| Literature DB >> 26167451 |
Nicholas Borcherding1, Nicholas Bormann2, David Kusner3, Ryan Kolb4, Weizhou Zhang5.
Abstract
Breast cancer is the leading cause of cancer-related mortality for females worldwide.1 Improving early screening strategies and understanding the events that lead to tumor initiation have led to demonstrable improvements in clinical outcome. Our previous work revealed a variance in the tumorigenic capacity between different mammary epithelial cell populations in an MMTV-ErbB2 mouse model. In order to greater understand how different mammary epithelial cells influence the tumorigenic capacity in ErbB2-induced breast cancer, we transplanted different cell populations from pre-neoplastic MMTV-ErbB2 female mice into recipient mice for tumorigenic study. We found that different mammary epithelial cells bear different tumorigenic potential even when induced by the same ErbB2 proto-oncogene. To understand the difference in tumors formed from different epithelial cells, we performed gene expression profiling using these tumors (GSE64487). Several genes were further validated using real-time reverse transcription polymerase chain reaction (RT-PCR). Here we provide further details on the experimental methods and microarray analysis. This data provides a resource to further understanding how different mammary cell populations can initiate ErbB2-driven tumors and the role of these cell populations as putative tumor-initiating cells (TICs).Entities:
Keywords: Breast cancer; luminal progenitors; mammary stem cells; myoepithelial cells; tumor-initiating cells
Year: 2015 PMID: 26167451 PMCID: PMC4493742 DOI: 10.1016/j.gdata.2015.04.008
Source DB: PubMed Journal: Genom Data ISSN: 2213-5960
Fig. 1Box plot of the quantile normalized expression level for the 12 microarrays. The line bisecting the boxplot is the mean probe value. Samples appear in the order of series matrix file of GSE64487 dataset, the order of the original blinding of the RNA experiment.
Fig. 2A. Volcano plot displaying the gene expression fold change and P-value for LP WT versus LP IkkaAA/ (AA). Genes with fold-change ≥ 1 and P-value ≤ 0.05 (15 genes) are highlighted in red and fold-change ≤ -1 and P-value ≤ 0.05 (23 genes) in green. B. Heatmap of the 20 most differentially expressed genes, as measured by absolute fold-change difference. Samples are labeled according to the GSE64487 dataset.
Fig. 3A. Volcano plot displaying the gene expression fold change and P-value for Myo WT versus MSC WT. Genes with fold-change ≥ 1 and P-value ≤ 0.05 (30 genes) are highlighted in red and fold-change ≤ − 1 and P-value ≤ 0.05 (39 genes) in green. B. Heatmap of the 20 most differentially expressed genes, as measured by absolute fold-change difference. Samples are labeled according to the GSE64487 dataset.
Fig. 4A. Volcano plot displaying the gene expression fold change and P-value for Myo WT versus LP WT. Genes with fold-change ≥ 1 and P-value ≤ 0.05 (14 genes) are highlighted in red and fold-change ≤ -1 and P-value ≤ 0.05 (8 genes) in green. B. Heatmap of the 20 most differentially expressed genes, as measured by absolute fold-change difference. Samples are labeled according to the GSE64487 dataset.
| Specifications | |
|---|---|
| Organism/cell line/tissue | |
| Sex | Female |
| Sequencer or array type | Illumina Infinium MouseWG-6 v2.0 |
| Data format | Raw: Available in TXT file |
| Experimental factors | Mammary tumors derived from basal and luminal mammary compartments. |
| Experimental features | Gene expression profiling in |
| Consent | N/A |
| Sample source location | Department of Pathology, University of Iowa, Iowa City, IA |