Breast cancer is the most frequent form of cancer in women and improved diagnostic methods are desirable. Malignant cells have altered metabolism and metabolic mapping might become a tool in cancer diagnostics. High-resolution magic angle spinning (HR MAS) MR spectroscopy of tissue biopsies provides detailed information on metabolic composition. The 600 MHz 1H HR MAS spectra were acquired of breast cancer tissue from 85 patients and adjacent non-involved tissue from 18 of these patients. Tissue specimens were investigated by microscopy after MR analysis. The resulting spectra were examined by three different approaches. Relative intensities of glycerophosphocholine (GPC), phosphocholine (PC) and choline were compared for cancerous and non-involved specimens. Eight metabolites, choline, creatine, beta-glucose, GPC, glycine, myo-inositol, PC and taurine, were quantified from the recorded spectra and compared with tumor histological type and size, patient's lymph node status and tissue composition of sample. The spectra were also compared with tumor histological type and size, lymph node status and tissue composition of samples using principal component analysis (PCA). Tumor samples could be distinguished from non-involved samples (82% sensitivity, 100% specificity) based on relative intensities of signals from GPC, PC and choline in 1H HR MAS spectra. Tissue concentrations of metabolites showed few differences between groups of samples, which can be caused by limitations in the quantification procedure. Choline and glycine concentrations were found to be significantly higher in tumors larger than 2 cm compared with smaller tumors. PCA of MAS spectra from patients with invasive ductal carcinomas indicated a possible prediction of spread to axillary lymph nodes. Metabolite estimates and PCA of MAS spectra were influenced by the percentage of tumor cells in the investigated specimens.

High-resolution magic angle spinning (HR MAS) may develop into a new diagnostic tool for studying intact tissue samples, and several types of cancer have been investigated with promising results. In this study HR MAS spectra of breast cancer tissue from 10 patients have been compared to conventional high-resolution spectra of perchloric acid extracts of the same tissue type. The HR MAS spectra show resolution comparable to spectra of extracts, and two-dimensional techniques lead to identification of a majority of the constituents. More than 30 different metabolites have been detected and assigned. To our knowledge this is the most detailed assignment of biochemical components in intact human breast tissue. The spectra of intact breast cancer tissue differ from perchloric acid extracts by the presence of lipids and fewer signals in the low field region. HR MAS analysis of intact breast tissue specimens is a rapid method, providing spectra with resolution where relative quantification of the majority of the detected metabolites is possible.

Triple-negative breast cancers (TNBC), characterized by absence of estrogen receptor (ER), progesterone receptor (PR) and lack of overexpression of human epidermal growth factor receptor 2 (HER2), are typically associated with poor prognosis, due to aggressive tumor phenotype(s), only partial response to chemotherapy and present lack of clinically established targeted therapies. Advances in the design of individualized strategies for treatment of TNBC patients require further elucidation, by combined 'omics' approaches, of the molecular mechanisms underlying TNBC phenotypic heterogeneity, and the still poorly understood association of TNBC with BRCA1 mutations. An overview is here presented on TNBC profiling in terms of expression signatures, within the functional genomic breast tumor classification, and ongoing efforts toward identification of new therapy targets and bioimaging markers. Due to the complexity of aberrant molecular patterns involved in expression, pathological progression and biological/clinical heterogeneity, the search for novel TNBC biomarkers and therapy targets requires collection of multi-dimensional data sets, use of robust multivariate data analysis techniques and development of innovative systems biology approaches.

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The goal of this study was to investigate the use of lactate and alanine as metabolic biomarkers of prostate cancer using 1