A decade in prostate cancer: from NMR to metabolomics

Precise diagnosis and risk stratification of prostate cancer by comprehensive serum metabolic fingerprints: a prediction model study

OBJECTIVES

Prostate cancer (PCa) is one of the most common malignancies in men worldwide and has caused increasing clinical morbidity and mortality, making timely diagnosis and accurate staging crucial. The authors introduced a novel approach based on mass spectrometry for precise diagnosis and stratification of PCa to facilitate clinical decision-making.

METHODS

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis of trace blood samples was combined with machine learning algorithms to construct diagnostic and stratification models. A total of 367 subjects, comprising 181 with PCa and 186 with non-PCa were enrolled. Additional 60 subjects, comprising 30 with PCa and 30 with non-PCa were enrolled as an external cohort for validation. Subsequent metabolomic analysis was carried out using Autoflex MALDI-TOF, and the mass spectra were introduced into various algorithms to construct different models.

RESULTS

Serum metabolic fingerprints were successfully obtained from 181 patients with PCa and 186 patients with non-PCa. The diagnostic model based on the eight signals demonstrated a remarkable area under curve of 100% and was validated in the external cohort with the area under curve of 87.3%. Fifteen signals were selected for enrichment analysis, revealing the potential metabolic pathways that facilitate tumorigenesis. Furthermore, the stage prediction model with an overall accuracy of 85.9% precisely classified subjects with localized disease and those with metastasis. The risk stratification model, with an overall accuracy of 89.6%, precisely classified the subjects as low-risk and high-risk.

CONCLUSIONS

Our study facilitated the timely diagnosis and risk stratification of PCa and provided new insights into the underlying mechanisms of metabolic alterations in PCa.

Urinary Metabolomic Analysis of Prostate Cancer by UPLC-FTMS and UPLC-Ion Trap MSn

Accumulative evidence suggests metabolic disorders correlate with prostate cancer. Metabolic profiling of urine allows the measurement of numerous metabolites simultaneously. This study set up a metabolomic platform consisting of UPLC-FTMS and UPLC-ion trap MSⁿ for urine metabolome analysis. The platform improved retention time, mass accuracy, and signal stability. Additionally, the product ion spectrum obtained from ion trap MSⁿ facilitated structure elucidation of candidate metabolites, especially when authentic standards were not available. Urine samples from six hernia patients and six BPH patients were used for the initial establishment of the analytic platform. This platform was further employed to analyze the urine samples of 27 PCa and 49 BPH patients. Choosing the upper and lower 16% of metabolites, 258 metabolite candidates were selected. Twenty-four of them with AUC values larger than 0.65 were further selected. Eighteen of the twenty-four features can be matched in METLIN and HMDB. Eleven of the eighteen features can be interpreted by MSⁿ experiments. They were used for the combination achieving the best differential power. Finally, four metabolites were combined to reach the AUC value of 0.842 (CI 95, 0.7559 to 0.9279). This study demonstrates the urinary metabolomic analysis of prostate cancer and sheds light on future research.

Association of altered metabolic profiles and long non-coding RNAs expression with disease severity in breast cancer patients: analysis by 1H NMR spectroscopy and RT-q-PCR

INTRODUCTION

Globally, one of the major causes of cancer related deaths in women is breast cancer. Although metabolic pattern is altered in cancer patients, robust metabolic biomarkers with a potential to improve the screening and disease monitoring are lacking. A complete metabolome profiling of breast cancer patients may lead to the identification of diagnostic/prognostic markers and potential targets.

OBJECTIVES

The aim of this study was to analyze the metabolic profile in the serum from 43 breast cancer patients and 13 healthy individuals.

MATERIALS & METHODS

We used ¹H NMR spectroscopy for the identification and quantification of metabolites. q-RT-PCR was used to examine the relative expression of lncRNAs.

RESULTS

Metabolites such as amino acids, lipids, membrane metabolites, lipoproteins, and energy metabolites were observed in the serum from both patients and healthy individuals. Using unsupervised PCA, supervised PLS-DA, supervised OPLS-DA, and random forest classification, we observed that more than 25 metabolites were altered in the breast cancer patients. Metabolites with AUC value > 0.9 were selected for further analysis that revealed significant elevation of lactate, LPR and glycerol, while the level of glucose, succinate, and isobutyrate was reduced in breast cancer patients in comparison to healthy control. The level of these metabolites (except LPR) was altered in advanced-stage breast cancer patients in comparison to early-stage breast cancer patients. The altered metabolites were also associated with over 25 signaling pathways related to metabolism. Further, lncRNAs such as H19, MEG3 and GAS5 were dysregulated in the breast tumor tissue in comparison to normal adjacent tissue.

CONCLUSION

The study provides insights into metabolic alteration in breast cancer patients. It also provides an avenue to examine the association of lncRNAs with metabolic patterns in patients.

Urine 1H-NMR Metabolomics to Discriminate Neurocysticercosis Patients from Healthy Controls: An Exploratory Study

The diagnosis of neurocysticercosis (NCC) is principally based on neuroimaging (magnetic resonance imaging or computed tomography), instrumentation that is scarcely available in the rural regions where Taenia solium transmission, primarily occurs due to poor sanitation conditions. Immunological assays for antigen or antibody detection complement the neuroimaging approach. However, no field-applicable assays to diagnose viable NCC or to guide the referral of cases for neuroimaging or for appropriate management are available. We performed an exploratory study on urine and serum samples using 1H-nuclear magnetic resonance (NMR)-based metabolomics to discriminate NCC patients (n = 14) from healthy control subjects (n = 22). Metabolic profiles demonstrated a discrimination between the urines of NCC patients and noninfected control subjects with a moderate predictive accuracy (R2 = 0.999, Q2 = 0.434). NMR metabolomics analysis has been proven useful in depicting biomarkers linked to other infectious diseases, various types of cancer, and other disorders. Our results, albeit preliminary, open a door to the development of better methods for detecting NCC through the identification of biomarkers participating in disturbed metabolic pathways.

Guide to Metabolomics Analysis: A Bioinformatics Workflow

Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites corresponding to each biological phenotype, and then provide an analysis of the mechanisms involved. Although metabolomics is important to understand the involved biological phenomena, the approach's ability to obtain an exhaustive description of the processes is limited. Thus, an analysis-integrated metabolomics, transcriptomics, proteomics, and other omics approach is recommended. Such integration of different omics data requires specialized statistical and bioinformatics software. This review focuses on the steps involved in metabolomics research and summarizes several main tools for metabolomics analyses. We also outline the most abnormal metabolic pathways in several cancers and diseases, and discuss the importance of multi-omics integration algorithms. Overall, our goal is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.

NMR based CSF metabolomics in tuberculous meningitis: correlation with clinical and MRI findings

We report the potential role of ¹H Nuclear Magnetic Resonance (NMR) based metabolomics in tuberculous meningitis (TBM). We also correlate the significant metabolites with clinical-radiological parameters. Forty-three patients with TBM were included, and their severity of meningitis was graded as stages I to III, and patients with positive Mycobacterium tuberculosis or its nucleic acid was considered as definite TBM. ¹H NMR-based metabolomic study was performed on (CSF) samples, and the significant metabolites compared to healthy controls were identified. Outcome at three months was defined as death, poor and good based on the modified Rankin Scale. These metabolites were compared between definite and probable groups of TBM, and also correlated with MRI findings. About 11 metabolites were found to be significant for distinguishing TBM from the controls. In TBM, lactate, glutamate, alanine, arginine, 2-hydroxyisobutyrate, formate, and cis-aconitate were upregulated, and glucose, fructose, glutamine, and myo-inositol were downregulated compared to the controls. For differentiating TBM from the controls, the AUC of the ROC curve generated using these significant metabolites was 0.99, with a 95% confidence interval from 0.96 to 1, demonstrating that these metabolites were able to classify cases with good sensitivity and specificity. Lactate concentration in CSF correlated with hemoglobin, CSF glucose, and infarction. The outcome did not correlate with metabolomics parameters. NMR-based CSF metabolomics have a potential role in differentiating TBM from the controls.

Potential of nuclear magnetic resonance metabolomics in the study of prostate cancer

Nuclear magnetic resonance (NMR) metabolomics is a powerful analytical technique and a tool which has unique characteristics and capabilities for the evaluation of a number of biochemicals/metabolites of cancer and other disease processes that are present in biofluids (urine and blood) and tissues. The potential of NMR metabolomics in prostate cancer (PCa) has been explored by researchers and its usefulness has been documented. A large number of metabolites such as citrate, choline, and sarcosine were detected by NMR metabolomics from biofluids and tissues related to PCa and their levels were compared with controls and benign prostatic hyperplasia. The changes in the levels of these metabolites aid in the diagnosis and help to understand the dysregulated metabolic pathways in PCa. We review recent studies on in vitro and ex vivo NMR spectroscopy-based PCa metabolomics and its possible role as a diagnostic tool.

Nuclear Magnetic Resonance Spectroscopy for Quantitative Analysis: A Review for Its Application in the Chemical, Pharmaceutical and Medicinal Domains

Nuclear magnetic resonance (NMR) is a rapid and accurate analytical tool for qualification and quantification. The capacity of NMR of being quantitative can also justify the calibration of other analytical methods. In pharmaceutical domain, quantitative NMR (qNMR) can be applied in the identification and quantification of drug simultaneously. The early drug development stage requires a minimum sample for analysis. Thus, priority should be given to utilize this technique to attain results with least investment, rapid analysis time and minimum sample consumption. This technique is a significant phenomenon to identify impurities, drug substance, residual solvents of in-process control (IPC) samples and characterizing the formulations. From an analyst's perspective, qNMR proved to be a routine practice in pharmaceutical industry to qualify any drug product. The absolute and relative methods offer great help in quantifying the component of interest in the process control samples and finished products. This review highlights the evolution of NMR application in the pharmaceutical industry, where determining the purity of drug substance, drug product and establishing the identity of impurities and its level are the challenging aspects. NMR in medicinal field emerging as a numero uno for Covid-19 severity detection and its dire consequences, accelerated vaccine development and the mapping of SAR-COV-2 RNA and proteins via chemical shift assignments.

Novel Metabolic Signatures of Prostate Cancer Revealed by 1H-NMR Metabolomics of Urine

Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on 1H nuclear magnetic resonance (1H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG "Glycine, Serine, and Threonine metabolism" in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.

Precision Medicine Approach in Prostate Cancer

Prostate cancer is the most prevalent type of cancer and the second cause of death in men worldwide. Various diagnostic and treatment procedures are available for this type of malignancy, but High-grade or locally advanced prostate cancers showed the potential to develop to lethal phase that can be causing dead. Therefore, new approaches are needed to prolong patients' survival and to improve their quality of life. Precision medicine is a novel emerging field that plays an essential role in identifying new sub-classifications of diseases and in providing guidance in treatment that is based on individual multi-omics data. Multi-omics approaches include the use of genomics, transcriptomics, proteomics, metabolomics, epigenomics and phenomics data to unravel the complexity of a disease-associated biological network, to predict prognostic biomarkers, and to identify new targeted drugs for individual cancer patients. We review the impact of multi-omics data in the framework of systems biology in the era of precision medicine, emphasising the combination of molecular imaging modalities with highthroughput techniques and the new treatments that target metabolic pathways involved in prostate cancer.

Non-invasive biomarkers for monitoring the immunotherapeutic response to cancer

Immunotherapy is an efficient way to cure cancer by modulating the patient’s immune response. However, the immunotherapy response is heterogeneous and varies between individual patients and cancer subtypes, reinforcing the need for early benefit predictors. Evaluating the infiltration of immune cells in the tumor and changes in cell-intrinsic tumor characteristics provide potential response markers to treatment. However, this approach requires invasive sampling and may not be suitable for real-time monitoring of treatment response. The recent emergence of quantitative imaging biomarkers provides promising opportunities. In vivo imaging technologies that interrogate T cell responses, metabolic activities, and immune microenvironment could offer a powerful tool to monitor the cancer response to immunotherapy. Advances in imaging techniques to identify tumors' immunological characteristics can help stratify patients who are more likely to respond to immunotherapy. This review discusses the metabolic events that occur during T cell activation and differentiation, anti-cancer immunotherapy-induced T cell responses, focusing on non-invasive imaging techniques to monitor T cell metabolism in the search for novel biomarkers of response to cancer immunotherapy.

Treatment With Hydrolyzed Diet Supplemented With Prebiotics and Glycosaminoglycans Alters Lipid Metabolism in Canine Inflammatory Bowel Disease

Canine inflammatory bowel disease (IBD) is a chronic, immunologically mediated intestinal disorder, resulting from the complex interaction of genetic, environmental and immune factors. Hydrolyzed diets are used in dogs with food-responsive diarrhea (FRD) to reduce adverse responses to immunostimulatory proteins. Prebiotics (PRBs) and glycosaminoglycans (GAGs) have previously been demonstrated to show anti-inflammatory activity in the intestinal mucosa. Notably, hydrolyzed diets combined with the administration of PRBs and GAGs offer a promising approach for the treatment of canine IBD. Our aim was to investigate the effects of hydrolyzed diet and GAG+PRB co-treatment on the serum metabolomic profile of IBD dogs. Dogs with IBD randomly received either hydrolyzed diet supplemented with GAGs and PRBs (treatment 1) or hydrolyzed diet alone (treatment 2) for 10 weeks. A targeted metabolomics approach using mass spectrometry was performed to quantify changes in the serum metabolome before and after treatment and between treatment 1 and 2. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), hierarchical cluster analysis (HCA) and univariate statistics were used to identify differences between the treatment groups. PCA, PLS-DA, and HCA showed a clear clustering of IBD dogs before and after hydrolyzed diet, indicating that the treatment impacted the serum metabolome. Univariate analysis revealed that most of the altered metabolites were involved in lipid metabolism. The most impacted lipid classes were components of cell membranes, including glycerophospholipids, sphingolipids, and di- and triglycerides. In addition, changes in serum metabolites after GAG+PRB co-treatment suggested a possible additional beneficial effect on the lipid metabolism in IBD dogs. In conclusion, the present study showed a significant increase in metabolites that protect gut cell membrane integrity in response to hydrolyzed diet alone or in combination with GAG+PRB co-treatment. Administration of such treatment over 70 days improved selected serum biomarkers of canine IBD, possibly indicating improved intestinal membrane integrity.

Update on urine as a biomarker in cancer: a necessary review of an old story

Introduction: Cancer causes thousands of deaths worldwide each year. Therefore, monitoring of health status and the early diagnosis of cancer using noninvasive assays, such as the analysis of molecular biomarkers in urine, is essential. However, effective biomarkers for early diagnosis of cancer have not been established in many types of cancer.Areas covered: In this review, we discuss recent findings with regard to the use of urine composition as a biomarker in eleven types of cancer. We also highlight the use of urine biomarkers for improving early diagnosis.Expert opinion: Urinary biomarkers have been applied for clinical application of early diagnosis. The main limitation is a lack of integrated approaches for identification of new biomarkers in most cancer. The utilization of urinary biomarker detection will be promoted by improved detection methods and new data from different types of cancers. With the development of precision medicine, urinary biomarkers will play an increasingly important clinical role. Future early diagnosis would benefit from changes in the utilization of urinary biomarkers.

Nuclear magnetic resonance spectroscopy of human body fluids and in vivo magnetic resonance spectroscopy: Potential role in the diagnosis and management of prostate cancer

Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.

Molecular Characterization of Prostate Cancer with Associated Gleason Score Using Mass Spectrometry Imaging

Diagnosis of prostate cancer is based on histologic evaluation of tumor architecture using a system known as the "Gleason score." This diagnostic paradigm, while the standard of care, is time-consuming, shows intraobserver variability, and provides no information about the altered metabolic pathways, which result in altered tissue architecture. Characterization of the molecular composition of prostate cancer and how it changes with respect to the Gleason score (GS) could enable a more objective and faster diagnosis. It may also aid in our understanding of disease onset and progression. In this work, we present mass spectrometry imaging for identification and mapping of lipids and metabolites in prostate tissue from patients with known prostate cancer with GS from 6 to 9. A gradient of changes in the intensity of various lipids was observed, which correlated with increasing GS. Interestingly, these changes were identified in both regions of high tumor cell density, and in regions of tissue that appeared histologically benign, possibly suggestive of precancerous metabolomic changes. A total of 31 lipids, including several phosphatidylcholines, phosphatidic acids, phosphatidylserines, phosphatidylinositols, and cardiolipins were detected with higher intensity in GS (4+3) compared with GS (3+4), suggesting they may be markers of prostate cancer aggression. Results obtained through mass spectrometry imaging studies were subsequently correlated with a fast, ambient mass spectrometry method for potential use as a clinical tool to support image-guided prostate biopsy. IMPLICATIONS: In this study, we suggest that metabolomic differences between prostate cancers with different Gleason scores can be detected by mass spectrometry imaging.

Preoperative Metabolic Signatures of Prostate Cancer Recurrence Following Radical Prostatectomy

Technological advances in mass spectrometry (MS), liquid chromatography (LC) separations, nuclear magnetic resonance (NMR) spectroscopy, and big data analytics have made possible studying metabolism at an "omics" or systems level. Here, we applied a multiplatform (NMR + LC-MS) metabolomics approach to the study of preoperative metabolic alterations associated with prostate cancer recurrence. Thus far, predicting which patients will recur even after radical prostatectomy has not been possible. Correlation analysis on metabolite abundances detected on serum samples collected prior to surgery from prostate cancer patients ( n = 40 remission vs n = 40 recurrence) showed significant alterations in a number of pathways, including amino acid metabolism, purine and pyrimidine synthesis, tricarboxylic acid cycle, tryptophan catabolism, glucose, and lactate. Lipidomics experiments indicated higher lipid abundances on recurrent patients for a number of classes that included triglycerides, lysophosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, diglycerides, acyl carnitines, and ceramides. Machine learning approaches led to the selection of a 20-metabolite panel from a single preoperative blood sample that enabled prediction of recurrence with 92.6% accuracy, 94.4% sensitivity, and 91.9% specificity under cross-validation conditions.

NMR-based metabolomics studies of human prostate cancer tissue

INTRODUCTION

Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. Serum prostate-specific antigen (PSA) remains the most used biomarker in the detection and management of patients with PCa, in spite of the problems related with its low specificity, false positive rate and overdiagnosis. Furthermore, PSA is unable to discriminate indolent from aggressive PCa, which can lead to overtreatment. Early diagnosed and treated PCa can have a good prognosis and is potentially curable. Therefore, the discovery of new biomarkers able to detect clinically significant aggressive PCa is urgently needed.

METHODS

This revision was based on an electronic literature search, using Pubmed, with Nuclear Magnetic Resonance (NMR), tissue and prostate cancer as keywords. All metabolomic studies performed in PCa tissues by NMR spectroscopy, from 2007 until March 2018, were included in this review.

RESULTS

In the context of cancer, metabolomics allows the analysis of the entire metabolic profile of cancer cells. Several metabolic alterations occur in cancer cells to sustain their abnormal rates of proliferation. NMR proved to be a suitable methodology for the evaluation of these metabolic alterations in PCa tissues, allowing to unveil alterations in citrate, spermine, choline, choline-related compounds, lactate, alanine and glutamate.

CONCLUSION

The study of the metabolic alterations associated with PCa progression, accomplished by the analysis of PCa tissue by NMR, offers a promising approach for elucidating biochemical pathways affected by PCa and also for discovering new clinical biomarkers. The main metabolomic alterations associated with PCa development and promising biomarker metabolites for diagnosis of PCa were outlined.

Analysis of the Effects of δ-Tocopherol on RAW264.7 and K562 Cells Based on 1H NMR Metabonomics

δ-Tocopherol (δ-TOH) is a form of vitamin E with higher bioactivity. In this study, we studied the bioactivity of δ-TOH using the IC₅₀ of δ-TOH on RAW264.7 (80 μM) and K562 (110 μM) cells. We compared the differential metabolites from the cell lines with and without δ-TOH treatment by ¹H NMR metabonomics analysis. It was found that δ-TOH affected the protein biosynthesis, betaine metabolism, and urea cycle in various ways in both cell lines. Metabolic levels of the cell lines were changed after treatment with δ-TOH as differential metabolites were produced. The betaine level in RAW264.7 cells was reduced significantly, while the l-lactic acid level in K562 cells was significantly enhanced. The metabolic changes might contribute to the switch of the respiration pattern from aerobic respiration to anaerobic respiration in K562 cells. These results are helpful in further understanding the subtoxicity of δ-TOH.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

PURPOSE

The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.

APPROACH

A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.

FINDINGS

A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.

CONCLUSIONS

Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

Increased transcriptional and metabolic capacity for lipid metabolism in the peripheral zone of the prostate may underpin its increased susceptibility to cancer

The human prostate gland comprises three distinct anatomical glandular zones, namely the peripheral, central and transitional zones. Although prostate cancer can arise throughout the prostate, it is more frequent in the peripheral zone. In contrast, hyperplasia occurs most frequently in the transitional zone. In this paper, we test the hypothesis that peripheral and transitional zones have distinct metabolic adaptations that may underlie their different inherent predispositions to cancer and hyperplasia. In order to do this, we undertook RNA sequencing and high-throughput metabolic analyses of non-cancerous tissue from the peripheral and transitional zones of patients undergoing prostatectomy. Integrated analysis of RNAseq and metabolomic data revealed that transcription of genes involved in lipid biosynthesis is higher in the peripheral zone, which was mirrored by an increase in fatty acid metabolites, such as lysolipids. The peripheral zone also exhibited increased fatty acid catabolic activity and contained higher level of neurotransmitters. Such increased capacity for de novo lipogenesis and fatty acid oxidation, which is characteristic of prostate cancer, can potentially provide a permissive growth environment within the peripheral zone for cancer growth and also transmit a metabolic growth advantage to newly emerging clones themselves. This lipo-rich priming may explain the observed susceptibility of the peripheral zone to oncogenesis.

Nuclear Magnetic Resonance technique in tumor metabolism

Cancer is one of the most serious diseases that cause an enormous number of deaths all over the world. Tumor metabolism has great discrimination from that of normal tissues. Exploring the tumor metabolism may be one of the best ways to find biomarkers for cancer detection, diagnosis and to provide novel insights into internal physiological state where subtle changes may happen in metabolite concentrations. Nuclear Magnetic Resonance (NMR) technique nowadays is a popular tool to analyze cell extracts, tissues and biological fluids, etc, since it is a relatively fast and an accurate technique to supply abundant biochemical information at molecular levels for tumor research. In this review, approaches in tumor metabolism are discussed, including sample collection, data profiling and multivariate data analysis methods etc. Some typical applications of NMR are also summarized in tumor metabolism.

NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics

BACKGROUND

To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH.

METHODS

The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort.

RESULTS

DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH.

CONCLUSIONS

(1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc.

NMR-based metabolomics of prostate cancer: a protagonist in clinical diagnostics

Advances in the application of NMR spectroscopy-based metabolomic profiling of prostate cancer comprises a potential tactic for understanding the impaired biochemical pathways arising due to a disease evolvement and progression. This technique involves qualitative and quantitative estimation of plethora of small molecular weight metabolites of body fluids or tissues using state-of-the-art chemometric methods delivering an important platform for translational research from basic to clinical, to reveal the pathophysiological snapshot in a single step. This review summarizes the present arrays and recent advancements in NMR-based metabolomics and a glimpse of currently used medical imaging tactics, with their role in clinical diagnosis of prostate cancer.

Metabolomics connects aberrant bioenergetic, transmethylation, and gut microbiota in sarcoidosis

Sarcoidosis is a systemic granulomatous disease of unknown etiology. Granulomatous inflammation in sarcoidosis may affect multiple organs, including the lungs, skin, CNS, and the eyes, leading to severe morbidity and mortality. The underlying mechanisms for sustained inflammation in sarcoidosis are unknown. We hypothesized that metabolic changes play a critical role in perpetuation of inflammation in sarcoidosis. ¹H nuclear magnetic resonance (NMR)-based untargeted metabolomic analysis was used to identify circulating molecules in serum to discriminate sarcoidosis patients from healthy controls. Principal component analyses (PCA) were performed to identify different metabolic markers and explore the changes of associated biochemical pathways. Using Chenomx 7.6 NMR Suite software, we identified and quantified metabolites responsible for such separation in the PCA models. Quantitative analysis showed that the levels of metabolites, such as 3-hydroxybutyrate, acetoacetate, carnitine, cystine, homocysteine, pyruvate, and trimethylamine N-oxide were significantly increased in sarcoidosis patients. Interestingly, succinate, a major intermediate metabolite involved in the tricyclic acid cycle was significantly decreased in sarcoidosis patients. Application of integrative pathway analyses identified deregulation of butanoate, ketone bodies, citric cycle metabolisms, and transmethylation. This may be used for development of new drugs or nutritional modification.

Metabolomic profiling of hormone-dependent cancers: a bird's eye view

Hormone-dependent cancers present a significant public health challenge, because they are among the most common cancers in the world. One factor associated with cancer development and progression is metabolic reprogramming. By understanding these alterations, we can identify potential markers and novel biochemical therapeutic targets. Metabolic profiling is an advanced technology that allows investigators to assess low-molecular-weight compounds that reflect physiological alterations. Current research in metabolomics on prostate (PCa) and breast cancer (BCa) have made great strides in uncovering specific metabolic pathways that are associated with cancer development, progression, and resistance. In this review, we highlight some of the major findings and potential therapeutic advances that have been reported utilizing this technology.

NMR metabolomics of renal cancer: an overview

This paper reviews the use of NMR metabolomics for the metabolic characterization of renal cancer. The existing challenges in the clinical management of this disease are first presented, followed by a brief introduction to the metabolomics approach, in the context of cancer research. A subsequent review of the literature on NMR metabolic studies of renal cancer reveals that the subject has been clearly underdeveloped, compared with other types of cancer, particularly regarding cultured cells and tissue analysis. NMR analysis of biofluids has focused on blood (plasma or serum) metabolomics, comprising no account of studies on human urine, in spite of its noninvasiveness and physiological proximity to the affected organs. Finally, some areas of potential future development are identified.

Translational metabolomics in cancer research

Over the last decade there has been a bottleneck in the introduction of new validated cancer metabolic biomarkers into clinical practice. Unfortunately, there are no biomarkers with adequate sensitivity for the early detection of cancer, and there remain a reliance on cancer antigens for monitoring treatment. The need for new diagnostics has led to the exploration of untargeted metabolomics for discovery of early biomarkers of specific cancers and targeted metabolomics to elucidate mechanistic aspects of tumor progression. The successful translation of such strategies to the treatment of cancer would allow earlier intervention to improve survival. We have reviewed the methodology that is being used to achieve these goals together with recent advances in implementing translational metabolomics in cancer.

Laboratory evaluation and metabolomics in inflammatory bowel disease

Diagnosis and prognosis of inflammatory bowel disease (IBD) remain a challenge for physicians, and they are often based on history, clinical symptoms and endoscopic, histological, radiological and laboratory findings. Studies have shown that metabolomics may have important value in the diagnosis and prognosis of IBD. This paper will review the latest progress in laboratory evaluation and metabolomics in IBD.

Phorbol ester stimulates ethanolamine release from the metastatic basal prostate cancer cell line PC3 but not from prostate epithelial cell lines LNCaP and P4E6

Background:

Malignancy alters cellular complex lipid metabolism and membrane lipid composition and turnover. Here, we investigated whether tumorigenesis in cancer-derived prostate epithelial cell lines influences protein kinase C-linked turnover of ethanolamine phosphoglycerides (EtnPGs) and alters the pattern of ethanolamine (Etn) metabolites released to the medium.

Methods:

Prostate epithelial cell lines P4E6, LNCaP and PC3 were models of prostate cancer (PCa). PNT2C2 and PNT1A were models of benign prostate epithelia. Cellular EtnPGs were labelled with [1-³H]-Etn hydrochloride. PKC was activated with phorbol ester (TPA) and inhibited with Ro31-8220 and GF109203X. D609 was used to inhibit PLD (phospholipase D). [³H]-labelled Etn metabolites were resolved by ion-exchange chromatography. Sodium oleate and mastoparan were tested as activators of PLD2. Phospholipase D activity was measured by a transphosphatidylation reaction. Cells were treated with ionomycin to raise intracellular Ca²⁺ levels.

Results:

Unstimulated cell lines release mainly Etn and glycerylphosphorylEtn (GPEtn) to the medium. Phorbol ester treatment over 3h increased Etn metabolite release from the metastatic PC3 cell line and the benign cell lines PNT2C2 and PNT1A but not from the tumour-derived cell lines P4E6 and LNCaP; this effect was blocked by Ro31-8220 and GF109203X as well as by D609, which inhibited PLD in a transphosphatidylation reaction. Only metastatic PC3 cells specifically upregulated Etn release in response to TPA treatment. Oleate and mastoparan increased GPEtn release from all cell lines at the expense of Etn. Ionomycin stimulated GPEtn release from benign PNT2C2 cells but not from cancer-derived cell lines P4E6 or PC3. Ethanolamine did not stimulate the proliferation of LNCaP or PC3 cell lines but decreased the uptake of choline (Cho).

Conclusions:

Only the metastatic basal PC3 cell line specifically increased the release of Etn on TPA treatment most probably by PKC activation of PLD1 and increased turnover of EtnPGs. The phosphatidic acid formed will maintain a cancer phenotype through the regulation of mTOR. Ethanolamine released from cells may reduce Cho uptake, regulating the membrane PtdEtn:PtdCho ratio and influencing the action of PtdEtn-binding proteins such as RKIP and the anti-apoptotic hPEBP4. The work highlights a difference between LNCaP cells used as a model of androgen-dependent early stage PCa and androgen-independent PC3 cells used to model later refractory stage disease.

Serum and urine metabolomic fingerprinting in diagnostics of inflammatory bowel diseases

AIM: To evaluate the utility of serum and urine metabolomic analysis in diagnosing and monitoring of inflammatory bowel diseases (IBD).

METHODS: Serum and urine samples were collected from 24 patients with ulcerative colitis (UC), 19 patients with the Crohn’s disease (CD) and 17 healthy controls. The activity of UC was assessed with the Simple Clinical Colitis Activity Index, while the activity of CD was determined using the Harvey-Bradshaw Index. The analysis of serum and urine samples was performed using proton nuclear magnetic resonance (NMR) spectroscopy. All spectra were exported to Matlab for preprocessing which resulted in two data matrixes for serum and urine. Prior to the chemometric analysis, both data sets were unit variance scaled. The differences in metabolite fingerprints were assessed using partial least-squares-discriminant analysis (PLS-DA). Receiver operating characteristic curves and area under curves were used to evaluate the quality and prediction performance of the obtained PLS-DA models. Metabolites responsible for separation in models were tested using STATISTICA 10 with the Mann-Whitney-Wilcoxon test and the Student’s t test (α = 0.05).

RESULTS: The comparison between the group of patients with active IBD and the group with IBD in remission provided good PLS-DA models (P value 0.002 for serum and 0.003 for urine). The metabolites that allowed to distinguish these groups were: N-acetylated compounds and phenylalanine (up-regulated in serum), low-density lipoproteins and very low-density lipoproteins (decreased in serum) as well as glycine (increased in urine) and acetoacetate (decreased in urine). The significant differences in metabolomic profiles were also found between the group of patients with active IBD and healthy control subjects providing the PLS-DA models with a very good separation (P value < 0.001 for serum and 0.003 for urine). The metabolites that were found to be the strongest biomarkers included in this case: leucine, isoleucine, 3-hydroxybutyric acid, N-acetylated compounds, acetoacetate, glycine, phenylalanine and lactate (increased in serum), creatine, dimethyl sulfone, histidine, choline and its derivatives (decreased in serum), as well as citrate, hippurate, trigonelline, taurine, succinate and 2-hydroxyisobutyrate (decreased in urine). No clear separation in PLS-DA models was found between CD and UC patients based on the analysis of serum and urine samples, although one metabolite (formate) in univariate statistical analysis was significantly lower in serum of patients with active CD, and two metabolites (alanine and N-acetylated compounds) were significantly higher in serum of patients with CD when comparing jointly patients in the remission and active phase of the diseases. Contrary to the results obtained from the serum samples, the analysis of urine samples allowed to distinguish patients with IBD in remission from healthy control subjects. The metabolites of importance included in this case up-regulated acetoacetate and down-regulated citrate, hippurate, taurine, succinate, glycine, alanine and formate.

CONCLUSION: NMR-based metabolomic fingerprinting of serum and urine has the potential to be a useful tool in distinguishing patients with active IBD from those in remission.

High-resolution NMR spectroscopy of human body fluids and tissues in relation to prostate cancer

High-resolution NMR spectroscopic studies of prostate tissue extracts, prostatic fluid, seminal fluid, serum and urine can be used for the detection of prostate cancer, based on the differences in their metabolic profiles. Useful diagnostic information is obtained by the detection or quantification of as many metabolites as possible and comparison with normal samples. Only a few studies have shown the potential of high-resolution in vitro NMR of prostate tissues. A survey of the literature has revealed that studies on body fluids, such as urine and serum, in relation to prostate cancer are rare. In addition, the potential of NMR of nuclei other than (1)H, such as (13)C and (31)P, has not been exploited fully. The metabolomic analysis of metabolites, detected by high-resolution NMR, may help to identify metabolites which could serve as useful biomarkers for prostate cancer detection. Such NMR-derived biomarkers would not only help in prostate cancer detection and in understanding the in vivo MRS metabolic profile, but also to investigate the biochemical and metabolic changes associated with cancer. Here, we review the published research work on body fluids in relation to prostate and prostate tissue extracts, and highlight the potential of such studies for future work.

Follicular adenomas exhibit a unique metabolic profile. ¹H NMR studies of thyroid lesions

Thyroid cancer is the most common endocrine malignancy. However, more than 90% of thyroid nodules are benign. It remains unclear whether thyroid carcinoma arises from preexisting benign nodules. Metabolomics can provide valuable and comprehensive information about low molecular weight compounds present in living systems and further our understanding of the biology regulating pathological processes. Herein, we applied ¹H NMR-based metabolic profiling to identify the metabolites present in aqueous tissue extracts of healthy thyroid tissue (H), non-neoplastic nodules (NN), follicular adenomas (FA) and malignant thyroid cancer (TC) as an alternative way of investigating cancer lesions. Multivariate statistical methods provided clear discrimination not only between healthy thyroid tissue and pathological thyroid tissue but also between different types of thyroid lesions. Potential biomarkers common to all thyroid lesions were identified, namely, alanine, methionine, acetone, glutamate, glycine, lactate, tyrosine, phenylalanine and hypoxanthine. Metabolic changes in thyroid cancer were mainly related to osmotic regulators (taurine and scyllo- and myo-inositol), citrate, and amino acids supplying the TCA cycle. Thyroid follicular adenomas were found to display metabolic features of benign non-neoplastic nodules and simultaneously displayed a partial metabolic profile associated with malignancy. This finding allows the discrimination of follicular adenomas from benign non-neoplastic nodules and thyroid cancer with similar accuracy. Moreover, the presented data indicate that follicular adenoma could be an individual stage of thyroid cancer development.

Chemistry and biochemistry of 13C hyperpolarized magnetic resonance using dynamic nuclear polarization

The study of transient chemical phenomena by conventional NMR has proved elusive, particularly for non-(1)H nuclei. For (13)C, hyperpolarization using the dynamic nuclear polarization (DNP) technique has emerged as a powerful means to improve SNR. The recent development of rapid dissolution DNP methods has facilitated previously impossible in vitro and in vivo study of small molecules. This review presents the basics of the DNP technique, identification of appropriate DNP substrates, and approaches to increase hyperpolarized signal lifetimes. Also addressed are the biochemical events to which DNP-NMR has been applied, with descriptions of several probes that have met with in vivo success.

Biomarker Discovery and Translation in Metabolomics

The multifaceted field of metabolomics has witnessed exponential growth in both methods development and applications. Owing to the urgent need, a significant fraction of research investigations in the field is focused on understanding, diagnosing and preventing human diseases; hence, the field of biomedicine has been the major beneficiary of metabolomics research. A large body of literature now documents the discovery of numerous potential biomarkers and provides greater insights into pathogeneses of numerous human diseases. A sizable number of findings have been tested for translational applications focusing on disease diagnostics ranging from early detection, to therapy prediction and prognosis, monitoring treatment and recurrence detection, as well as the important area of therapeutic target discovery. Current advances in analytical technologies promise quantitation of biomarkers from even small amounts of bio-specimens using non-invasive or minimally invasive approaches, and facilitate high-throughput analysis required for real time applications in clinical settings. Nevertheless, a number of challenges exist that have thus far delayed the translation of a majority of promising biomarker discoveries to the clinic. This article presents advances in the field of metabolomics with emphasis on biomarker discovery and translational efforts, highlighting the current status, challenges and future directions.

Sarcosine as a potential prostate cancer biomarker--a review

Prostate cancer (CaP) is the most common type of tumour disease in men. Early diagnosis of cancer of the prostate is very important, because the sooner the cancer is detected, the better it is treated. According to that fact, there is great interest in the finding of new markers including amino acids, proteins or nucleic acids. Prostate specific antigen (PSA) is commonly used and is the most important biomarker of CaP. This marker can only be detected in blood and its sensitivity is approximately 80%. Moreover, early stages cannot be diagnosed using this protein. Currently, there does not exist a test for diagnosis of early stages of prostate cancer. This fact motivates us to find markers sensitive to the early stages of CaP, which are easily detected in body fluids including urine. A potential is therefore attributed to the non-protein amino acid sarcosine, which is generated by glycine-N-methyltransferase in its biochemical cycle. In this review, we summarize analytical methods for quantification of sarcosine as a CaP marker. Moreover, pathways of the connection of synthesis of sarcosine and CaP development are discussed.

Metabolomics in food science

Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science.

Application of metabolomics to prostate cancer

The prostate has long been known to exhibit unique metabolite profiles. In the last decade, advances in nuclear magnetic resonance spectroscopy and mass spectrometry have been applied toward identifying metabolic alterations in prostate cancer that may provide clinically useful biomarkers. As with genomics and proteomics, advances in technology and bioinformatics have led to the application of metabolomic profiling to prostate cancer-the high throughput evaluation of a large complement of metabolites in the prostate and how they are altered by disease perturbations. Recently, high profile publications have drawn attention to the potential of metabolomic analysis to identify biomarkers for early detection or disease progression from readily accessible body fluids as well as tissue specimens from biopsy and surgery. This review will examine applications of metabolomics to prostate cancer and highlight clinical associations and potential challenges.

The changing therapeutic landscape of castration-resistant prostate cancer

Castration-resistant prostate cancer (CRPC) has a poor prognosis and remains a significant therapeutic challenge. Before 2010, only docetaxel-based chemotherapy improved survival in patients with CRPC compared with mitoxantrone. Our improved understanding of the underlying biology of CRPC has heralded a new era in molecular anticancer drug development, with a myriad of novel anticancer drugs for CRPC entering the clinic. These include the novel taxane cabazitaxel, the vaccine sipuleucel-T, the CYP17 inhibitor abiraterone, the novel androgen-receptor antagonist MDV-3100 and the radioisotope alpharadin. With these developments, the management of patients with CRPC is changing. In this Review, we discuss these promising therapies along with other novel agents that are demonstrating early signs of activity in CRPC. We propose a treatment pathway for patients with CRPC and consider strategies to optimize the use of these agents, including the incorporation of predictive and intermediate end point biomarkers, such as circulating tumor cells.