MRS-based Metabolomics in Cancer Research

• Published in: Magnetic Resonance Insights Vol. 2014; no. 2014; pp. 1 - 14
• Main Authors: Tedros, Bezabeh, Ijare, Omkar B., Nikulin, Alexander E., Somorjai, Rajmund L., Smith, Ian C.P.
• Format: Journal Article Book Review
• Language: English
• Published: London, England Libertas Academica 01.01.2014; SAGE Publishing; SAGE Publications; Sage Publications Ltd. (UK); Sage Publications Ltd
• Subjects: Cancer research; Diagnostic imaging; Engineering research; Innovations; Metabolomics; Nuclear magnetic resonance spectroscopy; Review; diagnosis; magnetic resonance spectroscopy; cancer; classification; metabolomics
• ISSN: 1178-623X; 1178-623X
• DOI: 10.4137/MRI.S13755

Metabolomics is a relatively new technique that is gaining importance very rapidly. MRS-based metabolomics, in particular, is becoming a useful tool in the study of body fluids, tissue biopsies and whole organisms. Advances in analytical techniques and data analysis methods have opened a new opportunity for such technology to contribute in the field of diagnostics. In the MRS approach to the diagnosis of disease, it is important that the analysis utilizes all the essential information in the spectra, is robust, and is non-subjective. Although some of the data analytic methods widely used in chemical and biological sciences are sketched, a more extensive discussion is given of a 5-stage Statistical Classification Strategy. This proposes powerful feature selection methods, based on, for example, genetic algorithms and novel projection techniques. The applications of MRS-based metabolomics in breast cancer, prostate cancer, colorectal cancer, pancreatic cancer, hepatobiliary cancers, gastric cancer, and brain cancer have been reviewed. While the majority of these applications relate to body fluids and tissue biopsies, some in vivo applications have also been included. It should be emphasized that the number of subjects studied must be sufficiently large to ensure a robust diagnostic classification. Before MRS-based metabolomics can become a widely used clinical tool, however, certain challenges need to be overcome. These include manufacturing user-friendly commercial instruments with all the essential features, and educating physicians and medical technologists in the acquisition, analysis, and interpretation of metabolomics data.