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Evaluation of metabolic alterations in patient plasma associated with disease aggressiveness in prostate cancer
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Computational Life Science Cluster (CLiC))
Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Urology and Andrology.
Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

GC-MS was used for the study of plasma metabolite profiles in prostate cancer patients. Multivariate analysis of the acquired data revealed metabolites and metabolite patterns associated with prostate cancer disease progression from benign disease to distant metastases. Moreover, by evaluation of plasma metabolite patterns before and after radical prostatectomy differences associated with biochemical relapse was detected. Specifically we found two unidentified plasma metabolites which showed decreased plasma levels with increased disease progression and, furthermore, increased plasma levels post compared to pre surgery in patients who later experienced biochemical relapse. We hypothesize that those metabolites are consumed by aggressive tumors more than by indolent tumors. Identification of those metabolites are hence crucial, and under-way, in order to enable biological interpretation of the results. We further hypothesized that any tumor-derived metabolite secreted into plasma would show increased concentrations with increased PCa risk. Notably we did not detect any such metabolite, but only a few metabolites which showed increased plasma concentrations in patients with metastases compared to patients with benign disease and low risk PCa. In addition, verification of metabolite markers for metastatic disease detected previously by us and others was made, and included decreased plasma levels of stearic acid and increased levels of pseudouridine with metastatic disease.

National Category
Other Medical Sciences not elsewhere specified
URN: urn:nbn:se:umu:diva-50972OAI: diva2:471649
Available from: 2012-01-02 Created: 2012-01-02 Last updated: 2012-01-04Bibliographically approved
In thesis
1. Multivariate profiling of metabolites in human disease: Method evaluation and application to prostate cancer
Open this publication in new window or tab >>Multivariate profiling of metabolites in human disease: Method evaluation and application to prostate cancer
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

There is an ever increasing need of new technologies for identification of molecular markers for early diagnosis of fatal diseases to allow efficient treatment. In addition, there is great value in finding patterns of metabolites, proteins or genes altered in relation to specific disease conditions to gain a deeper understanding of the underlying mechanisms of disease development. If successful, scientific achievements in this field could apart from early diagnosis lead to development of new drugs, treatments or preventions for many serious diseases.  Metabolites are low molecular weight compounds involved in the chemical reactions taking place in the cells of living organisms to uphold life, i.e. metabolism. The research field of metabolomics investigates the relationship between metabolite alterations and biochemical mechanisms, e.g. disease processes. To understand these associations hundreds of metabolites present in a sample are quantified using sensitive bioanalytical techniques. In this way a unique chemical fingerprint is obtained for each sample, providing an instant picture of the current state of the studied system. This fingerprint or picture can then be utilized for the discovery of biomarkers or biomarker patterns of biological and clinical relevance.

In this thesis the focus is set on evaluation and application of strategies for studying metabolic alterations in human tissues associated with disease. A chemometric methodology for processing and modeling of gas chromatography-mass spectrometry (GC-MS) based metabolomics data, is designed for developing predictive systems for generation of representative data, validation and result verification, diagnosis and screening of large sample sets.

The developed strategies were specifically applied for identification of metabolite markers and metabolic pathways associated with prostate cancer disease progression. The long-term goal was to detect new sensitive diagnostic/prognostic markers, which ultimately could be used to differentiate between indolent and aggressive tumors at diagnosis and thus aid in the development of personalized treatments. Our main finding so far is the detection of high levels of cholesterol in prostate cancer bone metastases. This in combination with previously presented results suggests cholesterol as a potentially interesting therapeutic target for advanced prostate cancer. Furthermore we detected metabolic alterations in plasma associated with metastasis development. These results were further explored in prospective samples attempting to verify some of the identified metabolites as potential prognostic markers.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet, 2012. 43 p.
metabolite profiling, metabolomics, predictive metabolomics, mass spectrometry, GC-MS, biomarkers, chemometrics, design of experiments, multivariate data analysis, prostate cancer, bone metastases, plasma
National Category
Other Medical Sciences not elsewhere specified
Research subject
biological chemistry
urn:nbn:se:umu:diva-50968 (URN)978-91-7459-344-0 (ISBN)
Public defence
2012-01-27, KBC-huset, KB3B1, Umeå universitet, Umeå, 10:00 (Swedish)
Available from: 2012-01-04 Created: 2012-01-02 Last updated: 2012-01-11Bibliographically approved

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Thysell, ElinStattin, PärWikström, PernillaAntti, Henrik
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