HR MAS MRS Research Articles

Metabolic profiling of colorectal cancer organoids: A comparison between high-resolution magic angle spinning magnetic resonance spectroscopy and solution nuclear magnetic resonance spectroscopy of polar extracts.

Patient-derived cancer cells cultured in vitro are a cornerstone of cancer metabolism research. More recently, the introduction of organoids has provided the research community with a more versatile model system. Physiological structure and organization of the cell source tissue are maintained in organoids, representing a closer link to in vivo tumor models. High-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) is a commonly applied analytical approach for metabolic profiling of intact tissue, but its use has not been reported for organoids. The aim of the current work was to compare the performance of HR MAS MRS and extraction-based nuclear magnetic resonance (NMR) in metabolic profiling of wild-type and tumor progression organoids (TPOs) from human colon cancer, and further to investigate how the sequentially increased genetic alterations of the TPOs affect the metabolic profile. Sixteen metabolites were reliably identified and quantified both in spectra based on NMR of extracts and HR MAS MRS of intact organoids. The metabolite concentrations from the two approaches were highly correlated (r = 0.94), and both approaches were able to capture the systematic changes in metabolic features introduced by the genetic alterations characteristic of colorectal cancer progression (e.g., increased levels of lactate and decreased levels of myo-inositol and phosphocholine with an increasing number of mutations). The current work highlights that HR MAS MRS is a well-suited method for metabolic profiling of intact organoids, with the additional benefit that the nondestructive nature of HR MAS enables subsequent recovery of the organoids for further analyses based on nucleic acids or proteins.

Historical Biobanks in Breast Cancer Metabolomics- Challenges and Opportunities.

Background: Metabolomic characterization of tumours can potentially improve prediction of cancer prognosis and treatment response. Here, we describe efforts to validate previous metabolomic findings using a historical cohort of breast cancer patients and discuss challenges with using older biobanks collected with non-standardized sampling procedures. Methods: In total, 100 primary breast cancer samples were analysed by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) and subsequently examined by histology. Metabolomic profiles were related to the presence of cancer tissue, hormone receptor status, T-stage, N-stage, and survival. RNA integrity number (RIN) and metabolomic profiles were compared with an ongoing breast cancer biobank. Results: The 100 samples had a median RIN of 4.3, while the ongoing biobank had a significantly higher median RIN of 6.3 (p = 5.86 × 10−7). A low RIN was associated with changes in choline-containing metabolites and creatine, and the samples in the older biobank showed metabolic differences previously associated with tissue degradation. The association between metabolomic profile and oestrogen receptor status was in accordance with previous findings, however, with a lower classification accuracy. Conclusions: Our findings highlight the importance of standardized biobanking procedures in breast cancer metabolomics studies.

Glutamine to proline conversion is associated with response to glutaminase inhibition in breast cancer

IntroductionGlutaminase inhibitors target cancer cells by blocking the conversion of glutamine to glutamate, thereby potentially interfering with anaplerosis and synthesis of amino acids and glutathione. The drug CB-839 has shown promising effects in preclinical experiments and is currently undergoing clinical trials in several human malignancies, including triple-negative breast cancer (TNBC). However, response to glutaminase inhibitors is variable and there is a need for identification of predictive response biomarkers. The aim of this study was to determine how glutamine is utilized in two patient-derived xenograft (PDX) models of breast cancer representing luminal-like/ER+ (MAS98.06) and basal-like/triple-negative (MAS98.12) breast cancer and to explore the metabolic effects of CB-839 treatment.ExperimentalMAS98.06 and MAS98.12 PDX mice received CB-839 (200 mg/kg) or drug vehicle two times daily p.o. for up to 28 days (n = 5 per group), and the effect on tumor growth was evaluated. Expression of 60 genes and seven glutaminolysis key enzymes were determined using gene expression microarray analysis and immunohistochemistry (IHC), respectively, in untreated tumors. Uptake and conversion of glutamine were determined in the PDX models using HR MAS MRS after i.v. infusion of [5-13C] glutamine when the models had received CB-839 (200 mg/kg) or vehicle for 2 days (n = 5 per group).ResultsTumor growth measurements showed that CB-839 significantly inhibited tumor growth in MAS98.06 tumors, but not in MAS98.12 tumors. Gene expression and IHC analysis indicated a higher proline synthesis from glutamine in untreated MAS98.06 tumors. This was confirmed by HR MAS MRS of untreated tumors demonstrating that MAS98.06 used glutamine to produce proline, glutamate, and alanine, and MAS98.12 to produce glutamate and lactate. In both models, treatment with CB-839 resulted in accumulation of glutamine. In addition, CB-839 caused depletion of alanine, proline, and glutamate ([1-13C] glutamate) in the MAS98.06 model.ConclusionOur findings indicate that TNBCs may not be universally sensitive to glutaminase inhibitors. The major difference in the metabolic fate of glutamine between responding MAS98.06 xenografts and non-responding MAS98.12 xenografts is the utilization of glutamine for production of proline. We therefore suggest that addiction to proline synthesis from glutamine is associated with response to CB-839 in breast cancer.Graphical abstractThe effect of glutaminase inhibition in two breast cancer patient-derived xenograft (PDX) models. 13C HR MAS MRS analysis of tumor tissue from CB-839-treated and untreated models receiving 13C-labeled glutamine ([5-13C] Gln) shows that the glutaminase inhibitor CB-839 is causing an accumulation of glutamine (arrow up) in two PDX models representing luminal-like breast cancer (MAS98.06) and basal-like breast cancer (MAS98.12). In MAS98.06 tumors, CB-839 is in addition causing depletion of proline ([5-13C] Pro), alanine ([1-13C] Ala), and glutamate ([1-13C] Glu), which could explain why CB-839 causes tumor growth inhibition in MAS98.06 tumors, but not in MAS98.12 tumors.

Metabolomic prostate cancer fields in HRMAS MRS-profiled histologically benign tissue vary with cancer status and distance from cancer.

In this article, we review the state of the field of high resolution magic angle spinning MRS (HRMAS MRS)-based cancer metabolomics since its beginning in 2004; discuss the concept of cancer metabolomic fields, where metabolomic profiles measured from histologically benign tissues reflect patient cancer status; and report our HRMAS MRS metabolomic results, which characterize metabolomic fields in prostatectomy-removed cancerous prostates. Three-dimensional mapping of cancer lesions throughout each prostate enabled multiple benign tissue samples per organ to be classified based on distance from and extent of the closest cancer lesion as well as the Gleason score (GS) of the entire prostate. Cross-validated partial least squares-discriminant analysis separations were achieved between cancer and benign tissue, and between cancer tissue from prostates with high (≥4+3) and low (≤3+4) GS. Metabolomic field effects enabled histologically benign tissue adjacent to cancer to distinguish the GS and extent of the cancer lesion itself. Benign samples close to either low GS cancer or extensive cancer lesions could be distinguished from those far from cancer. Furthermore, a successfully cross-validated multivariate model for three benign tissue groups with varying distances from cancer lesions within one prostate indicates the scale of prostate cancer metabolomic fields. While these findings could, at present, be potentially useful in the prostate cancer clinic for analysis of biopsy or surgical specimens to complement current diagnostics, the confirmation of metabolomic fields should encourage further examination of cancer fields and can also enhance understanding of the metabolomic characteristics of cancer in myriad organ systems. Our results together with the success of HRMAS MRS-based cancer metabolomics presented in our literature review demonstrate the potential of cancer metabolomics to provide supplementary information for cancer diagnosis, staging, and patient prognostication.

Integrative metabolic and transcriptomic profiling of prostate cancer tissue containing reactive stroma

Reactive stroma is a tissue feature commonly observed in the tumor microenvironment of prostate cancer and has previously been associated with more aggressive tumors. The aim of this study was to detect differentially expressed genes and metabolites according to reactive stroma content measured on the exact same prostate cancer tissue sample. Reactive stroma was evaluated using histopathology from 108 fresh frozen prostate cancer samples gathered from 43 patients after prostatectomy (Biobank1). A subset of the samples was analyzed both for metabolic (n = 85) and transcriptomic alterations (n = 78) using high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) and RNA microarray, respectively. Recurrence-free survival was assessed in patients with clinical follow-up of minimum five years (n = 38) using biochemical recurrence (BCR) as endpoint. Multivariate metabolomics and gene expression analysis compared low (≤15%) against high reactive stroma content (≥16%). High reactive stroma content was associated with BCR in prostate cancer patients even when accounting for the influence of Grade Group (Cox hazard proportional analysis, p = 0.013). In samples with high reactive stroma content, metabolites and genes linked to immune functions and extracellular matrix (ECM) remodeling were significantly upregulated. Future validation of these findings is important to reveal novel biomarkers and drug targets connected to immune mechanisms and ECM in prostate cancer. The fact that high reactive stroma grading is connected to BCR adds further support for the clinical integration of this histopathological evaluation.

Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy

Background:Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy.Methods:We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan–Meier survival analyses and concordance index (C-index).Results:High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively).Conclusions:Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.

Metabolic clusters of breast cancer in relation to gene- and protein expression subtypes.

BackgroundThe heterogeneous biology of breast cancer leads to high diversity in prognosis and response to treatment, even for patients with similar clinical diagnosis, histology, and stage of disease. Identifying mechanisms contributing to this heterogeneity may reveal new cancer targets or clinically relevant subgroups for treatment stratification. In this study, we have merged metabolite, protein, and gene expression data from breast cancer patients to examine the heterogeneity at a molecular level.MethodsThe study included primary tumor samples from 228 non-treated breast cancer patients. High-resolution magic-angle spinning magnetic resonance spectroscopy (HR MAS MRS) was performed to extract the tumors metabolic profiles further used for hierarchical cluster analysis resulting in three significantly different metabolic clusters (Mc1, Mc2, and Mc3). The clusters were further combined with gene and protein expression data.ResultsOur result revealed distinct differences in the metabolic profile of the three metabolic clusters. Among the most interesting differences, Mc1 had the highest levels of glycerophosphocholine (GPC) and phosphocholine (PCho), Mc2 had the highest levels of glucose, and Mc3 had the highest levels of lactate and alanine. Integrated pathway analysis of metabolite and gene expression data uncovered differences in glycolysis/gluconeogenesis and glycerophospholipid metabolism between the clusters. All three clusters had significant differences in the distribution of protein subtypes classified by the expression of breast cancer-related proteins. Genes related to collagens and extracellular matrix were downregulated in Mc1 and consequently upregulated in Mc2 and Mc3, underpinning the differences in protein subtypes within the metabolic clusters. Genetic subtypes were evenly distributed among the three metabolic clusters and could therefore contribute to additional explanation of breast cancer heterogeneity.ConclusionsThree naturally occurring metabolic clusters of breast cancer were detected among primary tumors from non-treated breast cancer patients. The clusters expressed differences in breast cancer-related protein as well as genes related to extracellular matrix and metabolic pathways known to be aberrant in cancer. Analyses of metabolic activity combined with gene and protein expression provide new information about the heterogeneity of breast tumors and, importantly, the metabolic differences infer that the clusters may be susceptible to different metabolically targeted drugs.Electronic supplementary materialThe online version of this article (doi:10.1186/s40170-016-0152-x) contains supplementary material, which is available to authorized users.

Anti-vascular effects of the cytosolic phospholipase A2 inhibitor AVX235 in a patient-derived basal-like breast cancer model.

BackgroundGroup IVA cytosolic phospholipase A2 (cPLA2α) plays an important role in tumorigenesis and angiogenesis. It is overexpressed in basal-like breast cancer (BLBC), which is aggressive and usually triple-negative, making it unresponsive to current targeted therapies. Here, we evaluated the anti-angiogenic effects of a specific cPLA2α inhibitor, AVX235, in a patient-derived triple-negative BLBC model.MethodsMice bearing orthotopic xenografts received i.p. injections of AVX235 or DMSO vehicle daily for 1 week and then every other day for up to 19 days. Six treated and six control mice were terminated after 2 days of treatment, and the tumors excised for high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) and prostaglandin E2 (PGE2) enzyme immunoassay (EIA) analysis. A 1-week imaging study was performed on a separate cohort of mice. Longitudinal dynamic contrast enhanced (DCE)-MRI was performed before, after 4 days, and after 1 week of treatment. The mice were then perfused with a radiopaque vascular casting agent, and the tumors excised for micro-CT angiography. Subsequently, tumors were sectioned and stained with lectin and for Ki67 or α-smooth muscle actin to quantify endothelial cell proliferation and vessel maturity, respectively. Partial least squares discriminant analysis was performed on the multivariate HR MAS MRS data, and non-parametric univariate analyses using Mann–Whitney U tests (α = 0.05) were performed on all other data.ResultsGlycerophosphocholine and PGE2 levels, measured by HR MAS MRS and EIA, respectively, were lower in treated tumors after 2 days of treatment. These molecular changes are expected downstream effects of cPLA2α inhibition and were followed by significant tumor growth inhibition after 8 days of treatment. DCE-MRI revealed that AVX235 treatment caused a decrease in tumor perfusion. Concordantly, micro-CT angiography showed that vessel volume fraction, density, and caliber were reduced in treated tumors. Moreover, histology showed decreased endothelial cell proliferation and fewer immature vessels in treated tumors.ConclusionsThese results demonstrate that cPLA2α inhibition with AVX235 resulted in decreased vascularization and perfusion and subsequent inhibition of tumor growth. Thus, cPLA2α inhibition may be a potential new therapeutic option for triple-negative basal-like breast cancer.

Abstract A36: Protein expression analysis of intratumor heterogeneity in a luminal-like breast cancer xenograft

Abstract Estrogen receptor is a key driver in breast cancer and is expressed in about 75% of breast tumors. ER positive tumors are susceptible to endocrine therapies; however, the major obstacle for curative treatment is recurrence due to resistance to anti-estrogens. Endocrine therapies may induce a selective pressure promoting growth of estrogen independent cell subclones. Our aim was to reveal molecular changes occurring in tumors in response to anti-estrogen treatment, and to identify subpopulations of cells able to withstand anti-estrogen treatment. A luminal-like estrogen-dependent orthotopically growing xenograft model was treated with fulvestrant, or exposed to estrogen deprivation. The effect of ER-signaling inhibition was analyzed using quantitative mass spectrometry (MS) -based proteomic analysis and high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). Cell surface marker expression (CD24 and SSEA-4) was monitored by flow cytometry, allowing detailed comparison of protein expression between intratumor cell subpopulations. We found that both modes of anti-estrogen therapy restrained tumor growth and induced expression of enzymes involved in TCA cycle, oxidative phosphorylation and fatty acid beta-oxidation. This was accompanied by changes in levels of specific metabolites indicative of a possible reprogramming of cell metabolism and utilization of oxidative phosphorylation in preference to aerobic glycolysis (decrease in Warburg effect). Furthermore, anti-estrogen treatment seemed to have selective effects on intratumor cell subpopulations, specified by expression of the markers CD24 and SSEA-4. More specifically, highly tumorigenic CD24low/SSEA-4low (dbl. low) cells were eliminated and the seemingly more benign CD24high/SSEA-4high (dbl. high) cells were enriched in the residual tumor. When comparing the proteome in dbl. low verus dbl. high cells sorted from untreated tumors, metabolism was one of the most differentially enriched processes. Enzymes involved in glycolysis, TCA cycle, respiratory electron transport chain and fatty acid were more abundant in the dbl. high subpopulation. These results suggest that cancer cells may reprogram their metabolism in response to anti-estrogen therapy to support a less estrogen-dependent phenotype. Moreover, subpopulations of cells with different metabolism may exist within the growing tumor, and these may respond differently to anti-estrogen treatment. Citation Format: Nirma Skrbo, Ufuk Kirik, Alexandr Kristian, Paolo Cifani, Linn Antberg, Siver A. Moestue, Olav Engebraaten, Gunhild M. Mælandsmo, Kristin Andersen, Peter James, Therese Sørlie. Protein expression analysis of intratumor heterogeneity in a luminal-like breast cancer xenograft. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr A36.

High tumor glycine concentration is an adverse prognostic factor in locally advanced rectal cancer

Background and purposeRecognizing the link between altered tumor metabolism and disease aggressiveness, this study aimed to identify associations between tumor metabolic profiles and therapeutic outcome in locally advanced rectal cancer (LARC). Materials and methodsPretreatment tumor metabolic profiles from 54 LARC patients receiving combined-modality neoadjuvant treatment and surgery were acquired by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). Metabolite concentrations were correlated to TNM and the presence of disseminated tumor cells (DTC) at diagnosis, ypTN and tumor regression grade (TRG) following neoadjuvant treatment, and progression-free survival (PFS). ResultsPretreatment tumor metabolite concentrations showed no significant associations to TNM, DTC, ypTN or TRG. In univariate regression analysis, high concentrations of glycine, creatine and myo-inositol were significantly associated with poor PFS, with metastasis as main PFS event. In multivariate analysis, high glycine concentration remained most significantly associated with poor PFS (hazard ratio=4.4, 95% confidence interval=1.4–14.3, p=0.008). ConclusionsHigh tumor glycine concentration was identified as adverse prognostic factor for PFS in LARC. In a patient population treated with curative intent but with metastatic disease as main PFS event further investigations of glycine as early predictor of metastatic progression and therapeutic target are warranted.

Metabolic profiles of placenta in preeclampsia using HR-MAS MRS metabolomics

IntroductionPreeclampsia is a heterogeneous gestational disease characterized by maternal hypertension and proteinuria, affecting 2–7% of pregnancies. The disorder is initiated by insufficient placental development, but studies characterizing the placental disease components are lacking. MethodsOur aim was to phenotype the preeclamptic placenta using high-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HR-MAS MRS). Placental samples collected after delivery from women with preeclampsia (n = 19) and normotensive pregnancies (n = 15) were analyzed for metabolic biomarkers including amino acids, osmolytes, and components of the energy and phospholipid metabolism. The metabolic biomarkers were correlated to clinical characteristics and inflammatory biomarkers in the maternal sera. ResultsPrincipal component analysis showed inherent differences in placental metabolic profiles between preeclamptic and normotensive pregnancies. Significant differences in metabolic profiles were found between placentas from severe and non-severe preeclampsia, but not between preeclamptic pregnancies with fetal growth restricted versus normal weight neonates. The placental metabolites correlated with the placental stress marker sFlt-1 and triglycerides in maternal serum, suggesting variation in placental stress signaling between different placental phenotypes. DiscussionHR-MAS MRS is a sensitive method for defining the placental disease component of preeclampsia, identifying several altered metabolic pathways. Placental HR-MAS MRS analysis may improve insight into processes affected in the preeclamptic placenta, and represents a novel long-required tool for a sensitive placental phenotyping of this heterogeneous disease.

Metabolite profiling in retinoblastoma identifies novel clinicopathological subgroups.

Background:Tumour classification, based on histopathology or molecular pathology, is of value to predict tumour behaviour and to select appropriate treatment. In retinoblastoma, pathology information is not available at diagnosis and only exists for enucleated tumours. Alternative methods of tumour classification, using noninvasive techniques such as magnetic resonance spectroscopy, are urgently required to guide treatment decisions at the time of diagnosis.Methods:High-resolution magic-angle spinning magnetic resonance spectroscopy (HR-MAS MRS) was undertaken on enucleated retinoblastomas. Principal component analysis and cluster analysis of the HR-MAS MRS data was used to identify tumour subgroups. Individual metabolite concentrations were determined and were correlated with histopathological risk factors for each group.Results:Multivariate analysis identified three metabolic subgroups of retinoblastoma, with the most discriminatory metabolites being taurine, hypotaurine, total-choline and creatine. Metabolite concentrations correlated with specific histopathological features: taurine was correlated with differentiation, total-choline and phosphocholine with retrolaminar optic nerve invasion, and total lipids with necrosis.Conclusions:We have demonstrated that a metabolite-based classification of retinoblastoma can be obtained using ex vivo magnetic resonance spectroscopy, and that the subgroups identified correlate with histopathological features. This result justifies future studies to validate the clinical relevance of these subgroups and highlights the potential of in vivo MRS as a noninvasive diagnostic tool for retinoblastoma patient stratification.

The three glioma rat models C6, F98 and RG2 exhibit different metabolic profiles: in vivo 1H MRS and ex vivo 1H HRMAS combined with multivariate statistics

Glioblastomas are the most malignant subtypes of glioma and many efforts are currently made to improve their characterization though molecular, microvascular, immunogenic and metabolomic approaches. The variability within pre-clinical tumor models may mimic glioma heterogeneity and force the development of innovative analytical methodologies. In this study, we investigate the metabolic variability within three rat models of glioma: C6, RG2 and F98, using in vivo magnetic resonance spectroscopy (1H MRS) and ex vivo high resolution magic angle spinning (1H HRMAS MRS). We used a multivariate statistic approach with orthogonal projection to latent structure-discriminant analysis (OPLS-DA) that was compared with univariate statistic. OPLS-DA reveals a clear separation between C6, RG2 and F98 tumors and, with the help of shared and unique structure plot (SUS-Plot), promotes a comprehensive view of their metabolic differences. Both in vivo and ex vivo analyses are similar but ex vivo 1H HRMAS MRS provides more robust results. In conclusion, MRS-based OPLS-DA appears sensitive enough to correctly predict the classification of tumors and to investigate the relationship between the host brain metabolism and the grafted tumor.

Impact of manganese on the hippocampus metabolism in the context of MEMRI: a proton HRMAS MRS study

The HRMAS spectrum revealed an important impact of Mn 500 nmol on the hippocampal metabolism, not observed with Mn 8 nmol.

Metabolic characterization of triple negative breast cancer.

BackgroundThe aims of this study were to characterize the metabolite profiles of triple negative breast cancer (TNBC) and to investigate the metabolite profiles associated with human epidermal growth factor receptor-2/neu (HER-2) overexpression using ex vivo high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). Metabolic alterations caused by the different estrogen receptor (ER), progesterone receptor (PgR) and HER-2 receptor statuses were also examined. To investigate the metabolic differences between two distinct receptor groups, TNBC tumors were compared to tumors with ERpos/PgRpos/HER-2pos status which for the sake of simplicity is called triple positive breast cancer (TPBC).MethodsThe study included 75 breast cancer patients without known distant metastases. HR MAS MRS was performed for identification and quantification of the metabolite content in the tumors. Multivariate partial least squares discriminant analysis (PLS-DA) modeling and relative metabolite quantification were used to analyze the MR data.ResultsCholine levels were found to be higher in TNBC compared to TPBC tumors, possibly related to cell proliferation and oncogenic signaling. In addition, TNBC tumors contain a lower level of Glutamine and a higher level of Glutamate compared to TPBC tumors, which indicate an increase in glutaminolysis metabolism. The development of glutamine dependent cell growth or “Glutamine addiction” has been suggested as a new therapeutic target in cancer. Our results show that the metabolite profiles associated with HER-2 overexpression may affect the metabolic characterization of TNBC. High Glycine levels were found in HER-2pos tumors, which support Glycine as potential marker for tumor aggressiveness.ConclusionsMetabolic alterations caused by the individual and combined receptors involved in breast cancer progression can provide a better understanding of the biochemical changes underlying the different breast cancer subtypes. Studies are needed to validate the potential of metabolic markers as targets for personalized treatment of breast cancer subtypes.

HR-MAS MRS of the pancreas reveals reduced lipid and elevated lactate and taurine associated with early pancreatic cancer.

The prognosis for patients with pancreatic cancer is extremely poor, as evidenced by the disease's five-year survival rate of ~5%. New approaches are therefore urgently needed to improve detection, treatment, and monitoring of pancreatic cancer. MRS-detectable metabolic changes provide useful biomarkers for tumor detection and response-monitoring in other cancers. The goal of this study was to identify MRS-detectable biomarkers of pancreatic cancer that could enhance currently available imaging approaches. We used (1) H high-resolution magic angle spinning MRS to probe metabolite levels in pancreatic tissue samples from mouse models and patients. In mice, the levels of lipids dropped significantly in pancreata with lipopolysaccharide-induced inflammation, in pancreata with pre-cancerous metaplasia (4 week old p48-Cre;LSL-Kras(G12D) mice), and in pancreata with pancreatic intraepithelial neoplasia, which precedes invasive pancreatic cancer (8 week old p48-Cre LSL-Kras(G12D) mice), to 26 ± 19% (p = 0.03), 19 ± 16% (p = 0.04), and 26 ± 10% (p = 0.05) of controls, respectively. Lactate and taurine remained unchanged in inflammation and in pre-cancerous metaplasia but increased significantly in pancreatic intraepithelial neoplasia to 266 ± 61% (p = 0.0001) and 999 ± 174% (p < 0.00001) of controls, respectively. Importantly, analysis of patient biopsies was consistent with the mouse findings. Lipids dropped in pancreatitis and in invasive cancer biopsies to 29 ± 15% (p = 0.01) and 26 ± 38% (p = 0.02) of normal tissue. In addition, lactate and taurine levels remained unchanged in inflammation but rose in tumor samples to 244 ± 155% (p = 0.02) and 188 ± 67% (p = 0.02), respectively, compared with normal tissue. Based on these findings, we propose that a drop in lipid levels could serve to inform on pancreatitis and cancer-associated inflammation, whereas elevated lactate and taurine could serve to identify the presence of pancreatic intraepithelial neoplasia and invasive tumor. Our findings may help enhance current imaging methods to improve early pancreatic cancer detection and monitoring.

Mo1233 Functional Evidence for the “Purse String Morphology” of the External Anal Sphincter

tion, in C57Bl6 mice. In vivo water T2 was not different between the NASH mouse model (MCD) and controls (MCS), however, the T2 of liver lipids as well as lipid fractions were significantly elevated in the MCD mice. Ex vivo metabolite profiles could be separated using principle component analysis (PCA) from HR-MAS MRS tissue data. Peaks identified to contribute to the separation of the MCD and the MCS mice, were found to have significant correlations to peaks associated with fatty acids. Our results indicate that non-invasive MRS is a usefull tool in diagnosis NAS as liver-derived lipid transverse relaxation rate values could discriminate the MCD mice from the MCS mice in vivo. The ex vivo HR-MAS results suggested that this could be due to subtle differences in the lipid profiles between the MCD and MCS groups. In conclusion, we report non-invasive in vivo diagnostic approach to NASH in mice. Our results promise translational value for MRS imaging in investigating disparities in lipid profiles in NASH.

Abstract 3227: Evaluation of prostate cancer metabolomic field effects with 1H HRMAS MRS and prostate needle biopsies.

Abstract Purpose: Randomly conducted prostate biopsies often result in false negatives for early-stage PCa patients. Results from our previous studies of intact tissue samples from PCa patients suggested the existence of metabolomic fields, where PCa metabolic information delocalizes from PCa glands and into surrounding benign structures, likely creating PCa “metabolomic lesions” that are larger than the histology cancer lesions. We designed the current study to test the metabolomic field hypothesis by evaluating prostate biopsy cores. Methods: We collected an additional prostate needle biopsy from patients undergoing trans-rectal ultrasound (TRUS) guided biopsy, with the location recorded, for MR analysis. MR experiments were carried out on a Bruker AVANCE spectrometer operating at 600 MHz (14.1T) and pre-cooled to 4°C. A 4mm zirconia rotor was used with inserts to create a 10μl sample space, and D2O was added for 2H field locking. Spectra were acquired using slow spinning rates of 600 and 700Hz and post-spectral edited with Min(A, B) scheme. Spectroscopic data were processed using an in-house MatLab based program. Following MRS analysis, the analyzed core from each patient was evaluated by histopathology and included in the final pathology report along with the other biopsy cores from the same patient. Results: Our studies have shown that spectral regions measured from histologically benign (Hb) samples, and the metabolomic profiles calculated according to principal component (PC) analysis, could differentiate pathological stage (pT) (T2ab, T2c, and T3) and the Gleason score (GS)7 group from GS6 and GS5, as well as identify cases of low aggressive potential, defined as GS≤6 and T2. Among the 111 measured biopsy cores, to evaluate the spatial distribution of the hypothesized PCa metabolomic fields, we identified the following four patient groups. A) The measured biopsy cores contained PCa glands (n=14), and for the cases where the measured cores were Hb: B) PCa glands were detected from the same quadrant by another biopsy core (n=13), C) PCa glands were seen in the adjacent quadrants (n=26), and D) PCa glands were located in the further away quadrants (n=15). Our results using the biopsy samples show that a number of spectral regions and profiles display significant differences among the four groups, including taurine at 3.43 ppm (p=0.0003), alanine at 1.47 (p=0.0011), PC1 (p=0.0001), and PC4 (p&amp;lt;0.0001). Conclusions: Our results presented here demonstrate the existence of PCa metabolomic fields. While more systematically designed studies are necessary to fully evaluate and understand the extent of the fields, the existence of these fields, nevertheless, presents an immediate clinical implication: with the enlarged PCa “metabolomic lesions," the implementation of PCa metabolomic imaging may realize the widely searched goal of targeted PCa biopsy to overcome the current histology error seen in the PCa clinic. Citation Format: Emily A. Decelle, Yannick Berker, Tilman Schwessinger, Shulin Wu, W Scott McDougal, Chin-Lee Wu, Leo L. Cheng. Evaluation of prostate cancer metabolomic field effects with 1H HRMAS MRS and prostate needle biopsies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3227. doi:10.1158/1538-7445.AM2013-3227

Spatially matched in vivo and ex vivo MR metabolic profiles of prostate cancer – investigation of a correlation with Gleason score

MR metabolic profiling of the prostate is promising as an additional diagnostic approach to separate indolent from aggressive prostate cancer. The objective of this study was to assess the relationship between the Gleason score and the metabolic biomarker (choline + creatine + spermine)/citrate (CCS/C) measured by ex vivo high-resolution magic angle spinning MRS (HR-MAS MRS) and in vivo MRSI, and to evaluate the correlation between in vivo- and ex vivo-measured metabolite ratios from spatially matched prostate regions. Patients (n = 13) underwent in vivo MRSI prior to radical prostatectomy. A prostate tissue slice was snap-frozen shortly after surgery and the locations of tissue samples (n = 40) collected for ex vivo HR-MAS were matched to in vivo MRSI voxels (n = 40). In vivo MRSI was performed on a 3T clinical MR system and ex vivo HR-MAS on a 14.1T magnet. Relative metabolite concentrations were calculated by LCModel fitting of in vivo spectra and by peak integration of ex vivo spectra. Spearman's rank correlations (ρ) between CCS/C from in vivo and ex vivo MR spectra, and with their corresponding Gleason score, were calculated. There was a strong positive correlation between the Gleason score and CCS/C measured both in vivo and ex vivo (ρ = 0.77 and ρ = 0.69, respectively; p < 0.001), and between in vivo and ex vivo metabolite ratios from spatially matched regions (ρ = 0.67, p < 0.001). Our data indicate that MR metabolic profiling is a potentially useful tool for the assessment of cancer aggressiveness. Moreover, the good correlation between in vivo- and ex vivo-measured CCS/C demonstrates that our method is able to bridge MRSI and HR-MAS molecular analysis.

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

BackgroundToday'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.MethodsPatients (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.ResultsAll 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.ConclusionsThe 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.