Title |
Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery
|
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Published in |
Genome Medicine, April 2012
|
DOI | 10.1186/gm336 |
Pubmed ID | |
Authors |
Carsten Denkert, Elmar Bucher, Mika Hilvo, Reza Salek, Matej Orešič, Julian Griffin, Scarlet Brockmöller, Frederick Klauschen, Sibylle Loibl, Dinesh Kumar Barupal, Jan Budczies, Kristiina Iljin, Valentina Nekljudova, Oliver Fiehn |
Abstract |
Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development. |
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Geographical breakdown
Country | Count | As % |
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India | 2 | <1% |
United States | 2 | <1% |
Spain | 2 | <1% |
Malaysia | 1 | <1% |
Italy | 1 | <1% |
Brazil | 1 | <1% |
South Africa | 1 | <1% |
Germany | 1 | <1% |
Costa Rica | 1 | <1% |
Other | 7 | 3% |
Unknown | 200 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 50 | 23% |
Researcher | 49 | 22% |
Student > Master | 23 | 11% |
Student > Bachelor | 16 | 7% |
Other | 11 | 5% |
Other | 37 | 17% |
Unknown | 33 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 64 | 29% |
Biochemistry, Genetics and Molecular Biology | 35 | 16% |
Medicine and Dentistry | 34 | 16% |
Chemistry | 16 | 7% |
Engineering | 9 | 4% |
Other | 22 | 10% |
Unknown | 39 | 18% |