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

Peak Resembling N-acetylaspartate (NAA) on Magnetic Resonance Spectroscopy of Brain Metastases

Background and Objectives: Differentiating between a high-grade glioma (HGG) and solitary cerebral metastasis presents a challenge when using standard magnetic resonance imaging (MRI) alone. Magnetic resonance spectroscopy (MRS), an advanced MRI technique, may assist in resolving this diagnostic dilemma. N-acetylaspartate (NAA), an amino acid found uniquely in the central nervous system and in high concentrations in neurons, typically suggests HGG over metastatic lesions in spectra from ring-enhancing lesions. This study investigates exceptions to this norm. Materials and Methods: We conducted an MRS study on 49 histologically confirmed and previously untreated patients with brain metastases, employing single-voxel (SVS) techniques with short and long echo times, as well as magnetic resonance spectroscopic imaging (MRSI). Results: In our cohort, 44 out of 49 (90%) patients demonstrated a typical MR spectroscopic profile consistent with secondary deposits: a Cho peak, very low or absent Cr, absence of NAA, and the presence of lipids. A peak at approximately 2 ppm, termed the "NAA-like peak", was present in spectra obtained with both short and long echo times. Among the MRS data from 49 individuals, we observed a peak at 2.0 ppm in five brain metastases from mucinous carcinoma of the breast, mucinous non-small-cell lung adenocarcinoma, two metastatic melanomas, and one metastatic non-small-cell lung cancer. Pathohistological verification of mucin in two of these five cases suggested this peak likely represents N-acetyl glycoproteins, indicative of mucin expression in cancer cells. Conclusions: The identification of a prominent peak at 2.0 ppm could be a valuable diagnostic marker for distinguishing single ring-enhancing lesions, potentially associated with mucin-expressing metastases, offering a new avenue for diagnostic specificity in challenging cases.

Metabolomic profiles of intact tissues reflect clinically relevant prostate cancer subtypes

BACKGROUND

Prostate cancer (PC) is a heterogenous multifocal disease ranging from indolent to lethal states. For improved treatment-stratification, reliable approaches are needed to faithfully differentiate between high- and low-risk tumors and to predict therapy response at diagnosis.

METHODS

A metabolomic approach based on high resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) analysis was applied on intact biopsies samples (n = 111) obtained from patients (n = 31) treated by prostatectomy, and combined with advanced multi- and univariate statistical analysis methods to identify metabolomic profiles reflecting tumor differentiation (Gleason scores and the International Society of Urological Pathology (ISUP) grade) and subtypes based on tumor immunoreactivity for Ki67 (cell proliferation) and prostate specific antigen (PSA, marker for androgen receptor activity).

RESULTS

Validated metabolic profiles were obtained that clearly distinguished cancer tissues from benign prostate tissues. Subsequently, metabolic signatures were identified that further divided cancer tissues into two clinically relevant groups, namely ISUP Grade 2 (n = 29) and ISUP Grade 3 (n = 17) tumors. Furthermore, metabolic profiles associated with different tumor subtypes were identified. Tumors with low Ki67 and high PSA (subtype A, n = 21) displayed metabolite patterns significantly different from tumors with high Ki67 and low PSA (subtype B, n = 28). In total, seven metabolites; choline, peak for combined phosphocholine/glycerophosphocholine metabolites (PC + GPC), glycine, creatine, combined signal of glutamate/glutamine (Glx), taurine and lactate, showed significant alterations between PC subtypes A and B.

CONCLUSIONS

The metabolic profiles of intact biopsies obtained by our non-invasive HR MAS NMR approach together with advanced chemometric tools reliably identified PC and specifically differentiated highly aggressive tumors from less aggressive ones. Thus, this approach has proven the potential of exploiting cancer-specific metabolites in clinical settings for obtaining personalized treatment strategies in PC.

Evaluation of prostate cancer tissue metabolomics: would clinics utilise it for diagnosis?

The difficulty of diagnosing prostate cancer (PC) with the available biomarkers frequently leads to over-diagnosis and overtreatment of PC, underscoring the need for novel molecular signatures. The purpose of this review is to provide a summary of the currently available cellular metabolomics for PC molecular signatures. A comprehensive search on PubMed was conducted to find studies published between January 2004 and August 2022 that reported biomarkers for PC detection, development, aggressiveness, recurrence and treatment response. Although potential studies have reported the presence of distinguishing molecules that can distinguish between benign and cancerous prostate tissue. However, there are few studies looking into signature molecules linked to disease development, therapy response or tumour recurrence. The majority of these studies use high-dimensional datasets, and the number of potential metabolites investigated frequently exceeds the size of the available samples. In light of this, pre-analytical, statistical, methodological and confounding factors such as antiandrogen therapy (NAT) may also be linked to the identified chemometric multivariate differences between PC and relevant control samples in the datasets. Despite the methodological and procedural challenges, a range of methodological groups and processes have consistently identified a number of signature metabolites and pathways that appear to imply a substantial involvement in the cellular metabolomics of PC for tumour formation and recurrence.

Alteration of Lipid Metabolism in Prostate Cancer: Multifaceted Oncologic Implications

Cancer is increasingly recognized as an extraordinarily heterogeneous disease featuring an intricate mutational landscape and vast intra- and intertumor variability on both genetic and phenotypic levels. Prostate cancer (PCa) is the second most prevalent malignant disease among men worldwide. A single metabolic program cannot epitomize the perplexing reprogramming of tumor metabolism needed to sustain the stemness of neoplastic cells and their prominent energy-consuming functional properties, such as intensive proliferation, uncontrolled growth, migration, and invasion. In cancerous tissue, lipids provide the structural integrity of biological membranes, supply energy, influence the regulation of redox homeostasis, contribute to plasticity, angiogenesis and microenvironment reshaping, mediate the modulation of the inflammatory response, and operate as signaling messengers, i.e., lipid mediators affecting myriad processes relevant for the development of the neoplasia. Comprehensive elucidation of the lipid metabolism alterations in PCa, the underlying regulatory mechanisms, and their implications in tumorigenesis and the progression of the disease are gaining growing research interest in the contemporary urologic oncology. Delineation of the unique metabolic signature of the PCa featuring major aberrant pathways including de novo lipogenesis, lipid uptake, storage and compositional reprogramming may provide novel, exciting, and promising avenues for improving diagnosis, risk stratification, and clinical management of such a complex and heterogeneous pathology.

High resolution magic angle spinning MRS in prostate cancer

INTRODUCTION

Prostate cancer (PCa) is one of the leading causes of death among men worldwide. The current methods utilized to screen for prostate cancer may not have sufficient sensitivity in distinguishing aggressive from indolent diseases, which affect the quality of life of patients in the short and long term. The overdiagnosis of cases and overtreatment are prevalent due to the heterogeneity of the disease in terms of latent and progressive variants, as well as in the tissue types present in biopsy samples.

METHODS

The purpose of this review is to discuss the potential clinical benefits of incorporating high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) modalities to overcome the current challenges in the diagnosis, prognostication, and monitoring of PCa.

Methodological Developments for Metabolic NMR Spectroscopy from Cultured Cells to Tissue Extracts: Achievements, Progress and Pitfalls

This is a broad overview and critical review of a particular group of closely related ex vivo and in vitro metabolic NMR spectroscopic methods. The scope of interest comprises studies of cultured cells and excised tissue, either intact or after physicochemical extraction of metabolites. Our detailed discussion includes pitfalls that have led to erroneous statements in the published literature, some of which may cause serious problems in metabolic and biological interpretation of results. To cover a wide range of work from relevant research areas, we consider not only the most recent achievements in the field, but also techniques that proved to be valid and successful in the past, although they may not have generated a very significant number of papers more recently. Thus, this comparative review also aims at providing background information useful for judiciously choosing between the metabolic ex vivo/in vitro NMR methods presented. Finally, the methods of interest are discussed in the context of, and in relation to, other metabolic analysis protocols such as HR-MAS and cell perfusion NMR, as well as the mass spectrometry approach.

Discrimination and Quantitation of Biologically Relevant Carboxylate Anions Using A [Dye•PAMAM] Complex

Carboxylate anions are analytical targets with environmental and biological relevance, whose detection is often challenging in aqueous solutions. We describe a method for discrimination and quantitation of carboxylates in water buffered to pH 7.4 based on their differential interaction with a supramolecular fluorescent sensor, self-assembled from readily available building blocks. A fifth-generation poly(amidoamine) dendrimer (PAMAM G5), bound to organic fluorophores (calcein or pyranine) through noncovalent interactions, forms a [dye•PAMAM] complex responsive to interaction with carboxylates. The observed changes in absorbance, and in fluorescence emission and anisotropy, were interpreted through linear discriminant analysis (LDA) and principal component analysis (PCA) to differentiate 10 structurally similar carboxylates with a limit of discrimination around 100 μM. The relationship between the analytes’ chemical structures and the system’s response was also elucidated. This insight allowed us to extend the system’s capabilities to the simultaneous identification of the nature and concentration of unknown analytes, with excellent structural identification results and good concentration recovery, an uncommon feat for a pattern-based sensing system.

The Emerging Clinical Role of Spermine in Prostate Cancer

Spermine, a member of polyamines, exists in all organisms and is essential for normal cell growth and function. It is highly expressed in the prostate compared with other organs and is detectable in urine, tissue, expressed prostatic secretions, and erythrocyte. A significant reduction of spermine level was observed in prostate cancer (PCa) tissue compared with benign prostate tissue, and the level of urinary spermine was also significantly lower in men with PCa. Decreased spermine level may be used as an indicator of malignant phenotype transformation from normal to malignant tissue in prostate. Studies targeting polyamines and key rate-limiting enzymes associated with spermine metabolism as a tool for PCa therapy and chemoprevention have been conducted with various polyamine biosynthesis inhibitors and polyamine analogues. The mechanism between spermine and PCa development are possibly related to the regulation of polyamine metabolism, cancer-driving pathways, oxidative stress, anticancer immunosurveillance, and apoptosis regulation. Although the specific mechanism of spermine in PCa development is still unclear, ongoing research in spermine metabolism and its association with PCa pathophysiology opens up new opportunities in the diagnostic and therapeutic roles of spermine in PCa management.

Spatial differentiation of metabolism in prostate cancer tissue by MALDI-TOF MSI

Background

Prostate cancer tissues are inherently heterogeneous, which presents a challenge for metabolic profiling using traditional bulk analysis methods that produce an averaged profile. The aim of this study was therefore to spatially detect metabolites and lipids on prostate tissue sections by using mass spectrometry imaging (MSI), a method that facilitates molecular imaging of heterogeneous tissue sections, which can subsequently be related to the histology of the same section.

Methods

Here, we simultaneously obtained metabolic and lipidomic profiles in different prostate tissue types using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MSI. Both positive and negative ion mode were applied to analyze consecutive sections from 45 fresh-frozen human prostate tissue samples (N = 15 patients). Mass identification was performed with tandem MS.

Results

Pairwise comparisons of cancer, non-cancer epithelium, and stroma revealed several metabolic differences between the tissue types. We detected increased levels of metabolites crucial for lipid metabolism in cancer, including metabolites involved in the carnitine shuttle, which facilitates fatty acid oxidation, and building blocks needed for lipid synthesis. Metabolites associated with healthy prostate functions, including citrate, aspartate, zinc, and spermine had lower levels in cancer compared to non-cancer epithelium. Profiling of stroma revealed higher levels of important energy metabolites, such as ADP, ATP, and glucose, and higher levels of the antioxidant taurine compared to cancer and non-cancer epithelium.

Conclusions

This study shows that specific tissue compartments within prostate cancer samples have distinct metabolic profiles and pinpoint the advantage of methodology providing spatial information compared to bulk analysis. We identified several differential metabolites and lipids that have potential to be developed further as diagnostic and prognostic biomarkers for prostate cancer. Spatial and rapid detection of cancer-related analytes showcases MALDI-TOF MSI as a promising and innovative diagnostic tool for the clinic.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00242-z.

Metabolism of prostate cancer by magnetic resonance spectroscopy (MRS)

Understanding the metabolism of prostate cancer (PCa) is important for developing better diagnostic approaches and also for exploring new therapeutic targets. Magnetic resonance spectroscopy (MRS) techniques have been shown to be useful in the detection and quantification of metabolites. PCa illustrates metabolic phenotype, showing lower levels of citrate (Cit), a key metabolite of oxidative phosphorylation and alteration in several metabolic pathways to sustain tumor growth. Recently, dynamic nuclear polarization (DNP) studies have documented high rates of glycolysis (Warburg phenomenon) in PCa. High-throughput metabolic profiling strategies using MRS on variety of samples including intact tissues, biofluids like prostatic fluid, seminal fluid, blood plasma/sera, and urine have also played a vital role in understanding the abnormal metabolic activity of PCa patients. The enhanced analytical potential of these techniques in the detection and quantification of a large number of metabolites provides an in-depth understanding of metabolic rewiring associated with the tumorigenesis. Metabolomics analysis offers dual advantages of identification of diagnostic and predictive biomarkers as well as in understanding the altered metabolic pathways which can be targeted for inhibiting the cancer progression. This review briefly describes the potential applications of in vivo ¹H MRS, high-resolution magic angle spinning spectroscopy (HRMAS) and in vitro MRS methods in understanding the metabolic changes of PCa and its usefulness in the management of PCa patients.

Simultaneous Detection of Zinc and Its Pathway Metabolites Using MALDI MS Imaging of Prostate Tissue

Levels of zinc, along with its mechanistically related metabolites citrate and aspartate, are widely reported as reduced in prostate cancer compared to healthy tissue and are therefore pointed out as potential cancer biomarkers. Previously, it has only been possible to analyze zinc and metabolites by separate detection methods. Through matrix-assisted laser desorption/ionization mass spectrometry imaging (MSI), we were for the first time able to demonstrate, in two different sample sets (n = 45 and n = 4), the simultaneous spatial detection of zinc, in the form of ZnCl₃^–, together with citrate, aspartate, and N-acetylaspartate on human prostate cancer tissues. The reliability of the ZnCl₃^– detection was validated by total zinc determination using laser ablation inductively coupled plasma MSI on adjacent serial tissue sections. Zinc, citrate, and aspartate were correlated with each other (range r = 0.46 to 0.74) and showed a significant reduction in cancer compared to non-cancer epithelium (p < 0.05, log₂ fold change range: −0.423 to −0.987), while no significant difference between cancer and stroma tissue was found. Simultaneous spatial detection of zinc and its metabolites is not only a valuable tool for analyzing the role of zinc in prostate metabolism but might also provide a fast and simple method to detect zinc, citrate, and aspartate levels as a biomarker signature for prostate cancer diagnostics and prognostics.

Disposable paper strips for carboxylate discrimination

A fluorescent macromolecular chemosensor, built from readily available components, performs chemical fingerprinting of carboxylate anions on low-cost, disposable paper supports.

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

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

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Prostate cancer (PCa) diagnosis with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment, highlighting the need for novel biomarkers. The aim of this review is to provide a summary of available metabolomics PCa biomarkers, particularly for clinically significant disease. A systematic search was conducted on PubMed for publications from July 2008 to July 2018 in accordance with PRISMA guidelines to report biomarkers with respect to their application in PCa diagnosis, progression, aggressiveness, recurrence, and treatment response. The vast majority of studies report biomarkers with the ability to distinguish malignant from benign prostate tissue with a few studies investigating biomarkers associated with disease progression, treatment response or tumour recurrence. In general, these studies report high dimensional datasets and the number of analysed metabolites often significantly exceeded the number of available samples. Hence, observed multivariate differences between case and control samples in the datasets might potentially also be associated with pre-analytical, technical, statistical and confounding factors. Giving the technical and methodological hurdles, there are nevertheless a number of metabolites and pathways repeatedly reported across various technical approaches, cohorts and sample types that appear to play a predominant role in PCa tumour biology, progression and recurrence.

Characterization of Brain Metabolism by Nuclear Magnetic Resonance

The noninvasive, quantitative ability of nuclear magnetic resonance (NMR) spectroscopy to characterize small molecule metabolites has long been recognized as a major strength of its application in biology. Numerous techniques exist for characterizing metabolism in living, excised, or extracted tissue, with a particular focus on 1 H-based methods due to the high sensitivity and natural abundance of protons. With the increasing use of high magnetic fields, the utility of in vivo 1 H magnetic resonance spectroscopy (MRS) has markedly improved for measuring specific metabolite concentrations in biological tissues. Higher fields, coupled with recent developments in hyperpolarization, also enable techniques for complimenting 1 H measurements with spectroscopy of other nuclei, such as 31 P and 13 C, and for combining measurements of metabolite pools with metabolic flux measurements. We compare ex vivo and in vivo methods for studying metabolism in the brain using NMR and highlight insights gained through using higher magnetic fields, the advent of dissolution dynamic nuclear polarization, and combining in vivo MRS and ex vivo NMR approaches.

Simultaneous 18F-fluciclovine Positron Emission Tomography and Magnetic Resonance Spectroscopic Imaging of Prostate Cancer

Purpose: To investigate the associations of metabolite levels derived from magnetic resonance spectroscopic imaging (MRSI) and ¹⁸F-fluciclovine positron emission tomography (PET) with prostate tissue characteristics.

Methods: In a cohort of 19 high-risk prostate cancer patients that underwent simultaneous PET/MRI, we evaluated the diagnostic performance of MRSI and PET for discrimination of aggressive cancer lesions from healthy tissue and benign lesions. Data analysis comprised calculations of correlations of mean standardized uptake values (SUV_mean), maximum SUV (SUV_max), and the MRSI-derived ratio of (total choline + spermine + creatine) to citrate (CSC/C). Whole-mount histopathology was used as gold standard.

Results: The results showed a moderate significant correlation between both SUVmean and SUVmax with CSC/C ratio.

Conclusions: We demonstrated that the simultaneous acquisition of ¹⁸F-fluciclovine PET and MRSI with an integrated PET/MRI system is feasible and a combination of these imaging modalities has potential to improve the diagnostic sensitivity and specificity of prostate cancer lesions.

Clinical applications of in vivo magnetic resonance spectroscopy in oncology

Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.

Metabolomic Prediction of Human Prostate Cancer Aggressiveness: Magnetic Resonance Spectroscopy of Histologically Benign Tissue

Prostate cancer alters cellular metabolism through events potentially preceding cancer morphological formation. Magnetic resonance spectroscopy (MRS)-based metabolomics of histologically-benign tissues from cancerous prostates can predict disease aggressiveness, offering clinically-translatable prognostic information. This retrospective study of 185 patients (2002-2009) included prostate tissues from prostatectomies (n = 365), benign prostatic hyperplasia (BPH) (n = 15), and biopsy cores from cancer-negative patients (n = 14). Tissues were measured with high resolution magic angle spinning (HRMAS) MRS, followed by quantitative histology using the Prognostic Grade Group (PGG) system. Metabolic profiles, measured solely from 338 of 365 histologically-benign tissues from cancerous prostates and divided into training-testing cohorts, could identify tumor grade and stage, and predict recurrence. Specifically, metabolic profiles: (1) show elevated myo-inositol, an endogenous tumor suppressor and potential mechanistic therapy target, in patients with highly-aggressive cancer, (2) identify a patient sub-group with less aggressive prostate cancer to avoid overtreatment if analysed at biopsy; and (3) subdivide the clinicopathologically indivisible PGG2 group into two distinct Kaplan-Meier recurrence groups, thereby identifying patients more at-risk for recurrence. Such findings, achievable by biopsy or prostatectomy tissue measurement, could inform treatment strategies. Metabolomics information can help transform a morphology-based diagnostic system by invoking cancer biology to improve evaluation of histologically-benign tissues in cancer environments.

A novel non-canonical Wnt signature for prostate cancer aggressiveness

Activation of the Canonical Wnt pathway (CWP) has been linked to advanced and metastatic prostate cancer, whereas the Wnt5a-induced non-canonical Wnt pathway (NCWP) has been associated with both good and poor prognosis. A newly discovered NCWP, Wnt5/Fzd2, has been shown to induce epithelial-to-mesenchymal transition (EMT) in cancers, but has not been investigated in prostate cancer. The aim of this study was to investigate if the CWP and NCWP, in combination with EMT, are associated with metabolic alterations, aggressive disease and biochemical recurrence in prostate cancer. An initial analysis was performed using integrated transcriptomics, ex vivo and in vivo metabolomics, and histopathology of prostatectomy samples (n=129), combined with at least five-year follow-up. This analysis detected increased activation of NCWP through Wnt5a/ Fzd2 as the most common mode of Wnt activation in prostate cancer. This activation was associated with increased expression of EMT markers and higher Gleason score. The transcriptional association between NCWP and EMT was confirmed in five other publicly available patient cohorts (1519 samples in total). A novel gene expression signature of concordant activation of NCWP and EMT (NCWP-EMT) was developed, and this signature was significantly associated with metastasis and shown to be a significant predictor of biochemical recurrence. The NCWP-EMT signature was also associated with decreased concentrations of the metabolites citrate and spermine, which have previously been linked to aggressive prostate cancer. Our results demonstrate the importance of NCWP and EMT in prostate cancer aggressiveness, suggest a novel gene signature for improved risk stratification, and give new molecular insight.

Presence of TMPRSS2-ERG is associated with alterations of the metabolic profile in human prostate cancer

TMPRSS2-ERG has been proposed to be a prognostic marker for prostate cancer. The aim of this study was to identify changes in metabolism, genes and biochemical recurrence related to TMPRSS2-ERG by using an integrated approach, combining metabolomics, transcriptomics, histopathology and clinical data in a cohort of 129 human prostate samples (41 patients). Metabolic analyses revealed lower concentrations of citrate and spermine comparing ERG_high to ERG_low samples, suggesting an increased cancer aggressiveness of ERG_high compared to ERG_low. These results could be validated in a separate cohort, consisting of 40 samples (40 patients), and magnetic resonance spectroscopy imaging (MRSI) indicated an in vivo translational potential. Alterations of gene expression levels associated with key enzymes in the metabolism of citrate and polyamines were in consistence with the metabolic results. Furthermore, the metabolic alterations between ERG_high and ERG_low were more pronounced in low Gleason samples than in high Gleason samples, suggesting it as a potential tool for risk stratification. However, no significant difference in biochemical recurrence was detected, although a trend towards significance was detected for low Gleason samples. Using an integrated approach, this study suggests TMPRSS2-ERG as a potential risk stratification tool for inclusion of active surveillance patients.

Applications of high-resolution magic angle spinning MRS in biomedical studies II-Human diseases

High-resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high-resolution spectra of non-liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non-localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.

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

Background:

Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy.

Methods:

We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan–Meier survival analyses and concordance index (C-index).

Results:

High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively).

Conclusions:

Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.

Metabolic Imaging in Humans

Metabolic imaging enhances understanding of disease metabolisms and holds great potential as a measurement tool for evaluating disease prognosis and treatment effectiveness. Advancement of techniques, such as magnetic resonance spectroscopy, positron emission tomography, and mass spectrometry, allows for improved accuracy for quantification of metabolites and present unique possibilities for use in clinic. This article reviews and discusses literature reports of metabolic imaging in humans published since 2010 according to disease type, including cancer, degenerative disorders, psychiatric disorders, and others, as well as the current application of the various related techniques.

Response of Degarelix treatment in human prostate cancer monitored by HR-MAS 1H NMR spectroscopy

INTRODUCTION

The androgen receptor (AR) is the master regulator of prostate cancer cell metabolism. Degarelix is a novel gonadotrophin-releasing hormone blocker, used to decrease serum androgen levels in order to treat advanced human prostate cancer. Little is known of the rapid metabolic response of the human prostate cancer tissue samples to the decreased androgen levels.

OBJECTIVES

To investigate the metabolic responses in benign and cancerous tissue samples from patients after treatment with Degarelix by using HRMAS 1H NMR spectroscopy.

METHODS

Using non-destructive HR-MAS 1H NMR spectroscopy we analysed the metabolic changes induced by decreased AR signalling in human prostate cancer tissue samples. Absolute concentrations of the metabolites alanine, lactate, glutamine, glutamate, citrate, choline compounds [t-choline = choline + phosphocholine (PC) + glycerophosphocholine (GPC)], creatine compounds [t-creatine = creatine (Cr) + phosphocreatine (PCr)], taurine, myo-inositol and polyamines were measured in benign prostate tissue samples (n = 10), in prostate cancer specimens from untreated patients (n = 7) and prostate cancer specimens from patients treated with Degarelix (n = 6).

RESULTS

Lactate, alanine and t-choline concentrations were significantly elevated in high-grade prostate cancer samples when compared to benign samples in untreated patients. Decreased androgen levels resulted in significant decreases of lactate and t-choline concentrations in human prostate cancer biopsies.

CONCLUSIONS

The reduced concentrations of lactate and t-choline metabolites due to Degarelix could in principle be monitored by in vivo 1H MRS, which suggests that it would be possible to monitor the effects of physical or chemical castration in patients by that non-invasive method.

Tissue Microstructure Is Linked to MRI Parameters and Metabolite Levels in Prostate Cancer

INTRODUCTION

Magnetic resonance imaging (MRI) can portray spatial variations in tumor heterogeneity, architecture, and its microenvironment in a non-destructive way. The objective of this study was to assess the relationship between MRI parameters measured on patients in vivo, individual metabolites measured in prostatectomy tissue ex vivo, and quantitative histopathology.

MATERIALS AND METHODS

Fresh frozen tissue samples (n = 53 from 15 patients) were extracted from transversal prostate slices and linked to in vivo MR images, allowing spatially matching of ex vivo measured metabolites with in vivo MR parameters. Color-based segmentation of cryosections of each tissue sample was used to identify luminal space, stroma, and nuclei.

RESULTS

Cancer samples have significantly lower area percentage of lumen and higher area percentage of nuclei than non-cancer samples (p ≤ 0.001). Apparent diffusion coefficient is significantly correlated with percentage area of lumen (ρ = 0.6, p < 0.001) and percentage area of nuclei (ρ = -0.35, p = 0.01). There is a positive correlation (ρ = 0.31, p = 0.053) between citrate and percentage area of lumen. Choline is negatively correlated with lumen (ρ = -0.38, p = 0.02) and positively correlated with percentage area of nuclei (ρ = 0.38, p = 0.02).

CONCLUSION

Microstructures that are observed by histopathology are linked to MR characteristics and metabolite levels observed in prostate cancer.

Hierarchical non-negative matrix factorization applied to three-dimensional 3 T MRSI data for automatic tissue characterization of the prostate

In this study non-negative matrix factorization (NMF) was hierarchically applied to simulated and in vivo three-dimensional 3 T MRSI data of the prostate to extract patterns for tumour and benign tissue and to visualize their spatial distribution. Our studies show that the hierarchical scheme provides more reliable tissue patterns than those obtained by performing only one NMF level. We compared the performance of three different NMF implementations in terms of pattern detection accuracy and efficiency when embedded into the same kind of hierarchical scheme. The simulation and in vivo results show that the three implementations perform similarly, although one of them is more robust and better pinpoints the most aggressive tumour voxel(s) in the dataset. Furthermore, they are able to detect tumour and benign tissue patterns even in spectra with lipid artefacts. Copyright © 2016 John Wiley & Sons, Ltd.

Practical aspects of prostate MRI: hardware and software considerations, protocols, and patient preparation

The use of multiparametric MRI scans for the evaluation of men with prostate cancer has increased dramatically and is likely to continue expanding as new developments come to practice. However, it has not yet gained the same level of acceptance of other imaging tests. Partly, this is because of the use of suboptimal protocols, lack of standardization, and inadequate patient preparation. In this manuscript, we describe several practical aspects of prostate MRI that may facilitate the implementation of new prostate imaging programs or the expansion of existing ones.

Metabolite profiling in retinoblastoma identifies novel clinicopathological subgroups

BACKGROUND

Tumour classification, based on histopathology or molecular pathology, is of value to predict tumour behaviour and to select appropriate treatment. In retinoblastoma, pathology information is not available at diagnosis and only exists for enucleated tumours. Alternative methods of tumour classification, using noninvasive techniques such as magnetic resonance spectroscopy, are urgently required to guide treatment decisions at the time of diagnosis.

METHODS

High-resolution magic-angle spinning magnetic resonance spectroscopy (HR-MAS MRS) was undertaken on enucleated retinoblastomas. Principal component analysis and cluster analysis of the HR-MAS MRS data was used to identify tumour subgroups. Individual metabolite concentrations were determined and were correlated with histopathological risk factors for each group.

RESULTS

Multivariate analysis identified three metabolic subgroups of retinoblastoma, with the most discriminatory metabolites being taurine, hypotaurine, total-choline and creatine. Metabolite concentrations correlated with specific histopathological features: taurine was correlated with differentiation, total-choline and phosphocholine with retrolaminar optic nerve invasion, and total lipids with necrosis.

CONCLUSIONS

We have demonstrated that a metabolite-based classification of retinoblastoma can be obtained using ex vivo magnetic resonance spectroscopy, and that the subgroups identified correlate with histopathological features. This result justifies future studies to validate the clinical relevance of these subgroups and highlights the potential of in vivo MRS as a noninvasive diagnostic tool for retinoblastoma patient stratification.

Multiparametric-MRI in diagnosis of prostate cancer

Multiparametric-magnetic resonance imaging (mp-MRI) has shown promising results in diagnosis, localization, risk stratification and staging of clinically significant prostate cancer. It has also opened up opportunities for focal treatment of prostate cancer. Combinations of T2-weighted imaging, diffusion imaging, perfusion (dynamic contrast-enhanced imaging) and spectroscopic imaging have been used in mp-MRI assessment of prostate cancer, but T2 morphologic assessment and functional assessment by diffusion imaging remains the mainstay for prostate cancer diagnosis on mp-MRI. Because assessment on mp-MRI can be subjective, use of the newly developed standardized reporting Prostate Imaging and Reporting Archiving Data System scoring system and education of specialist radiologists are essential for accurate interpretation. This review focuses on the present status of mp-MRI in prostate cancer and its evolving role in the management of prostate cancer.

Innovation in metabolomics to improve personalized healthcare

Metabolomics is the systemic study of all small molecules (metabolites) and their concentration as affected by pathological and physiological alterations or environmental or other factors. Metabolic alterations represent a "window" on the complex interactions between genetic expression, enzyme activity, and metabolic reactions. Techniques, including nuclear magnetic resonance spectroscopy, mass spectrometry, Fourier-transform infrared, and Raman spectroscopy, have led to significant advances in metabolomics. The field is shifting from feasibility studies to biological and clinical applications. Fields of application range from cancer biology to stem cell research and assessment of xenobiotics and drugs in tissues and single cells. Cross-validation across high-throughput platforms has allowed findings from expression profiling to be confirmed with metabolomics. Specific genetic alterations appear to drive unique metabolic programs. These, in turn, can be used as biomarkers of genetic subtypes of prostate cancer or as discovery tools for therapeutic targeting of metabolic enzymes. Thus, metabolites in blood may serve as biomarkers of tumor state, including inferring driving oncogenes. Novel applications such as these suggest that metabolic profiling may be utilized in refining personalized medicine.

Tissue metabolite profiling identifies differentiating and prognostic biomarkers for prostate carcinoma

Metabolomic research offers a deeper insight into biochemical changes in cancer metabolism and is a promising tool for identifying novel biomarkers. We aimed to evaluate the diagnostic and prognostic potential of metabolites in prostate cancer (PCa) tissue after radical prostatectomy. In matched malignant and nonmalignant prostatectomy samples from 95 PCa patients, aminoadipic acid, cerebronic acid, gluconic acid, glycerophosphoethanolamine, 2-hydroxybehenic acid, isopentenyl pyrophosphate, maltotriose, 7-methylguanine and tricosanoic acid were determined within a global metabolite profiling study using gas chromatography/liquid chromatography-mass spectrometry. The data were related to clinicopathological variables like prostate volume, tumor stage, Gleason score, preoperative prostate-specific antigen and disease recurrence in the follow-up. All nine metabolites showed higher concentrations in malignant than in nonmalignant samples except for gluconic acid and maltotriose, which had lower levels in tumors. Receiver -operating characteristics analysis demonstrated a significant discrimination for all metabolites between malignant and nonmalignant tissue with a maximal area under the curve of 0.86 for tricosanoic acid, whereas no correlation was observed between the metabolite levels and the Gleason score or tumor stage except for gluconic acid. Univariate Cox regression and Kaplan-Meier analyses showed that levels of aminoadipic acid, gluconic acid and maltotriose were associated with the biochemical tumor recurrence (prostate-specific antigen > 0.2 ng/mL). In multivariate Cox regression analyses, aminoadipic acid together with tumor stage and Gleason score remained in a model as independent marker for prediction of biochemical recurrence. This study proved that metabolites in PCa tissue can be used, in combination with traditional clinicopathological factors, as promising diagnostic and prognostic tools.

Spermine and citrate as metabolic biomarkers for assessing prostate cancer aggressiveness

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

Metabolomic imaging of prostate cancer with magnetic resonance spectroscopy and mass spectrometry

Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized noninvasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth in patients with asymptomatic PCa newly diagnosed by biopsy. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, PCa metabolomics is mainly studied by magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates has demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies has uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness noninvasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be applied not only to PCa, but also to different tissues and organs to evaluate other human malignancies and metabolic diseases.