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Title: An investigation of telomerase-based diagnostic and therapeutic strategies in canine cancer
Author: Long, Sam Nicholas
ISNI:       0000 0001 3612 4556
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 2005
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Recent research has shown that dogs represent a potentially valuable model in which to investigate novel anti-cancer strategies, and are genetically more similar to humans than existing mouse models. In addition, telomerase activity in humans is more closely paralleled by telomerase activity in dogs than mice, adding to the value of this model. For these reasons, this thesis aims to investigate the telomerase as a diagnostic and therapeutic tool in canine cancer. Several large studies have shown that 85-90% of all human tumours possess telomerase activity. Brain tumours represent an important subset of these because of the debilitating symptoms associated with their effects and because survival rates for the most malignant subtype, glioblastoma muitiforme, remain unchanged despite advances in anticancer treatment strategies over the past thirty years. Their canine counterparts show strikingly similar features both at the histological and genomic levels, and for this reason offer an attractive model for the development of novel therapies. Given the ubiquity of telomerase activity in other tumour types, telomerase activity in human brain tumours has been extensively examined as a potential prognostic indicator. However, there appears to be a wide variation in the reported incidence of telomerase activity in brain tumours which is likely to be the result of problems associated with the methods used to date. Studies have suggested that methods detecting telomerase activity in situ may resolve some of these problems. For this reason, we set out to investigate the immunohistochemical detection of telomerase activity using a number of antibodies directed at TERT.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral