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.

Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients) with a high cancer content (mean: 61.8%) were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS) were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS). Multivariate analysis (PLS, PLS-DA) and absolute quantification (LCModel) were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30) and high grade (GS≥7, n = 81) cancer with normal adjacent tissue (n = 47). High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044) and citrate (p = 7.73·10−4), and an increase in the clinically applied (total choline+creatine+polyamines)/citrate (CCP/C) ratio (p = 2.17·10−4). The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71), and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS) within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.

The purpose of the study was to evaluate the use of metabolic phenotype, described by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS), as a tool for prediction of histological grade, hormone status, and axillary lymphatic spread in breast cancer patients. Biopsies from breast cancer (n = 91) and adjacent non-involved tissue (n = 48) were excised from patients (n = 77) during surgery. HR MAS MR spectra of intact samples were acquired. Multivariate models relating spectral data to histological grade, lymphatic spread, and hormone status were designed. The multivariate methods applied were variable reduction by principal component analysis (PCA) or partial least-squares regression-uninformative variable elimination (PLS-UVE), and modelling by PLS, probabilistic neural network (PNN), or cascade correlation neural network. In the end, model verification by prediction of blind samples (n = 12) was performed. Validation of PNN training resulted in sensitivity and specificity ranging from 83 to 100% for all predictions. Verification of models by blind sample testing showed that hormone status was well predicted by both PNN and PLS (11 of 12 correct), lymphatic spread was best predicted by PLS (8 of 12), whereas PLS-UVE PNN was the best approach for predicting grade (9 of 12 correct). MR-determined metabolic phenotype may have a future role as a supplement for clinical decision-making-concerning adjuvant treatment and the adaptation to more individualised treatment protocols.

Absolute quantitative measures of breast cancer tissue metabolites can increase our understanding of biological processes. Electronic REference To access In vivo Concentrations (ERETIC) was applied to high resolution magic angle spinning MR spectroscopy (HR MAS MRS) to quantify metabolites in intact breast cancer samples. The ERETIC signal was calibrated using solutions of creatine and TSP. The largest relative errors of the ERETIC method were 8.4%, compared to 4.4% for the HR MAS MRS method using TSP as a standard. The same MR experimental procedure was applied to intact tissue samples from breast cancer patients with clinically defined good (n ¼ 13) and poor (n ¼ 16) prognosis. All samples were examined by histopathology for relative content of different tissue types and proliferation index (MIB-1) after MR analysis. The resulting spectra were analyzed by quantification of tissue metabolites (b-glucose, lactate, glycine, myo-inositol, taurine, glycerophosphocholine, phosphocholine, choline and creatine), by peak area ratios and by principal component analysis. We found a trend toward lower concentrations of glycine in patients with good prognosis (1.1 mmol/g) compared to patients with poor prognosis (1.9 mmol/g, p ¼ 0.067). Tissue metabolite concentrations (except for b-glucose) were also found to correlate to the fraction of tumor, connective, fat or glandular tissue by Pearson correlation analysis. Tissue concentrations of b-glucose correlated to proliferation index (MIB-1) with a negative correlation factor (S0.45, p ¼ 0.015), consistent with increased energy demand in proliferating tumor cells. By analyzing several metabolites simultaneously, either in ratios or by metabolic profiles analyzed by PCA, we found that tissue metabolites correlate to patients' prognoses and health status five years after surgery. This study shows that the diagnostic and prognostic potential in MR metabolite analysis of breast cancer tissue is greater when combining multiple metabolites (MR Metabolomics).

Inflammatory cytokines seem to play a key role in mechanisms initiating labor. Since cytokine levels are higher in preterm than in term labor, it has been hypothesized that labor-inducing effects of cytokines are inhibited by an upregulated production of cytokine antagonists, such as soluble cytokine receptors, at early stages of gestation. In this study, TNF, IL-1, IL-6, IL-8 and soluble TNF receptors (sTNFRs) were measured in amniotic fluid samples from a) 39 women in premature labor, b) 25 women who where not in labor but delivered prematurely, and c) 33 women in term labor. Fifty-four of the placentas from premature deliveries were evaluated for presence of histological chorioamnionitis. Chorioamnionitis was associated with increased levels of TNF, IL-1 and IL-6, whereas elevated IL-1, IL-6 and IL-8 concentrations were found in premature parturition with no signs of infection. Concentrations of sTNFR were lower in preterm than in term deliveries. The present study confirms the participation of inflammatory cytokines in parturition. Multivariate analysis suggests a dominant, role of IL-1 in the presence of chorioamnionitis, whereas IL-6 seems to be more important during idiopathic premature labor. TNFR data do not support the hypothesis that production of cytokine antagonists is upregulated prematurely to prevent partirution.

We present a safe and standardized method for procurement of a high quality fresh frozen prostate slice, suitable for gene expression analysis and MR spectroscopy.

Paraffin-embedded tissue is an important source of material for molecular pathology and genetic investigations. We used DNA isolated from microdissected formalin-fixed, paraffin-embedded gastric tumors for mutation analysis of a region of the human gene for uracil-DNA glycosylase (UNG), encoding the UNG catalytic domain, and detected apparent base substitutions which, after further investigation, proved to be polymerase chain reaction (PCR) artifacts. We demonstrate that low DNA template input in PCR can generate false mutations, mainly guanine to adenine transitions, in a sequence-dependent manner. One such mutation is identical to a mutation previously reported in the UNG gene in human glioma. This phenomenon was not caused by microheterogeneity in the sample material because the same artifact was seen after amplification of a homogenous, diluted plasmid. We did not observe genuine mutations in the UNG gene in 16 samples. Our results demonstrate that caution should be taken when interpreting data from PCR-based analysis of somatic mutations using low amounts of template DNA, and that methods used to enrich putative subpopulations of mutant molecules in a sample material could, in essence, be a further amplification of sequence-dependent PCR-generated artifacts.

Purpose: Low concentrations of citrate and high concentrations of choline-containing compounds (ChoCC) are metabolic characteristics observed by magnetic resonance spectroscopy of prostate cancer tissue. The objective was to investigate the gene expression changes underlying these metabolic aberrations to find regulatory genes with potential for targeted therapies.Experimental design: Fresh frozen samples (n ¼ 133) from 41 patients undergoing radical prostatectomy were included. Histopathologic evaluation was carried out for each sample before a metabolic profile was obtained with high-resolution magic angle spinning (HR-MAS) spectroscopy. Following the HR-MAS, RNA was extracted from the same sample and quality controlled before carrying out microarray gene expression profiling. A partial least square statistical model was used to integrate the data sets to identify genes whose expression show significant covariance with citrate and ChoCC levels.Results: Samples were classified as benign, n ¼ 35; cancer of low grade (Gleason score 6), n ¼ 24; intermediate grade (Gleason score 7), n ¼ 41; or high grade (Gleason score !8), n ¼ 33. RNA quality was high with a mean RNA Integrity Number score of 9.1 (SD 1.2). Gene products predicting significantly a reduced citrate level were acetyl citrate lyase (ACLY, P ¼ 0.003) and m-aconitase (ACON, P < 0.001). The two genes whose expression most closely accompanied the increase in ChoCC were those of phospholipase A2 group VII (PLA2G7, P < 0.001) and choline kinase a (CHKA, P ¼ 0.002).Conclusions: By integrating histologic, transcriptomic, and metabolic data, our study has contributed to an expanded understanding of the mechanisms underlying aberrant citrate and ChoCC levels in prostate cancer.