Burrows, Alysha (2018) Development of a cell based assay for candidate drug screening using transcription factor activated reporter (TFAR) construct. Masters by Research thesis (MSc), Manchester Metropolitan University.
|
Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (6MB) | Preview |
Abstract
There is a need for new high throughput drug screening models that are able to reliably and efficiently predict drug safety and efficacy during preclinical studies. Transcription factor activated reporter gene (TFAR) cassettes can be utilised in vitro and in vivo to quantify and define modulation of transcription factor activity in response to pharmacological stimulation. Insertion of such genetic constructs into target cells or tissues necessitates the use of genetic manipulation technologies and lentiviral vectors enable permanent integration of these TFAR constructs into a range of cell types. The aim of this project was to create a cell based model for drug screening using a range of previously constructed lentiviral TFARs responsive to NFκB, NRF2, TFEB, AP-1, TCF/LEF (Wnt Signalling), STAT3 and HIF transcription factors. Human embryonic kidney (HEK)293T cells were transduced with a lentiviral TFAR construct. Clonal selection and expansion was performed in response to known agonists for each TFAR. The clonal TFAR-HEK293T cell line panel was provisionally evaluated for responses to a pro-inflammatory cytokine (TNF-α), a cytokine-mediated phorbol ester (PMA) and a GSK-3β inhibitor (LiCl2). Fully quantitative luciferase luminometry data showed that all three factors activated the predicted canonical cell signalling pathways (NFκB, AP-1 and TCF/LEF respectively) but also activated non-canonical pathways. Results were broadly consistent with current literature, demonstrating that the clonal TFAR transduced cell based model could be a valuable first stage platform for evaluating newly synthesised drugs or screening drug libraries.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.