Despite significant advances in cancer treatment, clinical response remains suboptimal and there is a continued requirement for improved chemotherapeutics. The attrition rate for new therapies is high, due principally to lack of in vivo efficacy and poor pharmacodynamics. Consequently better systems are required to determine in vivo preclinical efficiency and drug-target interactions. Engineering of cancer cells to express fluorescent or bioluminescent proteins, either endogenously or under the control of specific gene promoters, and their detection by noninvasive optical imaging has the potential to improve preclinical drug development. In this study, a panel of colorectal cancer cell lines were engineered to express fluorescent and luminescent proteins either constitutively or under control of gene-promoters for the DNA damage response gene p53 or the cell cycle regulator p21, both important pharmacodynamic sensors. These cell lines were characterised for their potential as in vivo models of primary and metastatic tumour therapy response, several showing significant potential. In addition to the development of these models, this study also addressed the pharmacokinetics of different luciferase substrates and identified optimal temporal and dose characteristics for each. Furthermore, a new application for bioluminescent imaging was developed and validated for use in preclinical evaluation of vascular disrupting agents, a new generation of cancer therapeutic. This study demonstrates that despite the dynamic and variable nature of fluorescent and bioluminescent imaging, reproducible results can be obtained if appropriate precautions are taken. The models developed herein will expedite cancer drug development whilst reducing and refining the use of animals in research.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:546659 |
Date | January 2011 |
Creators | O'Farrell, Alice Claire |
Contributors | Shnyder, Steven D. : Gill, Jason H. : Bibby, Mike |
Publisher | University of Bradford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://hdl.handle.net/10454/5391 |
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