Targeting PyMT oncogene to diverse mammary cell populations enhances tumor heterogeneity and generates rare breast cancer subtypes
收藏NIAID Data Ecosystem2026-03-10 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40001
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We are generating a new mouse model for breast cancer heterogenaity using lentiviral infection to integrate the sporatically transforming EF1α-PyMT10C or Muc-PyMT10C lentivirus into mouse mammary epithelial cell genomes. We then transplant those cells into cleared mammary fat pads of recipient mice, allowing tumors to develop from luminal , myoepithelial, stem and progenitor cell lineages. We developed a wide variety of tumors including rare histologies such as squamous, tubular, spindloid and lipid rich. We used microarray analysis to compare our mouse model with a microarray analysis of 9 established mouse models (Herschkowitz, J.I. et al. Genome Biology, 2007). Heirarchal clustering was used to establish the molecular subtype of tumors developed through the lentiviral-PyMT mouse model. In addition, micrarray analysis was used in conjunction with GeneSifter and GO ontology to identify unique pathways for each of the rare tumor types. 43 total microarrays were generated from lentiviral-PyMT tumors, MMTV-PyMT transgenic tumors, and embryonic samples . Nine samples were two color arrays run at UNC microarray facility, while 34 were one color arrays run at Huntsman Cancer Instutite. The two color arrays were treated as one color arrays, we used the Cy5 intensity data for analysis. These data were merged and normalized (quantile and combat) with previously published arrays from UNC. Data were filtered on an intrinsic gene set developed in 2007 (Herschkowitz, J.I. et al. Genome Biology, 2007) and clustered using euclidian distance metrics This GEO submission consists of the 34 one color arrays run at Huntsman Cancer Instutite. The nine two color arrays run at UNC microarray facility are not included.
创建时间:
2017-01-12



