Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery

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.

Figures

Figure 1

Workflow of samples in the METAcancer project. Tissue samples were analyzed in parallel with mass spectrometry (GC-MS and LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. The metabolic profiles were linked to the analysis of mRNA markers and protein markers. DASL, cDNA-mediated annealing, selection, extension, and ligation assay; FFPE, formalin-fixed, paraffin-embedded; RT- PCR, reverse transcriptase PCR; TMA, tissue microarray.

Figure 2

Simplified schema of major metabolic fluxes in (a) aerobic non-malignant cells and (b) hypoxic tumor cells of breast carcinoma. Thickness of arrows and bold text indicate relative intensity of fluxes. CL, citrate lyase; CS, citrate synthase; IDH1, isocitrate dehydrogenase 1; PDH, pyruvate dehydrogenase. According to Metallo et al. [21], the increased flux from glutamine into the Krebs cycle by mutation of IDH1 provides the acetyl-CoA for lipid biosynthesis under hypoxic conditions, because most pyruvate in cancer cells is converted to lactate. Increase in flux through the pentose phosphate pathway delivers ribose-5-phosphate needed for DNA synthesis and NADPH required for lipid biosynthesis. Conversely, less NADH is produced through pyruvate dehydrogenase or the Krebs cycle, as mitochondrial respiration for ATP production is less favored.

Figure 3

Heat map derived from the GCTOF MS metabolomics dataset comparing 289 tumor samples and 15 normal samples[14]. Metabolites are plotted on the y-axis and samples on the x-axis. Data were log2-transformed and median centered in a metabolite-wise manner. Blue indicates data points with a value smaller than the median of the respective metabolite and red indicates higher values. The hierarchical clustering reveals that the measured metabolites can separate normal and cancer tissues. Only two cancer samples cluster together with the normal samples, and one normal sample behaves as an outlier.

Figure 4

Overview of the analysis of lipid metabolism in breast tumors. Using LC-MS, lipidomic profiles were measured in breast tumor, and these profiles were linked to analysis of key enzymes by immunohistochemistry (IHC) in corresponding tumor tissue samples. From an in silico analysis of candidate lipid pathways, siRNA knockdown experiments were designed to evaluate the function of these lipid-metabolizing enzymes for breast cancer proliferation and apoptosis. The detailed results of this part of the project have already been published [8].