NMR-based metabolomics: global analysis of metabolites to address problems in prostate cancer

Roberts, Matthew J., Schirra, Horst, Lavin, Martin F. and Gardiner, Robert A. (2014). NMR-based metabolomics: global analysis of metabolites to address problems in prostate cancer. In iConcept Press (Ed.), Cervical, Breast and Prostate Cancer (pp. 1-43) Tokwawan, Kowloon, Hong Kong: iConcept Press.

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Author Roberts, Matthew J.
Schirra, Horst
Lavin, Martin F.
Gardiner, Robert A.
Title of chapter NMR-based metabolomics: global analysis of metabolites to address problems in prostate cancer
Title of book Cervical, Breast and Prostate Cancer
Place of Publication Tokwawan, Kowloon, Hong Kong
Publisher iConcept Press
Publication Year 2014
Sub-type Research book chapter (original research)
Year available 2014
ISBN 9781922227720
Editor iConcept Press
Start page 1
End page 43
Total pages 43
Collection year 2015
Language eng
Formatted Abstract/Summary
Cancer significantly contributes to the worldwide burden of disease and premature death across many countries. Consequently, current oncology research focuses on discovering and validating new biomarkers to improve early detection. These efforts are of worldwide importance in detecting significant cancer while it is still localised and in lessening associated morbidities and death.

Biomarkers have mostly been sourced from non- or minimally invasive biofluids, such as blood, urine, and biopsy tissue. Traditionally, biomarkers were limited to circulating end-products of altered cellular function in cancer. However, technology advances and emergence of the –omics sciences have improved analysis of genes, gene expression, proteins and metabolites alike – on both an individual and system-wide scale. This field of research, termed “systems biology”, has allowed for molecules at all levels of the cellular hierarchy to be considered as biomarkers. Continuous improvements in sensitivity, resolution and precision of these analytical techniques produces large datasets, allowing for simultaneous characterisation of, ideally all, compounds in a single sample. Subsequent statistical analysis of these datasets and their interpretation with respect to cellular function is the basis of the different -omics technologies, such as genomics, transcriptomics, proteomics and metabolomics.

In this chapter, we will describe principles and processes that are involved in investigating biological or clinical problems with nuclear magnetic resonance (NMR)-based metabolomics - an approach that involves the global analysis of metabolites. In writing for the scope of this book, we have broken this chapter into three sections: First we will describe and illustrate the methods commonly used in NMRbased metabolomics, including spectral processing, data treatment and subsequent statistical analysis. Secondly, we will use prostate cancer (PCa) as a case study to illustrate how NMR-based metabolomics can be applied to a clinical problem. PCa is the second most common type of cancer and the sixth leading cause of cancer-related death worldwide (Center et al., 2012; Ferlay et al., 2010; Siegel et al., 2012). The diagnosis of prostate cancer is currently problematic for a number of reasons that include lack of sensitive and specific tumour markers as well as limitations due to morbidity inherent with the biopsy diagnosis process. Furthermore, many patients harbour early prostate cancer with insignificant tumours that may not progress to produce clinical problems. Lastly, we will briefly outline the future directions for the role of NMR-based metabolomics, including personalized medicine and integration with other –omics datasets, in order to create a holistic, systems biology approach to solving clinical problems.

Outlining the processes, applications and potential of metabolomics will be of assistance to biostatisticians and bioinformaticians who may be interested in expanding into this area of research. Similarly, we aim to inspire scientists and clinicians who are interested in applying this approach to a scientific or clinical problem.
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Created: Tue, 10 Dec 2013, 10:23:51 EST by Roheen Gill on behalf of UQ Centre for Clinical Research