Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511423
Title: Tumour chemo sensitivity assays : an investigation into the susceptibility of cells to chemotherapeutics
Author: Gill, Susan Catherine
Awarding Body: Nottingham Trent University
Current Institution: Nottingham Trent University
Date of Award: 2009
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Abstract:
To evaluate and identify new candidate cancer drug targets, there is an ongoing need for a reliable, sensitive and quantitative assay that enables the analysis of larger numbers of compounds in preclinical research. This thesis has developed, and optimized a sensitive enzyme-release assay for monitoring natural cytotoxicity. It measures the release of the intracellular enzyme adenylate kinase into the culture supernatant after membrane rupture and is evaluated as an indicator of cell death. This assay was proven to correlate and compete with currently used methodologies for the assessment of cytotoxicity and with its superior sensitivity; convenience and in expense, it should be applicable to the study of other cytotoxicity reactions. The resulting ToxiLight® kit is now being sold world-wide and rapidly became the top selling product for Lonza Bio Science with many references to its use in publications. It was proven from this investigation that to truly comprehend the effect a cytotoxic drug has on cells, two assays are required in combination; one to measure cytotoxicity and a second to measure viability. The two most sensitive kits tested in this study, the ViaLight® Plus assay and the newly designed ToxiLight® assay were used in combination to monitor the effect of commonly used cytotoxicity drugs on melanoma cells. It was hoped to find both a sensitive and resistant cell line for further analysis by MALDI-MS. The study revealed how cells of the same histological and tissue type can respond differently to the same anticancer drug with one cell line revealing cell death after treatment and another remaining unaffected. This is representative of how individual patients may respond differently to the treatments given in vitro and explains the vast biochemical heterogeneity of tumour cells and the complexity involved in developing anticancer drugs that will specifically kill tumours arising from a given cell. The primary melanoma cells used for the research were representative of the clinical situation and were a kind gift from the OYSTER (Outcome and Impact of Specific Treatment in European Research in melanoma) tissue bank; with the established cell lines obtained from ESTDAB. A selection of three of these cell lines (Ma Mel 28, Ma Mel 26a and MEWO) were chosen after investigating their sensitive/resistant nature to certain chemotherapeutic drugs and were further investigated with a novel agent currently in its early stages of drug trials, the histone deacetylase inhibitor, trichostatin A. To investigate this resistance further, MALDI-MS was performed on the chosen melanoma cell lysates. The results demonstrated that good quality proteomic data could be achieved from cell lines and that it is possible to generate discriminatory protein profiles that correlate with the cytotoxicity assays when analysed using artificial neural networks (ANNs). Through the analysis of the proteome the ANNs was able to train itself using the raw dataset from the MALDI-MS analysis and distinguish differences between those samples that were drug-treated and those that were left untreated. The differences between the two classes of treated and untreated cells revealed biomarkers that may correlate to cell death and thus the effect of the drug trichostatin A. These findings could lead to the discovery of proteins that are up regulated when a patient is responding to therapy. This could be of prognostic and therapeutic benefit to patients enabling them to find out in the early stages of treatment if they are responding to a given treatment; the long term outcome leading to personalised treatments for individuals in which a decision can be made on the best suited treatment.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.511423  DOI: Not available
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