Changes of inflammation in patients with psoriatic arthritis after high intensity interval training assessed by ultrasound and MRI, a randomized controlled trial.

BACKGROUND: In psoriatic arthritis (PsA) there is a theoretical risk of increased disease activity related to strenuous physical activity, including exercise. We evaluated the effect of high intensity interval training (HIIT) on objective measures of inflammation in PsA assessed by ultrasound (US) of peripheral joints and entheses, and by bone marrow edema (BME) on MRI of the sacroiliac joints (SIJ) and spine. METHODS: We randomly assigned 67 PsA patients to an intervention group that performed structured HIIT for 11 weeks, or to a control group instructed not to change their physical exercise habits. Outcome measures included US evaluation of the total cohort and MRI in a subgroup of 41; both assessed at 3 months. We calculated the proportions with an increased US B-mode and power-doppler (PD) signal of joints and entheses and Spondyloarthritis-Research-Consortium-of-Canada (SPARCC)-BME score of the SIJ and spine for both groups. RESULTS: Proportions with an increased US B-mode score of the joints were 32% and 28% in HIIT and control groups, respectively. Corresponding proportions of PD scores of the joints were 7% and 10% and PD scores of entheses were 32% and 31%. The proportions with increased MRI BME of the SIJ were 6% in the HIIT group and 10% in the control group. Corresponding proportions were 6% and 5% for the MRI BME of the spine. CONCLUSION: In PsA patients with a low to moderate disease activity, there was no clear evidence of objectively measured increased inflammation after HIIT, as evaluated by US and MRI. TRIAL REGISTRATION: ClinicalTrials.gov NCT02995460 (16/12/2016).

Feasibility of contrast-enhanced MRI derived textural features to predict overall survival in locally advanced breast cancer.

BACKGROUND: The prognosis for women with locally advanced breast cancer (LABC) is poor and there is a need for better treatment stratification. Gray-level co-occurrence matrix (GLCM) texture analysis of magnetic resonance (MR) images has been shown to predict pathological response and could become useful in stratifying patients to more targeted treatments. PURPOSE: To evaluate the ability of GLCM textural features obtained before neoadjuvant chemotherapy to predict overall survival (OS) seven years after diagnosis of patients with LABC. MATERIAL AND METHODS: This retrospective study includes data from 55 patients with LABC. GLCM textural features were extracted from segmented tumors in pre-treatment dynamic contrast-enhanced 3-T MR images. Prediction of OS by GLCM textural features was assessed and compared to predictions using traditional clinical variables. RESULTS: Linear mixed-effect models showed significant differences in five GLCM features (f1, f2, f5, f10, f11) between survivors and non-survivors. Using discriminant analysis for prediction of survival, GLCM features from 2 min post-contrast images achieved a classification accuracy of 73% (P < 0.001), whereas traditional prognostic factors resulted in a classification accuracy of 67% (P = 0.005). Using a combination of both yielded the highest classification accuracy (78%, P < 0.001). Median values for features f1, f2, f10, and f11 provided significantly different survival curves in Kaplan-Meier analysis. CONCLUSION: This study shows a clear association between textural features from post-contrast images obtained before neoadjuvant chemotherapy and OS seven years after diagnosis. Further studies in larger cohorts should be undertaken to investigate how this prognostic information can be used to benefit treatment stratification.

Urinary detection of corticosteroid in topical treatment of skin disease by 19F MRS.

OBJECTIVE: To investigate if it was feasible to quantify the renal excretion of topically applied corticosteroids by 19F MRS. MATERIALS AND METHODS: Five participants, one healthy and four with skin diseases, were treated with ointment containing betamethasone 17-valerate. Urine samples were collected for up to 87 h after the initial application. A sample of ointment mixed with urine served as a study control. Organic fractions were obtained after sample freeze drying, and resolved in deuterated chloroform prior to acquisition of 19F MR spectra at 470 MHz for typically 8 h. RESULTS: We detected fluorine signals in 40 of the 62 fractions of organic extracts. The corticosteroid was detected in samples from all patients, ranging from 0.1 to 2.8% of the applied steroid. No fluorine signal was obtained in samples from the healthy volunteer. DISCUSSION: 19F MRS can be utilized to detect topically applied corticosteroids in urine. However, more work is required to optimize and control for extraction procedures, complete spectral assignments and reliable quantification.

Quantifying bone marrow inflammatory edema in the spine and sacroiliac joints with thresholding.

BACKGROUND: Psoriatic Arthritis (PsA) is a chronic inflammatory arthritis that develops in patients with psoriasis. Inflammatory edema in the spine may reflect subclinical disease activity and be a predictor of radiographic progression. A semi-quantitative method established by the spondyloarthritis research consortium of Canada (SPARCC) is commonly used to assess the disease activity in MR images of the spine. This study aims to evaluate thresholding for quantification of subtle bone marrow inflammation in the spine and the sacroiliac (SI) joints of patients with PsA and compare it with the SPARCC scoring system. METHODS: Short tau inversion recovery (STIR) MR images of the spine (N = 85) and the SI joints (N = 95) of patients with PsA (N = 41) were analyzed. A threshold was applied to visible bone marrow in order to mask areas with higher signal intensity, which are consistent with inflammation. These areas were considered as inflammatory lesions. The volume and relative signal intensity of the lesions were calculated. Results from thresholding were compared to SPARCC scores using linear mixed-effects models. The specificity and sensitivity of thresholding were also calculated. RESULTS: A significant positive correlation between the volumes and mean relative signal intensities, which were calculated by thresholding analysis, and the SPARCC scores was detected for both spine (p < 0.001) and SI joints (p < 0.001). For the spine, thresholding had sensitivity and specificity of 83% and 76% respectively, while for the SI joints the values were 51% and 88% respectively. CONCLUSIONS: Thresholding allows quantification of subtle bone marrow inflammatory edema in patients with psoriatic arthritis, and could support SPARCC scoring of the spine. Improved image processing and inclusion of automatic segmentation are required for thresholding of STIR images to become a rapid and reliable method for quantitative measures of inflammation. TRIAL REGISTRATION: NCT02995460 (December 14, 2016) - Retrospectively registered.

Interplay of choline metabolites and genes in patient-derived breast cancer xenografts.

INTRODUCTION: Dysregulated choline metabolism is a well-known feature of breast cancer, but the underlying mechanisms are not fully understood. In this study, the metabolomic and transcriptomic characteristics of a large panel of human breast cancer xenograft models were mapped, with focus on choline metabolism. METHODS: Tumor specimens from 34 patient-derived xenograft models were collected and divided in two. One part was examined using high-resolution magic angle spinning (HR-MAS) MR spectroscopy while another part was analyzed using gene expression microarrays. Expression data of genes encoding proteins in the choline metabolism pathway were analyzed and correlated to the levels of choline (Cho), phosphocholine (PCho) and glycerophosphocholine (GPC) using Pearson's correlation analysis. For comparison purposes, metabolic and gene expression data were collected from human breast tumors belonging to corresponding molecular subgroups. RESULTS: Most of the xenograft models were classified as basal-like (N = 19) or luminal B (N = 7). These two subgroups showed significantly different choline metabolic and gene expression profiles. The luminal B xenografts were characterized by a high PCho/GPC ratio while the basal-like xenografts were characterized by highly variable PCho/GPC ratio. Also, Cho, PCho and GPC levels were correlated to expression of several genes encoding proteins in the choline metabolism pathway, including choline kinase alpha (CHKA) and glycerophosphodiester phosphodiesterase domain containing 5 (GDPD5). These characteristics were similar to those found in human tumor samples. CONCLUSION: The higher PCho/GPC ratio found in luminal B compared with most basal-like breast cancer xenograft models and human tissue samples do not correspond to results observed from in vitro studies. It is likely that microenvironmental factors play a role in the in vivo regulation of choline metabolism. Cho, PCho and GPC were correlated to different choline pathway-encoding genes in luminal B compared with basal-like xenografts, suggesting that regulation of choline metabolism may vary between different breast cancer subgroups. The concordance between the metabolic and gene expression profiles from xenograft models with breast cancer tissue samples from patients indicates that these xenografts are representative models of human breast cancer and represent relevant models to study tumor metabolism in vivo.

Metabolic changes in psoriatic skin under topical corticosteroid treatment.

BACKGROUND: MR spectroscopy of intact biopsies can provide a metabolic snapshot of the investigated tissue. The aim of the present study was to explore the metabolic pattern of uninvolved skin, psoriatic skin and corticosteroid treated psoriatic skin. METHODS: The three types of skin biopsy samples were excised from patients with psoriasis (N = 10). Lesions were evaluated clinically, and tissue biopsies were excised and analyzed by one-dimensional 1H MR spectroscopy. Relative levels were calculated for nine tissue metabolites. Subsequently, relative amounts of epidermis, dermis and subcutaneous tissue were scored by histopathological evaluation of HES stained sections. RESULTS: Seven out of 10 patients experienced at least 40% reduction in clinical score after corticosteroid treatment. Tissue biopsies from psoriatic skin contained lower levels of the metabolites myo-inositol and glucose, and higher levels of choline and taurine compared to uninvolved skin. In corticosteroid treated psoriatic skin, tissue levels of glucose, myo-inositol, GPC and glycine were increased, whereas choline was reduced, in patients with good therapeutic effect. These tissue levels are becoming more similar to metabolite levels in uninvolved skin. CONCLUSION: This MR method demonstrates that metabolism in psoriatic skin becomes similar to that of uninvolved skin after effective corticosteroid treatment. MR profiling of skin lesions reflect metabolic alterations related to pathogenesis and treatment effects.

Lactate and glycine-potential MR biomarkers of prognosis in estrogen receptor-positive breast cancers.

Breast cancer is a heterogeneous disease with a variable prognosis. Clinical factors provide some information about the prognosis of patients with breast cancer; however, there is a need for additional information to stratify patients for improved and more individualized treatment. The aim of this study was to examine the relationship between the metabolite profiles of breast cancer tissue and 5-year survival. Biopsies from breast cancer patients (n=98) were excised during surgery and analyzed by high-resolution magic angle spinning MRS. The data were analyzed by multivariate principal component analysis and partial least-squares discriminant analysis, and the findings of important metabolites were confirmed by spectral integration of the metabolite peaks. Predictions of 5-year survival using metabolite profiles were compared with predictions using clinical parameters. Based on the metabolite profiles, patients with estrogen receptor (ER)-positive breast cancer (n=71) were separated into two groups with significantly different survival rates (p=0.024). Higher levels of glycine and lactate were found to be associated with lower survival rates by both multivariate analyses and spectral integration, and are suggested as biomarkers for breast cancer prognosis. Similar metabolic differences were not observed for ER-negative patients, where survivors could not be separated from nonsurvivors. Predictions of 5-year survival of ER-positive patients using metabolite profiles gave better and more robust results than those using traditional clinical parameters. The results imply that the metabolic state of a tumor may provide additional information concerning breast cancer prognosis. Further studies should be conducted in order to evaluate the role of MR metabolomics as an additional clinical tool for determining the prognosis of patients with breast cancer.

Predicting long-term survival and treatment response in breast cancer patients receiving neoadjuvant chemotherapy by MR metabolic profiling.

PURPOSE: This study aimed to evaluate whether MR metabolic profiling can be used for prediction of long-term survival and monitoring of treatment response in locally advanced breast cancer patients during neoadjuvant chemotherapy (NAC). METHODS: High resolution magic angle spinning (HR MAS) MR spectra of pre- and post-treatment biopsies from 33 patients were acquired. Tissue concentrations of choline-containing metabolites (tCho), glycine and taurine were assessed using electronic reference to access in vivo concentration (ERETIC) of the signal and receiver operating characteristic (ROC) curves was used to define their potential to predict patient survival and treatment response. The metabolite profiles obtained by HR MAS spectroscopy were related to long-term survival and treatment response by genetic algorithm partial least squares discriminant analysis (GA PLS-DA). RESULTS: Different pre-treatment MR metabolic profiles characterized by higher levels of tCho and lower levels of lactate were observed in patients with long-term survival (≥5 years, survivors) compared to patients who died of cancer recurrence (<5 years, non-survivors). A significant decrease in glycerophosphocholine (GPC) post-treatment was associated with long-term survival (p = 0.046) and partial response (p = 0.014) to NAC. Long-term survival was best predicted by GPC using ROC analyses (sens. 66.7%, spec. 62.5%), while taurine had the best predictive value of treatment response (sens. 72.7%, spec. 63.2%). GA PLS-DA multivariate classification models successfully discriminated between survivors and non-survivors, resulting in 82.7% and 90.2% cross-validation (CV) classification accuracy, pre- and post-treatment, respectively. Classification of treatment response using GA PLS-DA was not successful for this patient cohort. CONCLUSIONS: Our results demonstrate that HR MAS MR metabolic profiles consisting of important metabolic characteristics of breast cancer tumors could potentially assist the classification and prediction of long-term survival in locally advanced breast cancer patients, in addition to being used as an adjunct for evaluation of treatment response to NAC.

Prognostic value of metabolic response in breast cancer patients receiving neoadjuvant chemotherapy.

BACKGROUND: Today's clinical diagnostic tools are insufficient for giving accurate prognosis to breast cancer patients. The aim of our study was to examine the tumor metabolic changes in patients with locally advanced breast cancer caused by neoadjuvant chemotherapy (NAC), relating these changes to clinical treatment response and long-term survival. METHODS: Patients (n = 89) participating in a randomized open-label multicenter study were allocated to receive either NAC as epirubicin or paclitaxel monotherapy. Biopsies were excised pre- and post-treatment, and analyzed by high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). The metabolite profiles were examined by paired and unpaired multivariate methods and findings of important metabolites were confirmed by spectral integration of the metabolite peaks. RESULTS: All patients had a significant metabolic response to NAC, and pre- and post-treatment spectra could be discriminated with 87.9%/68.9% classification accuracy by paired/unpaired partial least squares discriminant analysis (PLS-DA) (p < 0.001). Similar metabolic responses were observed for the two chemotherapeutic agents. The metabolic responses were related to patient outcome. Non-survivors (< 5 years) had increased tumor levels of lactate (p = 0.004) after treatment, while survivors (≥ 5 years) experienced a decrease in the levels of glycine (p = 0.047) and choline-containing compounds (p ≤ 0.013) and an increase in glucose (p = 0.002) levels. The metabolic responses were not related to clinical treatment response. CONCLUSIONS: The differences in tumor metabolic response to NAC were associated with breast cancer survival, but not to clinical response. Monitoring metabolic responses to NAC by HR MAS MRS may provide information about tumor biology related to individual prognosis.

Elevated Serum Lactate in Glioma Patients: Associated Factors.

Introduction: Serum lactate levels in brain cancer patients correlate with tumor malignancy grading, and serum lactate has been suggested as a potential biomarker and prognostic factor. The purpose of this study was to identify potential sources of elevated serum lactate in patients with brain gliomas by examining factors of importance for serum lactate production and clearance. Methods: In this cross-sectional study, data were collected from 261 glioma patients who underwent surgery from March 2011 to June 2015. We recorded patient gender, age, blood serum measures of lactate, glucose, pH, hemoglobin and base excess, patient health status, medications, and tumor characteristics. Patients with elevated and normal serum lactate levels were compared, and we explored if there were correlations between the variables. The association of serum lactate with the measured variables was investigated by simple and multivariable linear regression models. Results and Discussion: Patients with elevated serum lactate had higher blood glucose, larger tumor volumes, and more tumor edema; more often needed pressor medication during surgery; and more often received corticosteroid treatment. The investigated variables were highly correlated. Multivariable linear regression indicated that gender, tumor volume, Charlson Comorbidity Index, hyperglycemia, and corticosteroid treatment were associated with serum lactate levels. Histopathology was not an independent factor. In conclusion, comorbidities, hyperglycemia, and presurgical corticosteroid treatment exhibited the strongest association with serum lactate in glioma patients.

Evaluating the Impact of High Intensity Interval Training on Axial Psoriatic Arthritis Based on MR Images.

High intensity interval training (HIIT) has been shown to benefit patients with psoriatic arthritis (PsA). However, magnetic resonance (MR) imaging has uncovered bone marrow edema (BME) in healthy volunteers after vigorous exercise. The purpose of this study was to investigate MR images of the spine of PsA patients for changes in BME after HIIT. PsA patients went through 11 weeks of HIIT (N = 19, 4 men, median age 52 years) or no change in physical exercise habits (N = 20, 8 men, median age 45 years). We acquired scores for joint affection and pain and short tau inversion recovery (STIR) and T1-weighted MR images of the spine at baseline and after 11 weeks. MR images were evaluated for BME by a trained radiologist, by SpondyloArthritis Research Consortium of Canada (SPARCC) scoring, and by extraction of textural features. No significant changes of BME were detected in MR images of the spine after HIIT. This was consistent for MR image evaluation by a radiologist, by SPARCC, and by texture analysis. Values of textural features were significantly different in BME compared to healthy bone marrow. In conclusion, BME in spine was not changed after HIIT, supporting that HIIT is safe for PsA patients.

In vivo MRS of locally advanced breast cancer: characteristics related to negative or positive choline detection and early monitoring of treatment response.

OBJECT: To explore factors determining the detection of total choline (tCho) by in vivo MR spectroscopy (MRS) in locally advanced breast cancer and to evaluate the ability of in vivo tCho to predict treatment response after one cycle of neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: Breast cancer patients (N=40) scheduled for NAC were examined with an MR protocol including in vivo single voxel proton MRS, dynamic contrast enhanced MRI and diffusion weighted MRI. tCho was quantified based on the signal-to-noise ratio. The detection was considered positive with tCho signal-to-noise ratio≥2. RESULTS: tCho was detected in 60% of the patients. Excellent reliability in tCho (ICC=0.97, P<0.001) measurements was confirmed. The water/fat-ratio, tumor volume and distribution of Type II voxels (based on contrast uptake curve) were significantly higher in patients with positive choline detection. The probability of detecting tCho was higher in ER-negative patients. A significant decrease in tChoSNR was detected after treatment, but responders could not be distinguished from non-responders. CONCLUSION: The use of in vivo MRS in breast cancer diagnosis and treatment monitoring should bring supplementary information to the standard MR imaging protocol. With the currently observed low choline detection rate, this is not the case, and technological challenges related to choline detection have to be resolved.

Multivariate modeling and prediction of breast cancer prognostic factors using MR metabolomics.

Axillary lymph node status together with estrogen and progesterone receptor status are important prognostic factors in breast cancer. In this study, the potential of using MR metabolomics for prediction of these prognostic factors was evaluated. Biopsies from breast cancer patients (n = 160) were excised during surgery and analyzed by high resolution magic angle spinning MR spectroscopy (HR MAS MRS). The spectral data were preprocessed and variable stability (VAST) scaled, and training and test sets were generated using the Kennard-Stone and SPXY sample selection algorithms. The data were analyzed by partial least-squares discriminant analysis (PLS-DA), probabilistic neural networks (PNNs) and Bayesian belief networks (BBNs), and blind samples (n = 50) were predicted for verification. Estrogen and progesterone receptor status was successfully predicted from the MR spectra, and were best predicted by PLS-DA with a correct classification of 44 of 50 and 39 of 50 samples, respectively. Lymph node status was best predicted by BBN with 34 of 50 samples correctly classified, indicating a relationship between metabolic profile and lymph node status. Thus, MR profiles contain prognostic information that may be of benefit in treatment planning, and MR metabolomics may become an important tool for diagnosis of breast cancer patients.

Quantification of metabolites in breast cancer patients with different clinical prognosis using HR MAS MR spectroscopy.

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 = 13) and poor (n = 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 (ß-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 µmol/g) compared to patients with poor prognosis (1.9 µmol/g, p = 0.067). Tissue metabolite concentrations (except for ß-glucose) were also found to correlate to the fraction of tumor, connective, fat or glandular tissue by Pearson correlation analysis. Tissue concentrations of ß-glucose correlated to proliferation index (MIB-1) with a negative correlation factor (-0.45, p = 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).

Distinct choline metabolic profiles are associated with differences in gene expression for basal-like and luminal-like breast cancer xenograft models.

BACKGROUND: Increased concentrations of choline-containing compounds are frequently observed in breast carcinomas, and may serve as biomarkers for both diagnostic and treatment monitoring purposes. However, underlying mechanisms for the abnormal choline metabolism are poorly understood. METHODS: The concentrations of choline-derived metabolites were determined in xenografted primary human breast carcinomas, representing basal-like and luminal-like subtypes. Quantification of metabolites in fresh frozen tissue was performed using high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses. The metabolite profiles from xenografts were compared with profiles from human breast cancer, sampled from patients with estrogen/progesterone receptor positive (ER+/PgR+) or triple negative (ER-/PgR-/HER2-) breast cancer. RESULTS: In basal-like xenografts, glycerophosphocholine (GPC) concentrations were higher than phosphocholine (PCho) concentrations, whereas this pattern was reversed in luminal-like xenografts. These differences may be explained by lower choline kinase (CHKA, CHKB) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A (PLA2G4A) and phospholipase B1 (PLB1) in the basal-like model. The glycine concentration was higher in the basal-like model. Although glycine could be derived from energy metabolism pathways, the gene expression data suggested a metabolic shift from PtdCho synthesis to glycine formation in basal-like xenografts. In agreement with results from the xenograft models, tissue samples from triple negative breast carcinomas had higher GPC/PCho ratio than samples from ER+/PgR+ carcinomas, suggesting that the choline metabolism in the experimental models is representative for luminal-like and basal-like human breast cancer. CONCLUSIONS: The differences in choline metabolite concentrations corresponded well with differences in gene expression, demonstrating distinct metabolic profiles in the xenograft models representing basal-like and luminal-like breast cancer. The same characteristics of choline metabolite profiles were also observed in patient material from ER+/PgR+ and triple-negative breast cancer, suggesting that the xenografts are relevant model systems for studies of choline metabolism in luminal-like and basal-like breast cancer.

Merging transcriptomics and metabolomics--advances in breast cancer profiling.

BACKGROUND: Combining gene expression microarrays and high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) of the same tissue samples enables comparison of the transcriptional and metabolic profiles of breast cancer. The aim of this study was to explore the potential of combining these two different types of information. METHODS: Breast cancer tissue from 46 patients was analyzed by HR MAS MRS followed by gene expression microarrays. Two strategies were used to combine the gene expression and metabolic data; first using multivariate analyses to identify different groups based on gene expression and metabolic data; second correlating levels of specific metabolites to transcripts to suggest new hypotheses of connections between metabolite levels and the underlying biological processes. A parallel study was designed to address experimental issues of combining microarrays and HR MAS MRS. RESULTS: In the first strategy, using the microarray data and previously reported molecular classification methods, the majority of samples were classified as luminal A. Three subgroups of luminal A tumors were identified based on hierarchical clustering of the HR MAS MR spectra. The samples in one of the subgroups, designated A2, showed significantly lower glucose and higher alanine levels than the other luminal A samples, suggesting a higher glycolytic activity in these tumors. This group was also enriched for genes annotated with Gene Ontology (GO) terms related to cell cycle and DNA repair. In the second strategy, the correlations between concentrations of myo-inositol, glycine, taurine, glycerophosphocholine, phosphocholine, choline and creatine and all transcripts in the filtered microarray data were investigated. GO-terms related to the extracellular matrix were enriched among the genes that correlated the most to myo-inositol and taurine, while cell cycle related GO-terms were enriched for the genes that correlated the most to choline. Additionally, a subset of transcripts was identified to have slightly altered expression after HR MAS MRS and was therefore removed from all other analyses. CONCLUSIONS: Combining transcriptional and metabolic data from the same breast carcinoma sample is feasible and may contribute to a more refined subclassification of breast cancers as well as reveal relations between metabolic and transcriptional levels. See Commentary: http://www.biomedcentral.com/1741-7015/8/73.

Markers of Mitochondrial Metabolism in Tumor Hypoxia, Systemic Inflammation, and Adverse Outcome of Rectal Cancer.

Tumor hypoxia contributes to therapy resistance and metastatic progression of locally advanced rectal cancer (LARC). We postulated that the tumor mitochondrial metabolism, manifested by reactive oxygen species (ROS) and mitochondrial DNA (mtDNA) damage, reflects how hypoxic conditions connect to cancer-induced systemic inflammation and poor outcome. Levels of ROS and mtDNA damage were analyzed in three colorectal cancer (CRC) cell lines cultured for 24 hours under normoxia (21% O2) or hypoxia (0.2% O2) and serum sampled at the time of diagnosis from 35 LARC patients participating in a prospective therapy study. Compared with normoxia, ROS were significantly repressed and mtDNA damage was significantly enhanced in the hypoxic CRC cell lines; hence, a low ratio of ROS to mtDNA damage was an indicator of hypoxic conditions. In the LARC patients, low serum ROS were associated with elevated levels of circulating carcinoembryonic antigen and tumor choline concentration, both indicative of unfavorable biology, as well as adverse progression-free and overall survival. A low ratio of ROS to mtDNA damage in serum was associated with poor local tumor response to the neoadjuvant treatment and, of note, elevated systemic inflammation factors (C-reactive protein, the interleukin-1 receptor antagonist, and factors involved in tumor necrosis factor signaling), indicating that deficient treatment response locally and detrimental inflammation systemically link to a hypoxic mitochondrial metabolism. In conclusion, serum ROS and damaged mtDNA may be markers of the mitochondrial metabolism driven by the state of oxygenation of the primary tumor and possibly implicated in systemic inflammation and adverse outcome of LARC.

Principal component analysis for the comparison of metabolic profiles from human rectal cancer biopsies and colorectal xenografts using high-resolution magic angle spinning 1H magnetic resonance spectroscopy.

BACKGROUND: This study was conducted in order to elucidate metabolic differences between human rectal cancer biopsies and colorectal HT29, HCT116 and SW620 xenografts by using high-resolution magnetic angle spinning (MAS) magnetic resonance spectroscopy (MRS) and for determination of the most appropriate human rectal xenograft model for preclinical MR spectroscopy studies. A further aim was to investigate metabolic changes following irradiation of HT29 xenografts. METHODS: HR MAS MRS of tissue samples from xenografts and rectal biopsies were obtained with a Bruker Avance DRX600 spectrometer and analyzed using principal component analysis (PCA) and partial least square (PLS) regression analysis. RESULTS AND CONCLUSION: HR MAS MRS enabled assignment of 27 metabolites. Score plots from PCA of spin-echo and single-pulse spectra revealed separate clusters of the different xenografts and rectal biopsies, reflecting underlying differences in metabolite composition. The loading profile indicated that clustering was mainly based on differences in relative amounts of lipids, lactate and choline-containing compounds, with HT29 exhibiting the metabolic profile most similar to human rectal cancers tissue. Due to high necrotic fractions in the HT29 xenografts, radiation-induced changes were not detected when comparing spectra from untreated and irradiated HT29 xenografts. However, PLS calibration relating spectral data to the necrotic fraction revealed a significant correlation, indicating that necrotic fraction can be assessed from the MR spectra.

Metabolic mapping by use of high-resolution magic angle spinning 1H MR spectroscopy for assessment of apoptosis in cervical carcinomas.

BACKGROUND: High-resolution magic angle proton magnetic resonance spectroscopy (HR 1H MAS MRS) provides a broad metabolic mapping of intact tumor samples and allows for microscopy investigations of the samples after spectra acquisition. Experimental studies have suggested that the method can be used for detection of apoptosis, but this has not been investigated in a clinical setting so far. We have explored this hypothesis in cervical cancers by searching for metabolites associated with apoptosis that were not influenced by other histopathological parameters like tumor load and tumor cell density. METHODS: Biopsies (n = 44) taken before and during radiotherapy in 23 patients were subjected to HR MAS MRS. A standard pulse-acquire spectrum provided information about lipids, and a spin-echo spectrum enabled detection of non-lipid metabolites in the lipid region of the spectra. Apoptotic cell density, tumor cell fraction, and tumor cell density were determined by histopathological analysis after spectra acquisition. RESULTS: The apoptotic cell density correlated with the standard pulse-acquire spectra (p < 0.001), but not with the spin-echo spectra, showing that the lipid metabolites were most important. The combined information of all lipids contributed to the correlation, with a major contribution from the ratio of fatty acid -CH2 to CH3 (p = 0.02). In contrast, the spin-echo spectra contained the main information on tumor cell fraction and tumor cell density (p < 0.001), for which cholines, creatine, taurine, glucose, and lactate were most important. Significant correlations were found between tumor cell fraction and glucose concentration (p = 0.001) and between tumor cell density and glycerophosphocholine (GPC) concentration (p = 0.024) and ratio of GPC to choline (p < 0.001). CONCLUSION: Our findings indicate that the apoptotic activity of cervical cancers can be assessed from the lipid metabolites in HR MAS MR spectra and that the HR MAS data may reveal novel information on the metabolic changes characteristic of apoptosis. These changes differed from those associated with tumor load and tumor cell density, suggesting an application of the method to explore the role of apoptosis in the course of the disease.