Abstract 988: A mouse model gene expression database reveals E2Fs as key regulators of breast cancer metastasis

Metastasis is primarily responsible for the mortality associated with breast cancer. Despite this, the molecular underpinnings of cancer progression are poorly understood. By integrating bioinformatics with traditional genetics, we have addressed the hypothesis that genetic events mediating breast cancer metastasis can be elucidated from mouse models. To test this hypothesis, we assembled a gene expression database of over 1100 mouse breast cancers from 23 different models. Using this database, E2F transcription factors were predicted to be strikingly activated in metastatic mouse models. Transgenic MMTV-Neu mice were interbred with E2F transcription factor knockouts to test this hypothesis. Tumor latency was increased significantly with the loss of any of the activator E2Fs in the MMTV-Neu mice. Strikingly, there was also a significant reduction in the extent of pulmonary metastasis with loss of either E2F1 or E2F2. This metastasis reduction was shown to be a cell autonomous effect through a transplant experiment. Moreover, CD-31 staining revealed vasculature alterations with E2F loss. These data led to the hypothesis that E2F transcription factors were critical in mediating metastasis. Highly metastatic MMTV-PyMT transgenic mice also had predicted E2F transcription factor activation. Genetically testing this prediction, we noted that PyMT transgenic mice lacking E2F1 or E2F2 recapitulated the MMTV-Neu results with a vast reduction in metastasis. Using a tail vein injection we noted defects in extravasation with E2F1 or E2F2 loss. To determine the mechanism by which E2Fs regulated metastatic progression, we examined gene expression profiles of MMTV-Neu and PyMT tumors in both control and E2F knockout backgrounds. This analysis identified a cohort of genes with reduced expression in the non-metastatic E2F knockout breast cancers relative to the metastatic wild type E2F controls. Importantly, genes identified in the mouse model system are co-amplified in human HER2+ breast cancer but are not part of the HER2 amplicon. This amplicon is present in over 30% of HER2+ human breast cancers and is inversely associated with metastasis free survival. In addition to examining the amplicon genes in HER2+ human breast cancer, we have also examined predicted E2F activity using genomic signatures. This revealed four common combinations of E2F activity in HER2+ breast cancer. Importantly, low E2F1 and high E2F2 in the same sample was associated with far better relapse free survival than the opposite E2F pattern. These data indicate that the effects and the mechanisms uncovered in the mouse models are present in HER2+ human breast cancer. Taken together, by integrating bioinformatics with mouse models of breast cancer we have demonstrated that the E2F transcription factors play a pivotal role in progression from primary breast cancer to metastasis. Citation Format: Daniel Hollern, John Rennhack, Eran Andrechek. A mouse model gene expression database reveals E2Fs as key regulators of breast cancer metastasis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 988. doi:10.1158/1538-7445.AM2014-988