The metabolic profile of breast cancer
Metabolomics is the study of all metabolites in a cell or organism. Small changes in enzyme concentrations or activities can lead to large changes in metabolite levels. Such alterations could be used to classify different cancer types as well as identify new prognostic and predictive markers. The EU-funded 'Identification and validation of new breast cancer biomarkers based on integrated metabolomics' (METACANCER) project utilised state-of-the-art metabolic profiling in its study of human breast cancer. Given the high incidence of this cancer in women, the outcome of the METACANCER study has important ramifications for prompt tumour diagnosis and treatment. As a first step, project partners selected different metabolomics approaches suitable for the analysis of fresh-frozen human tumour tissue. These methods are nuclear magnetic resonance (NMR) spectroscopy, gas chromatography-mass spectrometry (GC-MS) and liquid-chromatography-MS (LC-MS). Several hundreds of metabolites were evaluated to detect metabolic differences between normal and malignant breast tissue. This was used to construct a metabolite-based testing approach for classifying breast cancer with sensitivity and specificity over 93 %. NMR data on metabolites successfully separated different types and grades of breast cancer, as well as molecular subtypes based on the oestrogen receptor (ER), progesterone receptor (PR) and Her2 expression. This clearly indicated that tumour metabolomics could provide useful information on biomarkers and biological pathways in different types of tissue. The metabolomic information was combined with proteomic and functional genomic data from the same samples. By focusing on certain relevant enzymes in breast cancer cohorts and functional models, researchers were able to link the metabolic alterations to changes in protein and gene expression. Key enzymes of lipid biosynthesis, such as glycerol-3-phosphate acyltransferase (GPAM) that led to changes in the lipid profiles of different cancer grades were also identified. Tools such as MetaMapp and METAtarget were developed for analysis of the metabolomics data with respect to structural and functional changes in the cell. Metabolic alterations in breast cancer tissue were envisaged to provide essential biological information regarding tumour onset and progression. Personalised cancer treatment is largely dependent on accurate information for early diagnosis and effective treatment.
