Biochemical characterization of metastatic lymph nodes of breast cancer patients by in vitro 1H magnetic resonance spectroscopy: a pilot study

Enhanced spectral resolution for correlated spectroscopic imaging using inner-product and covariance transform: a pilot analysis of metabolites and lipids in breast cancer in vivo

Acquisition duration of correlated spectroscopy in vivo can be longer due to a large number of t1 increments along the indirect (F1) dimension. Limited number of t1 increments on the other hand leads to poor spectral resolution along F1. Covariance transformation (CT) instead of Fourier transform along t1 is an alternative way of increasing the resolution of the 2D COSY spectrum. Prospectively undersampled five-dimensional echo-planar correlated spectroscopic imaging (EP-COSI) data from ten malignant patients and ten healthy women were acquired and reconstructed using compressed sensing. The COSY spectrum at each voxel location was then generated using FFT, CT and a variant of CT called Inner Product (IP). Metabolite and lipid ratios were computed with respect to water from unsuppressed one-dimensional spectrum. The effects of t1-ridging artifacts commonly seen with FFT were not observed with CT/IP. Statistically significant differences were observed in the fat cross peaks measured with CT/IP/FFT. Spectral resolution was increased ~ 8.5 times (~ 19.53 Hz in FFT, ~ 2.32 Hz in CT/IP) without affecting the spectral width along F1 was possible with CT/IP. CT and IP enabled substantially increased F1 resolution effectively with significant gain in scan time and reliable measure of unsaturation index as a biomarker for malignant breast cancer.

Ensemble Learning for Breast Cancer Lesion Classification: A Pilot Validation Using Correlated Spectroscopic Imaging and Diffusion-Weighted Imaging

The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional echo-planar correlated spectroscopic imaging (5D EP-COSI) and diffusion-weighted imaging (DWI). Twenty-four different metabolite and lipid ratios with respect to diagonal fat peaks (1.4 ppm, 5.4 ppm) from 2D spectra, and water and fat peaks (4.7 ppm, 1.4 ppm) from one-dimensional non-water-suppressed (NWS) spectra were used as the features. Additionally, water fraction, fat fraction and water-to-fat ratios from NWS spectra and apparent diffusion coefficients (ADC) from DWI were included. The nine most important features were identified using recursive feature elimination, sequential forward selection and correlation analysis. XGBoost (AUC: 93.0%, Accuracy: 85.7%, F1-score: 88.9%, Precision: 88.2%, Sensitivity: 90.4%, Specificity: 84.6%) and GradientBoost (AUC: 94.3%, Accuracy: 89.3%, F1-score: 90.7%, Precision: 87.9%, Sensitivity: 94.2%, Specificity: 83.4%) were the best-performing models. Conventional biomarkers like choline, myo-Inositol, and glycine were statistically significant predictors. Key features contributing to the classification were ADC, 2D diagonal peaks at 0.9 ppm, 2.1 ppm, 3.5 ppm, and 5.4 ppm, cross peaks between 1.4 and 0.9 ppm, 4.3 and 4.1 ppm, 2.3 and 1.6 ppm, and the triglyceryl-fat cross peak. The results highlight the contribution of the 2D spectral peaks to the model, and they demonstrate the potential of 5D EP-COSI for early breast cancer detection.

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

Correlated MR spectroscopic imaging of breast cancer to investigate metabolites and lipids: acceleration and compressed sensing reconstruction

Objectives

The main objective of this work was to detect novel biomarkers in breast cancer by spreading the MR spectra over two dimensions in multiple spatial locations using an accelerated 5D EP-COSI technology.

Methods

The 5D EP-COSI data were non-uniformly undersampled with an acceleration factor of 8 and reconstructed using group sparsity-based compressed sensing reconstruction. Different metabolite and lipid ratios were then quantified and statistically analyzed for significance. Linear discriminant models based on the quantified metabolite and lipid ratios were generated. Spectroscopic images of the quantified metabolite and lipid ratios were also reconstructed.

Results

The 2D COSY spectra generated using the 5D EP-COSI technique showed differences among healthy, benign, and malignant tissues in terms of their mean values of metabolite and lipid ratios, especially the ratios of potential novel biomarkers based on unsaturated fatty acids, myo-inositol, and glycine. It is further shown the potential of choline and unsaturated lipid ratio maps, generated from the quantified COSY signals across multiple locations in the breast, to serve as complementary markers of malignancy that can be added to the multiparametric MR protocol. Discriminant models using metabolite and lipid ratios were found to be statistically significant for classifying benign and malignant tumor from healthy tissues.

Conclusions

Accelerated 5D EP-COSI technique demonstrates the potential to detect novel biomarkers such as glycine, myo-inositol, and unsaturated fatty acids in addition to commonly reported choline in breast cancer, and facilitates metabolite and lipid ratio maps which have the potential to play a significant role in breast cancer detection.

Advances in knowledge

This study presents the first evaluation of a multidimensional MR spectroscopic imaging technique for the detection of potentially novel biomarkers based on glycine, myo-inositol, and unsaturated fatty acids, in addition to commonly reported choline. Spatial mapping of choline and unsaturated fatty acid ratios with respect to water in malignant and benign breast masses are also shown. These metabolic characteristics may serve as additional biomarkers for improving the diagnostic and therapeutic evaluation of breast cancer.

Magnetic Resonance Imaging (MRI) and MR Spectroscopic Methods in Understanding Breast Cancer Biology and Metabolism

A common malignancy that affects women is breast cancer. It is the second leading cause of cancer-related death among women. Metabolic reprogramming occurs during cancer growth, invasion, and metastases. Functional magnetic resonance (MR) methods comprising an array of techniques have shown potential for illustrating physiological and molecular processes changes before anatomical manifestations on conventional MR imaging. Among these, in vivo proton (1H) MR spectroscopy (MRS) is widely used for differentiating breast malignancy from benign diseases by measuring elevated choline-containing compounds. Further, the use of hyperpolarized 13C and 31P MRS enhanced the understanding of glucose and phospholipid metabolism. The metabolic profiling of an array of biological specimens (intact tissues, tissue extracts, and various biofluids such as blood, urine, nipple aspirates, and fine needle aspirates) can also be investigated through in vitro high-resolution NMR spectroscopy and high-resolution magic angle spectroscopy (HRMAS). Such studies can provide information on more metabolites than what is seen by in vivo MRS, thus providing a deeper insight into cancer biology and metabolism. The analysis of a large number of NMR spectral data sets through multivariate statistical methods classified the tumor sub-types. It showed enormous potential in the development of new therapeutic approaches. Recently, multiparametric MRI approaches were found to be helpful in elucidating the pathophysiology of cancer by quantifying structural, vasculature, diffusion, perfusion, and metabolic abnormalities in vivo. This review focuses on the applications of NMR, MRS, and MRI methods in understanding breast cancer biology and in the diagnosis and therapeutic monitoring of breast cancer.

Qualitative and Quantitative Evaluation of Chemical Constituents from Shuanghuanglian Injection Using Nuclear Magnetic Resonance Spectroscopy

By employing nuclear magnetic resonance (NMR), we implemented a chemical research on Shuanghuanglian injection (SHLI) and identified 17 components, including eight primary metabolites and nine secondary metabolites. Guided by the approach of network pharmacology, the potential activities were briefly predicted for seven primary metabolites except for formic acid, such as anti-inflammation, antioxidation, and cardiovascular protection. The focused primary metabolites were quantified by a proton nuclear magnetic resonance (¹H-NMR) method, which was verified with good linearity and satisfactory precision, repeatability, stability, and accuracy (except for myo-inositol with mean recovery at 135.78%). Based on the successfully established method, seven primary metabolites were effectively quantified with a slight fluctuation in 20 batches of SHLIs. The average total content of these compounds was 6.85 mg/mL, accounting for 24.84% in total solid of SHLI. This research provides an alternative method for analysis of primary metabolites and contributes to the quality control of SHLI.

MR spectroscopy in breast cancer metabolomics

Breast cancer poses a significant health care challenge worldwide requiring early detection and effective treatment strategies for better patient outcome. A deeper understanding of the breast cancer biology and metabolism may help developing better diagnostic and therapeutic approaches. Metabolomic studies give a comprehensive analysis of small molecule metabolites present in human tissues in vivo. The changes in the level of these metabolites provide information on the complex mechanism of the development of the disease and its progression. Metabolomic approach using analytical techniques such as magnetic resonance spectroscopy (MRS) has evolved as an important tool for identifying clinically relevant metabolic biomarkers. The metabolic characterization of breast lesions using in-vivo MRS has shown that malignant breast tissues contain elevated levels of choline containing compounds (tCho), suggesting rapid proliferation of cancer cells and alterations in membrane metabolism. Also, tCho has been identified as one of the important biomarkers that help to enhance the diagnostic accuracy of dynamic contrast enhanced magnetic resonance imaging and also for monitoring treatment response. Further, metabolome of malignant tissues can be studied using ex vivo and in vitro MRS at high magnetic fields. This provided the advantage of detection of a large number of compounds that facilitated more comprehensive insight into the altered metabolic pathways associated with the cancer development and progression and also in identification of several metabolites as potential biomarkers. This article briefly reviews the role of MRS based metabolic profiling in the discovery of biomarkers and understanding of the altered metabolism in breast cancer.

A Crosstalk- and Interferent-Free Dual Electrode Amperometric Biosensor for the Simultaneous Determination of Choline and Phosphocholine

Choline (Ch) and phosphocholine (PCh) levels in tissues are associated to tissue growth and so to carcinogenesis. Till now, only highly sophisticated and expensive techniques like those based on NMR spectroscopy or GC/LC- high resolution mass spectrometry permitted Ch and PCh analysis but very few of them were capable of a simultaneous determination of these analytes. Thus, a never reported before amperometric biosensor for PCh analysis based on choline oxidase and alkaline phosphatase co-immobilized onto a Pt electrode by co-crosslinking has been developed. Coupling the developed biosensor with a parallel sensor but specific to Ch, a crosstalk-free dual electrode biosensor was also developed, permitting the simultaneous determination of Ch and PCh in flow injection analysis. This novel sensing device performed remarkably in terms of sensitivity, linear range, and limit of detection so to exceed in most cases the more complex analytical instrumentations. Further, electrode modification by overoxidized polypyrrole permitted the development of a fouling- and interferent-free dual electrode biosensor which appeared promising for the simultaneous determination of Ch and PCh in a real sample.

Clinical relevance of total choline (tCho) quantification in suspicious lesions on multiparametric breast MRI

Purpose

To assess the additional value of quantitative tCho evaluation to diagnose malignancy and lymph node metastases in suspicious lesions on multiparametric breast MRI (mpMRI, BI-RADS 4, and BI-RADS 5).

Methods

One hundred twenty-one patients that demonstrated suspicious multiparametric breast MRI lesions using DCE, T2w, and diffusion-weighted (DW) images were prospectively enrolled in this IRB-approved study. All underwent single-voxel proton MR spectroscopy (¹H-MRS, point-resolved spectroscopy sequence, TR 2000 ms, TE 272 ms) with and without water suppression. The total choline (tCho) amplitude was measured and normalized to millimoles/liter according to established methodology by two independent readers (R1, R2). ROC-analysis was employed to predict malignancy and lymph node status by tCho results.

Results

One hundred three patients with 74 malignant and 29 benign lesions had full ¹H-MRS data. The area under the ROC curve (AUC) for prediction of malignancy was 0.816 (R1) and 0.809 (R2). A cutoff of 0.8 mmol/l tCho could diagnose malignancy with a sensitivity of > 95%. For prediction of lymph node metastases, tCho measurements achieved an AUC of 0.760 (R1) and 0.788 (R2). At tCho levels < 2.4 mmol/l, no metastatic lymph nodes were found.

Conclusion

Quantitative tCho evaluation from ¹H-MRS allowed diagnose malignancy and lymph node status in breast lesions suspicious on multiparametric breast MRI. tCho therefore demonstrated the potential to downgrade suspicious mpMRI lesions and stratify the risk of lymph node metastases for improved patient management.

Key Points

• Quantitative tCho evaluation can distinguish benign from malignant breast lesions suspicious after multiparametric MRI assessment.

• Quantitative tCho levels are associated with lymph node status in breast cancer.

• Quantitative tCho levels are higher in hormonal receptor positive compared to hormonal receptor negative lesions.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-06678-z) contains supplementary material, which is available to authorized users.

Noninvasive detection of cancer spread to lymph nodes: A review of molecular imaging principles and protocols

Identification of cancer spread to tumor-draining lymph nodes offers critical information for guiding treatment in many cancer types. Current clinical methods of nodal staging are invasive and can have substantial negative side effects. Molecular imaging protocols have long been proposed as a less invasive means of nodal staging, having the potential to enable highly sensitive and specific evaluations. This review article summarizes the current status and future perspectives for molecular targeted nodal staging.

Alteration in lipid composition differentiates breast cancer tissues: a 1H HRMAS NMR metabolomic study

INTRODUCTION

Breast cancer is the most frequent diagnosed cancer among women with a mortality rate of 15% of all cancer related deaths in women. Breast cancer is heterogeneous in nature and produces plethora of metabolites allowing its early detection using molecular diagnostic techniques like magnetic resonance spectroscopy.

OBJECTIVES

To evaluate the variation in metabolic profile of breast cancer focusing on lipids as triglycerides (TG) and free fatty acids (FFA) that may alter in malignant breast tissues and lymph nodes from adjacent benign breast tissues by HRMAS ¹H NMR spectroscopy.

METHODS

The ¹H NMR spectra recorded on 173 tissue specimens comprising of breast tumor tissues, adjacent tissues, few lymph nodes and overlying skin tissues obtained from 67 patients suffering from breast cancer. Multivariate statistical analysis was employed to identify metabolites acting as major confounders for differentiation of malignancy.

RESULT

Reduction in lipid content were observed in malignant breast tissues along with a higher fraction of FFA. Four small molecule metabolites e.g., choline containing compounds (Chocc), taurine, glycine, and glutamate were also identified as major confounders. The test set for prediction provided sensitivity and specificity of more than 90% excluding the lymph nodes and skin tissues.

CONCLUSION

Fatty acids composition in breast cancer using in vivo magnetic resonance spectroscopy (MRS) is gaining its importance in clinical settings (Coum et al. in Magn Reson Mater Phys Biol Med 29:1-4, 2016). The present study may help in future for precise evaluation of lipid classification including small molecules as a source of early diagnosis of invasive ductal carcinoma by employing in vivo magnetic resonance spectroscopic methods.

Metabolic Portraits of Breast Cancer by HR MAS MR Spectroscopy of Intact Tissue Samples

Despite progress in early detection and therapeutic strategies, breast cancer remains the second leading cause of cancer-related death among women globally. Due to the heterogeneity and complexity of tumor biology, breast cancer patients with similar diagnosis might have different prognosis and response to treatment. Thus, deeper understanding of individual tumor properties is necessary. Cancer cells must be able to convert nutrients to biomass while maintaining energy production, which requires reprogramming of central metabolic processes in the cells. This phenomenon is increasingly recognized as a potential target for treatment, but also as a source for biomarkers that can be used for prognosis, risk stratification and therapy monitoring. Magnetic resonance (MR) metabolomics is a widely used approach in translational research, aiming to identify clinically relevant metabolic biomarkers or generate novel understanding of the molecular biology in tumors. Ex vivo proton high-resolution magic angle spinning (HR MAS) MR spectroscopy is widely used to study central metabolic processes in a non-destructive manner. Here we review the current status for HR MAS MR spectroscopy findings in breast cancer in relation to glucose, amino acid and choline metabolism.

¹H magnetic resonance spectroscopy: a review of the current literature and its potential utility in veterinary oncology

Advanced imaging of veterinary cancer patients has evolved in recent years and modalities once limited to human medicine have now been described for diagnostic purposes in veterinary medicine (positron emission tomography/computed tomography, single-photon emission computed tomography, whole body magnetic resonance imaging). Magnetic resonance spectroscopy (MRS) is a non-invasive and non-ionizing technique that is well described in the human medical literature and is most frequently used to evaluate the metabolic activity of tissues with questionable malignant transformation. Differentiation of neoplastic tissue from surrounding normal tissue is dependent on variations in cellular metabolism. Positive identification of malignancy can be made when neoplastic alterations are occurring at the cellular level prior to gross anatomic changes. This improved, early detection of cancer occurrence (or recurrence) can improve patient survival and direct medical therapy. MRS techniques are largely underutilized in veterinary medicine, with current research predominantly limited to the brain (both evaluation of normal and diseased tissue). Given the clinical utility of MRS in humans, the technique may also be useful in the staging of cancer in veterinary medicine.

Is higher lactate an indicator of tumor metastatic risk? A pilot MRS study using hyperpolarized (13)C-pyruvate

RATIONALE AND OBJECTIVES

Cancer cells generate more lactate than normal cells under both aerobic and hypoxic conditions-exhibiting the so-called Warburg effect. However, the relationship between the Warburg effect and tumor metastatic potential remains controversial. We intend to investigate whether the higher lactate reflects higher tumor metastatic potential.

MATERIALS AND METHODS

We used hyperpolarized (13)C-pyruvate magnetic resonance spectroscopy (MRS) to compare lactate (13)C-labeling in vivo in mouse xenografts of the highly metastatic (MDA-MB-231) and the relatively indolent (MCF-7) human breast cancer cell lines. We obtained the kinetic parameters of the lactate dehydrogenase (LDH)-catalyzed reaction by three methods of data analysis including the differential equation fit, q-ratio fit, and ratio fit methods.

RESULTS

Consistent results from the three methods showed that the highly metastatic tumors exhibited a smaller apparent forward rate constant (k(+) = 0.060 ± 0.004 s(-1)) than the relatively indolent tumors (k(+) = 0.097 ± 0.013 s(-1)). The ratio fit generated the greatest statistical significance for the difference (P = .02). No significant difference in the reverse rate constant was found between the two tumor lines.

CONCLUSIONS

The result indicates that the less metastatic breast tumors may produce more lactate than the highly metastatic ones from the injected (13)C-pyruvate and supports the notion that breast tumor metastatic risk is not necessarily associated with the high levels of glycolysis and lactate production. More studies are needed to confirm whether and how much the measured apparent rate constants are affected by the membrane transporter activity and whether they are primarily determined by the LDH activity.

Revealing the metabonomic variation of EC using ¹H-NMR spectroscopy and its association with the clinicopathological characteristics

In this study, (1)H NMR-based metabonomics has been applied to investigate esophageal cancer metabolic signatures in plasma and urine, purpose of assessing the diagnostic potential of this approach and gaining novel insights into esophageal cancer metabolism and systemic effects. Plasma and urine samples from esophageal cancer patients (n = 108) and a control healthy group (n = 40) were analyzed by Nuclear Magnetic Resonance (NMR) spectroscopy (600 MHz), and their spectral profiles subjected to Orthogonal Projections to Latent Structures (OPLS-DA) for multivariate statistics. Potential metabolic biomarkers were identified using data base comparisons used for examining the significance of metabolites. Compared to healthy controls, esophageal cancer plasma had higher levels of dimethylamine, α-glucose, β-glucose, citric acid, together with lower levels of Leucine, alanine, isoleucine, valine, glycoprotein, lactate, acetone, acetate, choline, isobutyrate, unsaturated lipid, VLDL, LDL, 1-methylhistidine; Compared to healthy controls, esophageal cancer urine had higher levels of Mannitol, glutamate, γ-propalanine, phenylalanine, acetate, allantoin, pyruvate, tyrosine, β-glucose and guinolinate, together with lower levels of N-acetylcysteine, valine, dihydrothymine, hippurate, methylguanidine, 1-methylnicotin- amide and Citric acid; Very good discrimination between cancer and control groups was achieved by multivariate modeling of plasma and urinary profiles. (1)H NMR-based metabolite profiling analysis was shown to be an effective approach to differentiating between patients with EC and healthy subjects. Good sensitivity and selectivity were shown by using the metabolite markers discovered to predict the classification of samples from the healthy control group and the patients with the disease. Plasma and urine metabolic profiling may have potential for early diagnosis of EC and may enhance our understanding of its mechanisms.

The challenges of integrating molecular imaging into the optimization of cancer therapy

We review novel, in vivo and tissue-based imaging technologies that monitor and optimize cancer therapeutics. Recent advances in cancer treatment centre around the development of targeted therapies and personalisation of treatment regimes to individual tumour characteristics. However, clinical outcomes have not improved as expected. Further development of the use of molecular imaging to predict or assess treatment response must address spatial heterogeneity of cancer within the body. A combination of different imaging modalities should be used to relate the effect of the drug to dosing regimen or effective drug concentration at the local site of action. Molecular imaging provides a functional and dynamic read-out of cancer therapeutics, from nanometre to whole body scale. At the whole body scale, an increase in the sensitivity and specificity of the imaging probe is required to localise (micro)metastatic foci and/or residual disease that are currently below the limit of detection. The use of image-guided endoscopic biopsy can produce tumour cells or tissues for nanoscopic analysis in a relatively patient-compliant manner, thereby linking clinical imaging to a more precise assessment of molecular mechanisms. This multimodality imaging approach (in combination with genetics/genomic information) could be used to bridge the gap between our knowledge of mechanisms underlying the processes of metastasis, tumour dormancy and routine clinical practice. Treatment regimes could therefore be individually tailored both at diagnosis and throughout treatment, through monitoring of drug pharmacodynamics providing an early read-out of response or resistance.

[Non-invasive imaging modalities for preoperative axillary lymph node staging in patients with breast cancer]

In the last decade sentinel lymph node biopsy has become a well-established method for axillary lymph node staging in patients with breast cancer. Using preoperative imaging modalities it can be tested whether patients are suitable for sentinel node biopsy or if they should directly undergo an axillary dissection. The imaging modalities used must be mainly characterized by a high positive predictive value (PPV). For this question B-mode ultrasound is the best evaluated method and provides clear morphological signs for a high PPV (>90%) but the sensitivity barely exceeds 50%. It has not yet been proven whether other modalities such as duplex sonography, magnetic resonance imaging, computed tomography (CT) or scintigraphy might achieve a higher sensitivity while still maintaining a high PPV. There is only some evidence that positron emission tomography (PET) might achieve a higher sensitivity. This should be confirmed by further studies because PET or PET/CT will play an increasing role for an initial whole body staging in patients with breast cancer in the near future.

Glycosidic intermediates identified in 1H MR spectra of intact tumour cells may contribute to the clarification of aspects of glycosylation pathways

The glycosylation process, through the addition of carbohydrates, is a major post-translational modification of proteins and glycolipids. Proteins may be glycosylated in either the secretory pathway leading to N-linked or O-linked glycoproteins or as nucleocytoplasmic glycosylation that targets only single proteins involving a single β-linked N-acetylglucosamine. In both cases, the key precursors are the uridine diphospho-N-acetylhexosamines synthesised by the hexosamine biosynthetic pathway. Furthermore, uridine diphospho-N-acetylglucosamine participates in the biosynthesis of sialic acid. In this work, we propose MRS for the detection of uridine diphospho-N-acetylhexosamines visible in high-resolution MR spectra of intact cells from different human tumours. Signals from the nucleotide and amino sugar moieties, including amide signals observed for the first time in whole cells, are assigned, also taking advantage of spectral changes that follow cell treatment with ammonium chloride. Finally, parallel changes in uridine diphospho-N-acetylhexosamines and glutamine pools, observed after pH changes induced by ammonium chloride in the different tumour cell lines, may provide more details on the glycosylation processes.

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, (1)H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology.

Artificial neural networks for classification in metabolomic studies of whole cells using 1H nuclear magnetic resonance

We report the successful classification, by artificial neural networks (ANNs), of (1)H NMR spectroscopic data recorded on whole-cell culture samples of four different lung carcinoma cell lines, which display different drug resistance patterns. The robustness of the approach was demonstrated by its ability to classify the cell line correctly in 100% of cases, despite the demonstrated presence of operator-induced sources of variation, and irrespective of which spectra are used for training and for validation. The study demonstrates the potential of ANN for lung carcinoma classification in realistic situations.

Similarity in the metabolic profile in macroscopically involved and un-involved colonic mucosa in patients with inflammatory bowel disease: an in vitro proton ((1)H) MR spectroscopy study

BACKGROUND

The histological extent of inflammatory bowel disease (IBD) is greater than that evident by colonoscopic evaluation. We hypothesized that metabolic profile in macroscopically un-involved colonic mucosa in IBD is similar to that of controls with healthy colon. We thus assessed the differences in metabolic profile in macroscopically involved and un-involved colonic mucosa of IBD patients to further substantiate the extent of disease.

PATIENTS AND METHODS

Colonic mucosal biopsies were obtained and snap frozen from both the macroscopically un-involved and involved colonic mucosa of IBD patients and macroscopically normal colonic mucosa of controls and were subjected to in-vitro high-resolution proton ((1)H) magnetic resonance (MR) spectroscopy and the concentrations of metabolites were determined.

RESULTS

Thirty-two metabolites were assigned in the proton MR spectrum of colonic mucosa of IBD patients. The concentrations of amino acids (isoleucine, leucine, valine, arginine, lysine, glutamine/glutamate, alanine), membrane metabolites (choline, glycerophosphorylcholine/phosphorylcholine), glycolytic product (lactate) and short chain fatty acid (formate) were significantly lower while significantly high level of glucose were observed in the macroscopically un-involved colonic mucosa of IBD patients compared to the macroscopically normal mucosa of controls. There was no significant difference in the concentrations of metabolites in macroscopically involved and un-involved colonic mucosa of IBD patients.

CONCLUSIONS

The metabolic profile in macroscopically un-involved colonic mucosa of IBD patients is similar to that of macroscopically involved mucosa but different from colonic mucosa of controls. This suggests that even macroscopically un-involved colonic mucosa is metabolically abnormal and may explain the increase in extent of disease with time.

1H-14N HSQC detection of choline-containing compounds in solutions

Choline nitrogen ((14)N) has a long relaxation time (seconds) which is due to the highly symmetric chemical environments. (14)N in choline also has coupling constants with protons (0.6 Hz to methyl protons, 2.7 Hz to CH(2)O protons and 0.2 Hz to NCH(2) protons). Based on these properties, we introduce a two-dimensional NMR method to detect choline and its derivatives in solutions. This method is the (1)H-(14)N hetero-nuclear single-quantum correlation (HSQC) experiment which has been developed in solid-state NMR in recent years. Experiments have demonstrated that the (1)H-(14)N HSQC technique is a sensitive method for detection of choline-containing compounds in solutions. From 1mM choline solution in 16 min on a 500 MHz NMR spectrometer, a (1)H-(14)N HSQC spectrum has been recorded with a signal-to-noise ratio of 1700. Free choline, phosphocholine and glycerophosphocholine in milk can be well separated in (1)H-(14)N HSQC spectra. This technique would become a promising analytical approach to mixture analyses where choline-containing compounds are of interest, such as tissue extracts, body fluids and food solutions.

In vivo proton MR spectroscopy of the breast using the total choline peak integral as a marker of malignancy

OBJECTIVE

The purpose of our study was to use the total choline-containing compound (tCho) peak integral as a marker of malignancy in breast MR spectroscopy (MRS).

SUBJECTS AND METHODS

Forty-eight single-voxel water- and fat-suppressed 1.5-T MRS measurements were performed in 42 patients, obtaining both absolute tCho peak integral and tCho peak integral normalized for the volume of interest (VOI). Our reference standard was histology for lesions with BI-RADS category 4 and 5 and histology or at least a 2-year follow-up for findings with BI-RADS 2 and 3 and normal glands. Receiver operating characteristic (ROC) analysis, Mann-Whitney U test, and Spearman's rank correlation were used.

RESULTS

Three of 48 measurements (6%) failed. Of the remaining 45 spectra, 18 nonmalignant tissues showed no tCho peak, eight nonmalignant tissues showed a tCho peak integral from 0.99 to 9.03 arbitrary units (AU), and 19 malignant lesions showed a tCho peak integral from 1.26 to 19.80 AU. The diameter of nonmalignant tissues was 16.9 +/- 7.4 mm; that of malignant lesions was 15.3 +/- 6.9 mm (p = 0.308). At ROC analysis, the optimal threshold was 1.90 AU for absolute tCho peak, with 0.895 (17/19) sensitivity, 0.923 (24/26) specificity, and an AUC (area under the curve) of 0.917 (95% CI, 0.822-1.000); the optimal threshold was 0.85 AU/mL for the normalized tCho peak integral with 0.842 (16/19) sensitivity, 0.885 (23/26) specificity, and an AUC of 0.941 (0.879-1.000) (p = 0.470). A negative correlation (p = 0.011) was found between the VOI and the normalized tCho peak integral of malignant tissues.

CONCLUSION

Breast MRS using tCho peak integral reaches a high level of diagnostic performance.

Magnetic resonance imaging methodology

INTRODUCTION

Magnetic resonance (MR) methods are non-invasive techniques to provide detailed, multi-parametric information on human anatomy, function and metabolism. Sensitivity, specificity, spatial and temporal resolution may, however, vary depending on hardware (e.g., field strength, gradient strength and speed) and software (optimised measurement protocols and parameters for the various techniques). Furthermore, multi-modality imaging may enhance specificity to better characterise complex disease patterns.

OBJECTIVE

Positron emission tomography (PET) is an interesting, largely complementary modality, which might be combined with MR. Despite obvious advantages, combining these rather different physical methods may also pose challenging problems. At this early stage, it seems that PET quality may be preserved in the magnetic field and, if an adequate detector material is used for the PET, MR sensitivity should not be significantly degraded. Again, this may vary for the different MR techniques, whereby functional and metabolic MR is more susceptible than standard anatomical imaging.

DISCUSSION

Here we provide a short introduction to MR basics and MR techniques, also discussing advantages, artefacts and problems when MR hardware and PET detectors are combined. In addition to references for more detailed descriptions of MR fundamentals and applications, we provide an early outlook on this novel and exciting multi-modality approach to PET/MR.

Biochemical characterization of breast tumors by in vivo and in vitro magnetic resonance spectroscopy (MRS)

Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) have evolved as sensitive tools for anatomic and metabolic evaluation of breast cancer. In vivo MRS studies have documented the presence of choline containing compounds (tCho) as a reliable biochemical marker of malignancy and also useful for monitoring the tumor response to therapy. Recent studies on the absolute quantification of tCho are expected to provide cut-off values for discrimination of various breast pathologies. Addition of MRS investigation was also reported to increase the specificity of MRI. Further, ex vivo and in vitro MRS studies of intact tissues and tissue extracts provided several metabolites that were not be detected in vivo and provided insight into underlying biochemistry of the disease processes. In this review, we present briefly the role of various 1H MRS methods used in breast cancer research and their potential in relation to diagnosis, monitoring of therapeutic response and metabolism.

Investigation of breast cancer using two-dimensional MRS

Proton (1H) MRS enables non-invasive biochemical assay with the potential to characterize malignant, benign and healthy breast tissues. In vitro studies using perchloric acid extracts and ex vivo magic angle spinning spectroscopy of intact biopsy tissues have been used to identify detectable metabolic alterations in breast cancer. The challenges of 1H MRS in vivo include low sensitivity and significant overlap of resonances due to limited chemical shift dispersion and significant inhomogeneous broadening at most clinical magnetic field strengths. Improvement in spectral resolution can be achieved in vivo and in vitro by recording the MR spectra spread over more than one dimension, thus facilitating unambiguous assignment of metabolite and lipid resonances in breast cancer. This article reviews the recent progress with two-dimensional MRS of breast cancer in vitro, ex vivo and in vivo. The discussion includes unambiguous detection of saturated and unsaturated fatty acids, as well as choline-containing groups such as free choline, phosphocholine, glycerophosphocholine and ethanolamines using two-dimensional MRS. In addition, characterization of invasive ductal carcinomas and healthy fatty/glandular breast tissues non-invasively using the classification and regression tree (CART) analysis of two-dimensional MRS data is reviewed.

Metabolism of the colonic mucosa in patients with inflammatory bowel diseases: an in vitro proton magnetic resonance spectroscopy study

Metabolism of the colonic mucosa of patients with ulcerative colitis (UC; n=31) and Crohn's disease (CD; n=26) and normal mucosa (control, n=26) was investigated using in vitro high-resolution proton magnetic resonance spectroscopy. Of the 31 UC patients, 20 were in the active phase and 11 were in the remission phase of the disease. Out of 26 CD patients, 20 were in the active phase, while 6 were in the remission phase of the disease. Twenty-nine metabolites were assigned unambiguously in the perchloric acid extract of colonic mucosa. In the active phase of UC and CD, significantly lower (P Collapse

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MESH Headings

• Analysis of Variance
• Case-Control Studies
• Colon/metabolism
• Humans
• In Vitro Techniques
• Inflammatory Bowel Diseases/metabolism
• Intestinal Mucosa/metabolism
• Magnetic Resonance Spectroscopy/methods
• Perchlorates

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Affiliation(s)

Krithika Balasubramanian Department of NMR, All India Institute of Medical Sciences, New Delhi 110 029, India
Sandeep Kumar
Rajeev R Singh
Uma Sharma
Vineet Ahuja
Govind K Makharia
Naranamangalam R Jagannathan

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Metabolomic studies of human lung carcinoma cell lines using in vitro (1)H NMR of whole cells and cellular extracts

We report principal component analysis (PCA) of (1)H NMR spectra recorded for a group of human lung carcinoma cell lines in culture and (1)H NMR analysis of extracts from the same samples. The samples studied were cells of lung tumour origin with different chemotherapy drug resistance patterns. For whole cells, it was found that the statistically significant causes of spectral variation were an increase in the choline and a decrease in the methylene mobile lipid (1)H resonance intensities, which correlate with our knowledge of the level of resistance displayed by the different cells. Similarly, in the (1)H NMR spectra of the aqueous and lipophilic extracts, significant quantitative differences in the metabolite distributions were apparent, which are consistent with the PCA results.

Causes and consequences of increased glucose metabolism of cancers

In this review we examine the mechanisms (causes) underlying the increased glucose consumption observed in tumors within a teleological context (consequences). In other words, we will ask not only "How do cancers have high glycolysis?" but also, "Why?" We believe that the insights gained from answering the latter question support the conclusion that elevated glucose consumption is a necessary component of carcinogenesis. Specifically we propose that glycolysis is elevated because it produces acid, which provides an evolutionary advantage to cancer cells vis-à-vis normal parenchyma into which they invade.

Novel corrective equations for complete estimation of human tissue lipids after their partial destruction by perchloric acid pre-treatment: high-resolution (1)H-NMR-based study

Owing to the small quantity of tissue available in human biopsy specimens, aqueous and lipid components often have to be determined in the same tissue sample. Perchloric acid (PCA) used for the extraction of aqueous metabolites has a deleterious effect on lipid components; the severity of the damage is not known. In this study, human muscle tissue was first treated with PCA to extract aqueous metabolites, and the residue was then used for lipid extraction by conventional methods, i.e. the methods of Folch and Bligh & Dyer and a standardised one using methanol/chloroform (1:3, v/v) used in our laboratory. A (1)H-NMR spectrum was obtained for each lipid extract. Lipid was quantified by measuring the integral area of N(+)-(CH(3))(3) signals of phospholipids (PLs). Triacylglycerol (TG) and cholesterol (CHOL) were quantified using the -CH(2)- signals of glycerol and the C18 methyl signal, respectively. This study shows that prior use of PCA caused marked attenuation of TG, PL, and CHOL. This was confirmed by recovery experiments and observation of the direct effect of PCA on the standard lipid components. On the basis of the quantity of lipid lost in each case, three novel equations (with respect to TG, PL, and CHOL) were derived. Application of these equations to lipid quantities estimated in different pathological tissues after PCA pre-treatment produced values equivalent to those estimated without PCA use. This study conclusively shows that PCA pre-treatment damages all three lipid moieties, TG, PL, and CHOL. When PCA is used in a fixed ratio to the tissue, the lipid damage is also proportional and correctable by statistically derived equations. These equations will be useful in human biopsy specimens where aqueous and lipid components have to be studied using the same tissue sample because of the small quantity available.

Metabolic alterations in cultured mouse fibroblasts induced by an inhibitor of the tyrosine kinase receptor Fibroblast Growth Factor Receptor 1

Proton nuclear magnetic resonance (NMR) spectroscopy was used to identify and quantify the metabolites present in cultured mouse fibroblast cells 3T6 in their native state and after treatment with PD166866, an inhibitor of the fibroblast growth factor receptor. Cell extracts were prepared according to the Bligh-Dyer protocol which prevents artifacts deriving from the chemical demolition of macromolecules. Also the growth medium was subjected to the same extraction procedure. The NMR approach made possible the identification and quantification of about 40 different metabolites at nanomoles/mg of protein level: the biological relevance of the variation of some metabolite levels is discussed. Our experimental procedure offers a prospective method for the evaluation of variations of the metabolic profile deriving from different biochemical treatments of these cells.

Imaging breast cancer

Imaging has a significant role in diagnosing, treating, and monitoring breast cancer. Advances in this field are having a great impact in the clinical management of this disease. Breast cancer has now become an "outpatient cancer". This article describes the role and advances of imaging in breast cancer.

Phosphocholine as a biomarker of breast cancer: Molecular and biochemical studies

The discovery of metabolic and molecular markers that help improving the detection and diagnosis of breast cancer is an important goal to be achieved. A high composite-choline signal in magnetic resonance spectra of breast lesions has been demonstrated to improve the accuracy of breast cancer diagnosis. In the present study we revealed the principal molecular and biochemical steps associated with the induction of choline metabolism and phosphocholine accumulation in human breast cancer cell-lines in comparison with normal human mammary epithelial cells. We found upregulation of the expression levels of specific choline transporters: organic cation transporter-2 and choline high affinity transporter-1, as well as of the enzyme choline kinase alpha in the cancerous cells in comparison with that in the normal mammary epithelial cells. The expression levels of choline transporter like-1, organic cation transporter-1 and choline kinase beta were similar in normal and cancerous cells. We further showed that choline transport rates and choline kinase activity indeed increased by several fold in the cancer cells leading to the elevation of phosphocholine. The results strongly suggest that phosphocholine can serve as a biomarker of breast cancer reflecting upregulation of specific choline transporters and choline kinase genes.

Potential of magnetic resonance spectroscopy to detect metastasis in axillary lymph nodes in breast cancer

Focused pathological evaluation of axillary lymph nodes in breast cancer is gaining importance. Nuclear magnetic resonance (NMR) spectroscopy that assesses the whole of the specimen has the potential in evaluating micrometastases. The biochemical changes associated with breast cancer metastases in axillary nodes by in vitro NMR and its use in the detection of axillary metastases in a clinical setting in comparison with conventional histopathology is presented in this study. Eighty-eight lymph nodes obtained from 30 patients with breast cancer were investigated. Histopathology revealed metastases in 20 nodes from 11 patients, while in vitro NMR spectroscopy revealed metastases in 22 nodes. Out of these 22 nodes, 16 were the same, which showed metastases on histopathology, while 6 nodes have shown metastases only on in vitro magnetic resonance spectroscopy (MRS). These 6 nodes with suspicion of metastases on MRS were subjected to reevaluation with serial sectioning and immunohistochemistry, but no additional metastases were revealed. Forty metabolites could be identified from the MR spectrum of lymph nodes. The levels of the glycerophosphocholine-phosphocholine (GPC-PC), choline, lactate, alanine and uridine diphosphoglucose were elevated significantly in nodes with metastases. In addition, the intensity ratio of GPC-PC/threonine (Thr) was higher in nodes with metastases, and using this as marker, MRS detected the axillary metastases with a sensitivity, specificity and accuracy of 80%, 91% and 88%, respectively. Neoadjuvant chemotherapy (NACT) lowered the concentrations of GPC-PC and GPC-PC/Thr ratio. The accuracy of MRS in detecting metastases was 75% in patients who received NACT (n=9) as compared to 96% in those who did not (n=21). Our results demonstrate the potential of in vitro MRS in characterizing the metabolite profile of the axillary nodes with breast cancer metastases. It detected axillary metastases with reasonable accuracy and can be complementary to histopathological evaluation and immunohistochemistry.