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Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry. / Julia Grassl

Swansea University Author: Julia Grassl

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...

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Published: 2007
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
URI: https://cronfa.swan.ac.uk/Record/cronfa42525
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first_indexed 2018-08-02T18:54:55Z
last_indexed 2019-10-21T16:47:59Z
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spelling 2018-08-29T14:39:59.5878558 v2 42525 2018-08-02 Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry. b16c32413ff3cececbd491c9a17bbd63 NULL Julia Grassl Julia Grassl true true 2018-08-02 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. E-Thesis Medicine.;Oncology. 31 12 2007 2007-12-31 COLLEGE NANME Swansea University Medical School COLLEGE CODE Swansea University Doctoral Ph.D 2018-08-29T14:39:59.5878558 2018-08-02T16:24:29.5561973 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Julia Grassl NULL 1 0042525-02082018162501.pdf 10805274.pdf 2018-08-02T16:25:01.3670000 Output 36873242 application/pdf E-Thesis true 2018-08-02T16:25:01.3670000 false
title Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry.
spellingShingle Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry.
Julia Grassl
title_short Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry.
title_full Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry.
title_fullStr Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry.
title_full_unstemmed Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry.
title_sort Breast cancer serum proteomics: Sample processing and protein profiling by mass spectrometry.
author_id_str_mv b16c32413ff3cececbd491c9a17bbd63
author_id_fullname_str_mv b16c32413ff3cececbd491c9a17bbd63_***_Julia Grassl
author Julia Grassl
author2 Julia Grassl
format E-Thesis
publishDate 2007
institution Swansea University
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description 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.
published_date 2007-12-31T03:53:08Z
_version_ 1763752634975518720
score 11.037144

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