Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.752053
Title: Breast cancer serum proteomics : sample processing and protein profiling by mass spectrometry
Author: Grassl, Julia
Awarding Body: Swansea University
Current Institution: Swansea University
Date of Award: 2007
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Abstract:
The aim of this project was to develop a method for discovery of biomarkers or a protein pattern, as a signature of breast cancer. Early detection of breast cancer is crucial to increase the survival rates of patients. Little was published about biomarker discovery from serum using mass spectrometry, so over the course of the project each factor of the methodology was analysed and optimized. It was shown that standardisation of sample preparation and handling is critical for any quantitative study. The presence of albumin and other highly abundant proteins in serum interferes with proteomic analysis and so depletion techniques were investigated. Centrifugal ultrafiltration was optimised and an extensive study showed it to be a robust and efficient method to enrich the LMW proteome for subsequent biomarker discovery in serum. SELDI-ToF and MALDI-ToF MS were compared for intact protein profiling for breast cancer. In contrast to SELDI-ToF, MALDI-ToF MS had been little tested for this purpose and therefore new software was developed for peak alignment enabling comparison of multiple spectra. LMW serum samples from 8 breast cancer and 8 control individuals were analysed in each experiment. Here we detected seven potential markers in total and gained initial peptide identifications for three markers. This study also tested the use of label-free quantitation using LC-MS on serum samples from breast cancer patients; one differentially-expressed peptide was discovered. The lack of a software tool for comparison of the resulting spectra limited the detection of further markers. The profiling results showed that the use of replicates all the way from starting with the initial serum sample through to data retrieval is crucial due to variation between the biological replicates, and also to reduce any variation occurring from sample preparation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.752053  DOI: Not available
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