Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445140
Title: Genetic events involved in bladder cancer progression
Author: Babalghith, Ahmad Omar
ISNI:       0000 0001 3434 6964
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2007
Availability of Full Text:
Access from EThOS:
Abstract:
Bladder cancer is one of the most common cancers of the genitourinary tract. Transitional cell carcinoma (TCC) of the bladder includes two disease categories. Approximately, 85% of TCC are superficial tumours and the remaining percentage is invasive at presentation. Transurethral resection of the superficial tumours is the standard treatment. High recurrence rate was reported in these tumours and approximately 30% developed invasive tumours. Thus, it is essential to establish and identify molecular markers, which predict recurrence and progression status of bladder cancer patients. This study was divided into three main parts. The first part of this study was to optimise the CGH technique for DNA, extracted from bladder cancer cell lines and tissues. Since the origin of DNA used in CGH is crucial, different optimisation steps were investigated. Labelling of DNA by nick translation was determined to be 45 minutes for cell lines, while 20 minutes was sufficient for DNA extracted from tissues. Then probe mix preparation from cell lines was determined to be 800 ng of green probe and 400 ng of red probe, while in tissue 1600 ng of both probes were shown to have the best hybridisation signals. Denaturation time was the target in optimisation of CGH; denaturation of the human metaphase chromosome for 7 minutes produced the best fluorescent signals. Hybridisation for 6 days showed identical results between cell lines and tissues. In addition, washing the metaphase chromosomes to remove unbounded probes was determined to be 10 seconds for both cell lines and tissues. Furthermore, CGH was tested using DNA with known genetic aberrations and CGH was able to detect these aberrations.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.445140  DOI: Not available
Share: