbreast cancer may be drawn and provides an important bioinformatic resource.