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Single cell sequencing of Tri-PyMT cells

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NIAID Data Ecosystem2026-04-30 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP185442
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To study the contribution of epithelial-to-mesenchymal transition (EMT) in tumor metastasis, we established an EMT lineage tracing model in a multiple-transgenic mouse (MMTV-PyMT/Fsp1-Cre/Rosa26mT/mG, Tri-PyMT). In this model, breast tumor cells that underwent EMT would irreversibly switch their expression of the fluorescent marker from RFP+ to GFP+ due to the mesenchymal specific Cre expression. Surprisingly, we found that metastatic tumor cells did not convert from RFP+ to GFP+. Lung metastases were predominantly composed of RFP+ tumor cells persistently exhibiting epithelial phenotypes. These findings challenge the concept that EMT is required for metastasis, and have attracted vigorous discussion about its true contributions to metastasis. One of the major concerns with the EMT lineage tracing model is that expression of GFP only indicates the complete EMT transition. The partial-EMT programming, a novel concept describing tumor cells exhibiting both epithelial and mesenchymal features, could possibly fail to launch the Fsp1-Cre-mediated fluorescent marker switch. To address this concern, we evaluated the EMT status of Tri-PyMT cells on the single cell level by performing single cell RNA-sequencing (scRNA-seq). We found that the expression of epithelial markers (i.e. Epcam and Krt18) and mesenchymal markers (i.e. Vim and S110a4) were largely confined to RFP+ and GFP+ subpopulations, respectively. Based on the differentially expressed EMT related genes, we observed an EMT spectrum in which the low EMT score end was enriched with RFP+ cells, whereas the high EMT score end was enriched with GFP+ cells. Indeed, the fluorescent marker switch in Tri-PyMT cells predicted their EMT status with high specificity and sensitivity. Tri-PyMT cells which were derived from the primary breast tumor of triple transgenic mouse (MMTV-PyMT:Fsp1-cre:Rosa26mT/mG) were sorted into RFP+ or GFP+ populations by FACS and subjected for Drop-seq analysis. Overall design: Single cells of RFP+ and GFP+ populations (4 samples each) were sequenced seperately by Drop-seq in two lanes
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2022-02-02
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