EMT Reporter Models for Cancer Research: A Window into Invasion and MetastasisNov 12, 2020 at 12:00 PM ET
Epithelial to mesenchymal transition (EMT) involves decreased cell adhesion and increased cell motility, marked by the downregulation of epithelial markers and upregulation of mesenchymal markers. Following this transition in real time can be challenging for breast cancer researchers, as in vitro EMT reporter models in mammary cell lines are not readily available. To address this need, ATCC scientists used CRISPR/Cas9 technology to engineer an EMT reporter into the MCF 10A mammary cell line. The resulting advanced model harbors a knock-in in which E-cadherin is fused with EmGFP for real-time monitoring of EMT progression. The transgene was verified at genomic DNA, transcript, and protein levels. Upon TGF-β stimulation, MCF 10A E-cadherin EmGFP shows enhanced migration, reduced E-cadherin-GFP expression, and elevated vimentin and fibronectin expression, making this engineered cell line an ideal model for screening anticancer therapeutics that target EMT.
- ATCC scientists used CRISPR/Cas9 to engineer an E-cadherin EmGFP (ECAD-EmGFP) reporter knock-in into a breast epithelial cell line.
- The integrity of the ECAD-EmGFP knock-in was verified at the genomic, mRNA, and protein level.
- This advanced cancer model can be used to track EMT status of cells in vitro by monitoring GFP expression.
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Sangeeta Kumari, MS
Senior Biologist, ATCC
Sangeeta Kumari is a Senior Biologist in the Research and Development department at ATCC. In the past several years, she optimized and employed the CRISPR/Cas9 genome-editing platform to generated new advanced cancer model cell lines for biopharma and basic researchers. Previously, Ms. Kumari worked at the Food Drug and Administration, National Institutes of Health, and University of Virginia. Throughout her research career, she has authored many scientific publications and made significant contributions in the areas of biomedical research. Ms. Kumari Received her Master of Science in Bioinformatics degree from the University of Maryland and Bachelor of Arts in Biology degree from University of Virginia.