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Title: Improved orthotopic and metastatic breast cancer models incorporating key elements of the tumour microenvironment enabling patient-relevant drug testing
Author: Nicolaou, Niovi
ISNI:       0000 0004 5358 6631
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2015
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Breast cancer (BC) is the most commonly diagnosed cancer in the UK and the second leading cause of cancer-related deaths in women worldwide. Limited treatment is available to patients with metastatic BCs, which are resistant to therapy. There is a strong link between metastatic BC and Epithelial Mesenchymal Transition (EMT). There is a need to target EMT, in order to prevent metastasis for which the therapy is not effective. Therefore, there is a need for improved pre-clinical models that will allow studying EMT in real-time. This study aimed to refine current in vivo models of BC, by incorporating inducible bioluminescent reporter(s) that will allow real-time read-out of EMT. The cell-lines used were classified according to their expression of EMT markers and cancer stem cell (CSC) profile. Inducible bioluminescent EMT reporters based on the S100A4 or E-cadherin or N-cadherin promoter driving firefly luciferase were constructed and used to transduce the cell lines. The activity of the S100A4 reporter was validated in hypoxic conditions in MCF-7 and BT549 cells, where it was shown that induction of S100A4-generated bioluminescence was associated with upregulation in S100A4. In vivo it was shown that human mesenchymal stem cells promoted the tumour growth of MCF-7 cells and/or induced EMT-related traits, including downregulation/loss of E-cadherin, upregulation of Vimentin and/or upregulation of S100A4. The activity of the S100A4 reporter was tested in a similar in vivo model, where it was shown that S100A4-generated bioluminescence correlated with protein expression of S100A4. Taken all the data together, we generated an inducible bioluminescent EMT reporter that can detect the baseline levels and changes in the S100A4 expression. The model can be potentially used for giving a real-time read out of EMT/early stages of EMT and subsequently for testing novel drugs targeted at the onset of EMT.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: WP Gynecology