Description
We previously generated genetically engineered mouse (GEM) models based on perturbation of Tp53, Rb with or without Brca1 or Brca2 that develop serous epithelial ovarian cancer (SEOC) closely resembling the human disease on histologic and molecular levels. We have adapted these GEM models to orthotopic allografts that uniformly develop tumors with short latency in immunocompetent recipients and are ideally suited for routine preclinical studies. To monitor passaged tumors at the molecular level, we analyzed transcriptional profiles of a set of primary SEOC and matching derived passaged tumors. We have merged this dataset with previously published ( doi: 10.1158/0008-5472.CAN-11-3834; PMID 22617326) dataset of murine primary ovarian tumors from our GEM models (GSE46169) and merged and compared them to expression profiles of human dataset published previously (doi: 10.1038/nature10166).