High resolution magic angle spinning NMR spectroscopy for metabolic assessment of cancer presence and Gleason score in human prostate needle biopsies

Integrative Metabolomic Analysis of Serum and Selected Serum Exosomal microRNA in Metastatic Castration-Resistant Prostate Cancer

Metastatic castration-resistant prostate cancer (mCRPC) remains a lethal disease due to the absence of effective therapies. A more comprehensive understanding of molecular events, encompassing the dysregulation of microRNAs (miRs) and metabolic reprogramming, holds the potential to unveil precise mechanisms underlying mCRPC. This study aims to assess the expression of selected serum exosomal miRs (miR-15a, miR-16, miR-19a-3p, miR-21, and miR-141a-3p) alongside serum metabolomic profiling and their correlation in patients with mCRPC and benign prostate hyperplasia (BPH). Blood serum samples from mCRPC patients (n = 51) and BPH patients (n = 48) underwent metabolome analysis through 1H-NMR spectroscopy. The expression levels of serum exosomal miRs in mCRPC and BPH patients were evaluated using a quantitative real-time polymerase chain reaction (qRT-PCR). The 1H-NMR metabolomics analysis revealed significant alterations in lactate, acetate, citrate, 3-hydroxybutyrate, and branched-chain amino acids (BCAAs, including valine, leucine, and isoleucine) in mCRPC patients compared to BPH patients. MiR-15a, miR-16, miR-19a-3p, and miR-21 exhibited a downregulation of more than twofold in the mCRPC group. Significant correlations were predominantly observed between lactate, citrate, acetate, and miR-15a, miR-16, miR-19a-3p, and miR-21. The importance of integrating metabolome analysis of serum with selected serum exosomal miRs in mCRPC patients has been confirmed, suggesting their potential utility for distinguishing of mCRPC from BPH.

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.

Metabolite interactions in prostatic fluid mimics assessed by 1H NMR

INTRODUCTION

Molecular interactions in prostatic fluid are of biological interest and may affect MRI and MRS of the prostate. We investigated the existence of interactions between the major components of this fluid: spermine, citrate and myoinositol, metal ions, including zinc, and proteins.

MATERIALS AND METHODS

Solutions of 90 mM citrate, 18 mM spermine and 6 mM myo-inositol, mimicking expressed prostatic fluid, were investigated by 1H NMR using changes in T2 relaxation and chemical shift as markers for interactions.

RESULTS AND DISCUSSION

Adding to this metabolite mixture the ions Na⁺ , K⁺, Ca⁺⁺, Mg⁺⁺ and Zn⁺⁺, decreased the T2 relaxation times of citrate and spermine protons by factors of 3 and 2, respectively, with Zn++ causing the largest effect, indicating ion-metabolite interactions. The T2 of 18 mM spermine dropped by a factor of 2 upon addition with 90 mM citrate, but no effect on T2 was seen with myo-inositol pointing to a specific citrate-spermine interaction. Moreover, the T2 of citrate in the presence of spermine decreased by adding metal ions and increasing amounts of Zn⁺⁺, indicating complexation of citrate and spermine with metal ions, particularly with Zn. The addition of bovine serum albumin (BSA), as an index protein, substantially further decreased the T2 of spermine and citrate implying the formation of a transient spermine-metal ion-citrate-BSA complex. Finally, we found that the T2 of citrate in extracellular fluid of prostate cancer cells, as a mimic of fluid in cancerous prostates, decreased by adding fetal calf serum, indicating protein binding.

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.

Developments in proton MR spectroscopic imaging of prostate cancer

In this paper, we review the developments of 1H-MR spectroscopic imaging (MRSI) methods designed to investigate prostate cancer, covering key aspects such as specific hardware, dedicated pulse sequences for data acquisition and data processing and quantification techniques. Emphasis is given to recent advancements in MRSI methodologies, as well as future developments, which can lead to overcome difficulties associated with commonly employed MRSI approaches applied in clinical routine. This includes the replacement of standard PRESS sequences for volume selection, which we identified as inadequate for clinical applications, by sLASER sequences and implementation of 1H MRSI without water signal suppression. These may enable a new evaluation of the complementary role and significance of MRSI in prostate cancer management.

Ex Vivo High-Resolution Magic Angle Spinning (HRMAS) 1H NMR Spectroscopy for Early Prostate Cancer Detection

Simple Summary

Prostate cancer is the second leading cancer diagnosed in men worldwide. Current diagnostic standards lack sufficient reliability in detecting and characterizing prostate cancer. Due to the cancer’s multifocality, prostate biopsies are associated with high numbers of false negatives. Whereas several studies have already shown the potential of metabolomic information for PCa detection and characterization, in this study, we focused on evaluating its predictive power for future PCa diagnosis. In our study, metabolomic information differed substantially between histobenign patients based on their risk for receiving a future PCa diagnosis, making metabolomic information highly valuable for the individualization of active surveillance strategies.

Abstract

The aim of our study was to assess ex vivo HRMAS (high-resolution magic angle spinning) ¹H NMR spectroscopy as a diagnostic tool for early PCa detection by testing whether metabolomic alterations in prostate biopsy samples can predict future PCa diagnosis. In a primary prospective study (04/2006–10/2018), fresh biopsy samples of 351 prostate biopsy patients were NMR spectroscopically analyzed (Bruker 14.1 Tesla, Billerica, MA, USA) and histopathologically evaluated. Three groups of 16 patients were compared: group 1 and 2 represented patients whose NMR scanned biopsy was histobenign, but patients in group 1 were diagnosed with cancer before the end of the study period, whereas patients in group 2 remained histobenign. Group 3 included cancer patients. Single-metabolite concentrations and metabolomic profiles were not only able to separate histobenign and malignant prostate tissue but also to differentiate between samples of histobenign patients who received a PCa diagnosis in the following years and those who remained histobenign. Our results support the hypothesis that metabolomic alterations significantly precede histologically visible changes, making metabolomic information highly beneficial for early PCa detection. Thanks to its predictive power, metabolomic information can be very valuable for the individualization of PCa active surveillance strategies.

Absolute choline tissue concentration mapping for prostate cancer localization and characterization using 3D 1 H MRSI without water-signal suppression

PURPOSE

Until now, ¹ H MRSI of the prostate has been performed with suppression of the large water signal to avoid distortions of metabolite signals. However, this signal can be used for absolute quantification and spectral corrections. We investigated the feasibility of water-unsuppressed MRSI in patients with prostate cancer for water signal-mediated spectral quality improvement and determination of absolute tissue levels of choline.

METHODS

Eight prostate cancer patients scheduled for radical prostatectomy underwent multi-parametric MRI at 3 T, including 3D water-unsuppressed semi-LASER MRSI. A postprocessing algorithm was developed to remove the water signal and its artifacts and use the extracted water signal as intravoxel reference for phase and frequency correction of metabolite signals and for absolute metabolite quantification.

RESULTS

Water-unsuppressed MRSI with dedicated postprocessing produced water signal and artifact-free MR spectra throughout the prostate. In all patients, the absolute choline tissue concentration was significantly higher in tumorous than in benign tissue areas (mean ± SD: 7.2 ± 1.4 vs 3.8 ± 0.7 mM), facilitating tumor localization by choline mapping. Tumor tissue levels of choline correlated better with the commonly used (choline + spermine + creatine)/citrate ratio (r = 0.78 ± 0.1) than that of citrate (r = 0.21 ± 0.06). The highest maximum choline concentrations occurred in high-risk cancer foci.

CONCLUSION

This report presents the first successful water-unsuppressed MRSI of the whole prostate. The water signal enabled amelioration of spectral quality and absolute metabolite quantification. In this way, choline tissue levels were identified as tumor biomarker. Choline mapping may serve as a tool in prostate cancer localization and risk scoring in multi-parametric MRI for diagnosis and biopsy procedures.

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.

Comprehensive metabolomics analysis of prostate cancer tissue in relation to tumor aggressiveness and TMPRSS2-ERG fusion status

Background

Prostate cancer (PC) can display very heterogeneous phenotypes ranging from indolent asymptomatic to aggressive lethal forms. Understanding how these PC subtypes vary in their striving for energy and anabolic molecules is of fundamental importance for developing more effective therapies and diagnostics. Here, we carried out an extensive analysis of prostate tissue samples to reveal metabolic alterations during PC development and disease progression and furthermore between TMPRSS2-ERG rearrangement-positive and -negative PC subclasses.

Methods

Comprehensive metabolomics analysis of prostate tissue samples was performed by non-destructive high-resolution magic angle spinning nuclear magnetic resonance (¹H HR MAS NMR). Subsequently, samples underwent moderate extraction, leaving tissue morphology intact for histopathological characterization. Metabolites in tissue extracts were identified by ¹H/³¹P NMR and liquid chromatography-mass spectrometry (LC-MS). These metabolomics profiles were analyzed by chemometric tools and the outcome was further validated using proteomic data from a separate sample cohort.

Results

The obtained metabolite patterns significantly differed between PC and benign tissue and between samples with high and low Gleason score (GS). Five key metabolites (phosphocholine, glutamate, hypoxanthine, arginine and α-glucose) were identified, who were sufficient to differentiate between cancer and benign tissue and between high to low GS. In ERG-positive PC, the analysis revealed several acylcarnitines among the increased metabolites together with decreased levels of proteins involved in β-oxidation; indicating decreased acyl-CoAs oxidation in ERG-positive tumors. The ERG-positive group also showed increased levels of metabolites and proteins involved in purine catabolism; a potential sign of increased DNA damage and oxidative stress.

Conclusions

Our comprehensive metabolomic analysis strongly indicates that ERG-positive PC and ERG-negative PC should be considered as different subtypes of PC; a fact requiring different, sub-type specific treatment strategies for affected patients.

Functional Expression of Choline Transporter-Like Protein 1 in LNCaP Prostate Cancer Cells: A Novel Molecular Target

Prostate cancer is one of the most common cancers in men. Choline PET or PET/CT has been used to visualize prostate cancer, and high levels of choline accumulation have been observed in tumors. However, the uptake system for choline and the functional expression of choline transporters in prostate cancer are not completely understood. In this study, the molecular and functional aspects of choline uptake were investigated in the LNCaP prostate cancer cell line along with the correlations between choline uptake and cell viability in drug-treated cells. Choline transporter-like protein 1 (CTL1) and CTL2 mRNA were highly expressed in LNCaP cells. CTL1 and CTL2 were located in the plasma membrane and mitochondria, respectively. [³H]Choline uptake was mediated by a single Na⁺-independent, intermediate-affinity transport system in the LNCaP cells. The anticancer drugs, flutamide and bicalutamide, inhibited cell viability and [³H]choline uptake in a concentration-dependent manner. The correlations between the effects of these drugs on cell viability and [³H]choline uptake were significant. Caspase-3/7 activity was significantly increased by both flutamide and bicalutamide. Furthermore, these drugs decreased CTL1 expression in the prostate cancer cell line. These results suggest that CTL1 is functionally expressed in prostate cancer cells and are also involved in abnormal proliferation. Identification of this CTL1-mediated choline transport system in prostate cancer cells provides a potential new therapeutic target for the treatment of this disease.

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.

NMR-Based Metabolomic Profiling of Urine: Evaluation for Application in Prostate Cancer Detection

Detection of prostate cancer (PCa) and distinguishing indolent versus aggressive forms of the disease is a critical clinical challenge. The current clinical test is circulating prostate-specific antigen levels, which faces particular challenges in cancer diagnosis in the range of 4 to 10 ng/mL. Thus, a concerted effort toward building a noninvasive biomarker panel has developed. In this report, the hypothesis that nuclear magnetic resonance (NMR)-derived metabolomic profiles measured in the urine of biopsy-negative versus biopsy-positive individuals would nominate a selection of potential biomarker signals was investigated. 1H NMR spectra of urine samples from 317 individuals (111 biopsy-negative, 206 biopsy-positive) were analyzed. A double cross-validation partial least squares-discriminant analysis modeling technique was utilized to nominate signals capable of distinguishing the two classes. It was observed that after variable selection protocols were applied, a subset of 29 variables produced an area under the curve (AUC) value of 0.94 after logistic regression analysis, whereas a “master list” of 18 variables produced a receiver operating characteristic ROC) AUC of 0.80. As proof of principle, this study demonstrates the utility of NMR-based metabolomic profiling of urine biospecimens in the nomination of PCa-specific biomarker signals and suggests that further investigation is certainly warranted.

Levels of choline-containing compounds in normal liver and liver metastases of colorectal cancer as recorded by 1 H MRS

PURPOSE

A relatively high signal for choline-containing compounds (total choline, tCho) is commonly found in ¹ H MR spectra of malignant tumors, but it is unclear if this also occurs in tumors in the liver. We evaluated the potential of the tCho signal in single voxel ¹ H MR spectra of the human liver to assess metastases of colorectal cancers.

EXPERIMENT

MR spectra of an 8 cm³ PRESS-localized voxel were obtained at 3 T from the livers of 12 healthy volunteers and from metastatic lesions in 20 patients in two different sessions. To correct for motion artifacts, sequentially recorded spectra were individually phased and frequency aligned before averaging. Spectra were analyzed using LCModel and tissue levels estimated by water referencing. Repeatability was assessed with Bland-Altman analyses. To estimate tumor necrosis, diffusion-weighted imaging of the liver was performed. High resolution magic angle spinning (HRMAS) spectra of tumor and normal liver samples were obtained at 11.7 T.

RESULTS

With increasing tumor volumes, tCho levels decreased, indicating a partial volume effect. Mean tCho content in tumors larger than the PRESS voxel (>8 cm³ ) was significantly lower (p < 0.01) than for normal liver: 1.6 (range 0.0-3.4) versus 6.9 (range 4.9-11.1) mmol/kg wet weight, while it was comparable for tumors smaller than 8 cm³ : 7.0 (range 3.8-9.3) mmol/kg. The higher 90th percentile apparent diffusion coefficient value in the larger lesions indicates more necrosis. Measurement repeatability was average in normal livers and poor in tumors. HRMAS did not show substantial differences in choline-containing compounds between normal liver and metastasis.

CONCLUSION

An increased tCho content was not observed in ¹ H MR spectra of liver metastasis of colorectal cancer, compared with normal liver. This may be due to the background of a high tCho signal in spectra of normal liver or to an intrinsic lower tCho content in these tumors, but is most likely the result of necrosis in metastatic tumor tissue.

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.

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.

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.

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications

One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

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.

(1)H MR spectroscopic imaging of the prostate at 7T using spectral-spatial pulses

PURPOSE

To assess the feasibility of prostate (1)H MR spectroscopic imaging (MRSI) using low-power spectral-spatial (SPSP) pulses at 7T, exploiting accurate spectral selection and spatial selectivity simultaneously.

METHODS

A double spin-echo sequence was equipped with SPSP refocusing pulses with a spectral selectivity of 1 ppm. Three-dimensional prostate (1)H-MRSI at 7T was performed with the SPSP-MRSI sequence using an 8-channel transmit array coil and an endorectal receive coil in three patients with prostate cancer and in one healthy subject. No additional water or lipid suppression pulses were used.

RESULTS

Prostate (1)H-MRSI could be obtained well within specific absorption rate (SAR) limits in a clinically feasible time (10 min). Next to the common citrate signals, the prostate spectra exhibited high spermine signals concealing creatine and sometimes also choline. Residual lipid signals were observed at the edges of the prostate because of limitations in spectral and spatial selectivity.

CONCLUSION

It is possible to perform prostate (1)H-MRSI at 7T with a SPSP-MRSI sequence while using separate transmit and receive coils. This low-SAR MRSI concept provides the opportunity to increase spatial resolution of MRSI within reasonable scan times.

Increased levels of choline metabolites are an early marker of docetaxel treatment response in BRCA1-mutated mouse mammary tumors: an assessment by ex vivo proton magnetic resonance spectroscopy

Background

Docetaxel is one of the most frequently used drugs to treat breast cancer. However, resistance or incomplete response to docetaxel is a major challenge. The aim of this study was to utilize MR metabolomics to identify potential biomarkers of docetaxel resistance in a mouse model for BRCA1-mutated breast cancer.

Methodology

High resolution magic angle spinning (HRMAS) ¹H MR spectroscopy was performed on tissue samples obtained from docetaxel-sensitive or -resistant BRCA1-mutated mammary tumors in mice. Measurements were performed on samples obtained before treatment and at 1-2, 3-5 and 6-7 days after a 25 mg/kg dose of docetaxel. The MR spectra were analyzed by multivariate analysis, followed by analysis of the signals of individual compounds by peak fitting and integration with normalization to the integral of the creatine signal and of all signals between 2.9 and 3.6 ppm.

Results

The HRMAS spectra revealed significant metabolic differences between sensitive and resistant tissue samples. In particular choline metabolites were higher in resistant tumors by more than 50% with respect to creatine and by more than 30% with respect to all signals between 2.9 and 3.6 ppm. Shortly after treatment (1-2 days) the normalized choline metabolite levels were significantly increased by more than 30% in the sensitive group coinciding with the time of highest apoptotic activity induced by docetaxel. Thereafter, choline metabolites in these tumors returned towards pre-treatment levels. No change in choline compounds was observed in the resistant tumors over the whole time of investigation.

Conclusions

Relative tissue concentrations of choline compounds are higher in docetaxel resistant than in sensitive BRCA1-mutated mouse mammary tumors, but in the first days after docetaxel treatment only in the sensitive tumors an increase of these compounds is observed. Thus both pre- and post-treatment tissue levels of choline compounds have potential to predict response to docetaxel treatment.

Temporal B0 field variation effects on MRSI of the human prostate at 7 T and feasibility of correction using an internal field probe

Spectral degradations as a result of temporal field variations are observed in MRSI of the human prostate. Moving organs generate substantial temporal and spatial field fluctuations as a result of susceptibility mismatch with the surrounding tissue (i.e. periodic breathing, cardiac motion or random bowel motion). Nine patients with prostate cancer were scanned with an endorectal coil (ERC) on a 7-T MR scanner. Temporal B0 field variations were observed with fast dynamic B0 mapping in these patients. Simulations of dynamic B0 corrections were performed using zero- to second-order shim terms. In addition, the temporal B0 variations were applied to simulated MR spectra causing, on average, 15% underestimation of the choline/citrate ratio. Linewidth distortions and frequency shifts (up to 30 and 8 Hz, respectively) were observed. To demonstrate the concept of observing local field fluctuations in real time during MRSI data acquisition, a field probe (FP) tuned and matched for the (19)  F frequency was incorporated into the housing of the ERC. The data acquired with the FP were compared with the B0 field map data and used to correct the MRSI datasets retrospectively. The dynamic B0 mapping data showed variations of up to 30 Hz (0.1 ppm) over 72 s at 7 T. The simulated zero-order corrections, calculated as the root mean square, reduced the standard deviation (SD) of the dynamic variations by an average of 41%. When using second-order corrections, the reduction in the SD was, on average, 56%. The FP data showed the same variation range as the dynamic B0 data and the variation patterns corresponded. After retrospective correction, the MRSI data showed artifact reduction and improved spectral resolution. B0 variations can degrade the MRSI substantially. The simple incorporation of an FP into an ERC can improve prostate cancer MRSI without prior knowledge of the origin of the dynamic field distortions.

Choline transporter-like proteins CTLs/SLC44 family as a novel molecular target for cancer therapy

Choline is essential for the synthesis of the major membrane phospholipid phosphatidylcholine (PC), the methyl donor betaine and the neurotransmitter acetylcholine (ACh). Elevated levels of choline and up-regulated choline kinase activity have been detected in various cancers. Thus, the intracellular accumulation of choline through choline transporters is the rate-limiting step in phospholipid metabolism and a prerequisite for cancer cell proliferation. Previous studies have demonstrated abnormalities in choline uptake and choline phospholipid metabolism in cancer cells using the imaging of cancer with positron emission tomography (PET) and magnetic resonance spectroscopy (MRS). The aberrant choline metabolism in cancer cells is strongly correlated with their malignant progression. Using quantitative real-time PCR, the mRNA expression of choline transporters was measured, and it was found that choline transporter-like proteins CTLs/SLC44 family are highly expressed in various cancer cell lines. Choline uptake through CTLs is associated with cell viability, and the functional inhibition of CTLs could promote apoptotic cell death. Furthermore, non-neuronal cholinergic systems that include CTLs-mediated choline transport are associated with cell proliferation and their inhibition promotes apoptotic cell death in colon cancer, small cell lung cancer and human leukemic T-cells. The identification of this new CTLs-mediated choline transport system provides a potential new target for cancer therapy.

High-resolution 1H NMR spectroscopy of fish muscle, eggs and small whole fish via Hadamard-encoded intermolecular multiple-quantum coherence

BACKGROUND AND PURPOSE

Nuclear magnetic resonance (NMR) spectroscopy has become an important technique for tissue studies. Since tissues are in semisolid-state, their high-resolution (HR) spectra cannot be obtained by conventional NMR spectroscopy. Because of this restriction, extraction and high-resolution magic angle spinning (HR MAS) are widely applied for HR NMR spectra of tissues. However, both of the methods are subject to limitations. In this study, the feasibility of HR (1)H NMR spectroscopy based on intermolecular multiple-quantum coherence (iMQC) technique is explored using fish muscle, fish eggs, and a whole fish as examples.

MATERIALS AND METHODS

Intact salmon muscle tissues, intact eggs from shishamo smelt and a whole fish (Siamese algae eater) are studied by using conventional 1D one-pulse sequence, Hadamard-encoded iMQC sequence, and HR MAS.

RESULTS

When we use the conventional 1D one-pulse sequence, hardly any useful spectral information can be obtained due to the severe field inhomogeneity. By contrast, HR NMR spectra can be obtained in a short period of time by using the Hadamard-encoded iMQC method without shimming. Most signals from fatty acids and small metabolites can be observed. Compared to HR MAS, the iMQC method is non-invasive, but the resolution and the sensitivity of resulting spectra are not as high as those of HR MAS spectra.

CONCLUSION

Due to the immunity to field inhomogeneity, the iMQC technique can be a proper supplement to HR MAS, and it provides an alternative for the investigation in cases with field distortions and with samples unsuitable for spinning. The acquisition time of the proposed method is greatly reduced by introduction of the Hadamard-encoded technique, in comparison with that of conventional iMQC method.

Mapping of prostate cancer by 1H MRSI

In many studies, it has been demonstrated that (1)H MRSI of the human prostate has great potential to aid prostate cancer management, e.g. in the detection and localisation of cancer foci in the prostate or in the assessment of its aggressiveness. It is particularly powerful in combination with T2 -weighted MRI. Nevertheless, the technique is currently mainly used in a research setting. This review provides an overview of the state-of-the-art of three-dimensional MRSI, including the specific hardware required, dedicated data acquisition sequences and information on the spectral content with background on the MR-visible metabolites. In clinical practice, it is important that relevant MRSI results become available rapidly, reliably and in an easy digestible way. However, this functionality is currently not fully available for prostate MRSI, which is a major obstacle for routine use by inexperienced clinicians. Routine use requires more automation in the processing of raw data than is currently available. Therefore, we pay specific attention in this review on the status and prospects of the automated handling of prostate MRSI data, including quality control. The clinical potential of three-dimensional MRSI of the prostate is illustrated with literature examples on prostate cancer detection, its localisation in the prostate, its role in the assessment of cancer aggressiveness and in the selection and monitoring of therapy.

High-resolution magic angle spinning 1H MRS in prostate cancer

Prostate cancer (PCa) is the most frequently diagnosed malignancy in men worldwide, largely as a result of the increased use of the annual serum prostate-specific antigen (PSA) screening test for detection. PSA screening has saved lives, but it has also resulted in the overtreatment of many patients with PCa because of a limited ability to accurately localize and characterize PCa lesions through imaging. High-resolution magic angle spinning (HRMAS) (1)H MRS has proven to be a strong potential clinical tool for PCa diagnosis and prognosis. The HRMAS technique allows valuable metabolic information to be obtained from ex vivo intact tissue samples and also enables the performance of histopathology on the same tissue specimens. Studies have found that the quantification of individual metabolite levels and metabolite ratios, as well as metabolomic profiles, shows strong potential to improve accuracy in PCa detection, diagnosis and monitoring. Ex vivo HRMAS is also a valuable tool for the interpretation of in vivo results, including the localization of tumors, and thus has the potential to improve in vivo diagnostic tests used in the clinic. Here, we primarily review publications of HRMAS (1)H MRS and its use for the study of intact human prostate tissue.

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

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

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.

1H-NMR based metabonomic profiling of human esophageal cancer tissue

BACKGROUND

The biomarker identification of human esophageal cancer is critical for its early diagnosis and therapeutic approaches that will significantly improve patient survival. Specially, those that involves in progression of disease would be helpful to mechanism research.

METHODS

In the present study, we investigated the distinguishing metabolites in human esophageal cancer tissues (n = 89) and normal esophageal mucosae (n = 26) using a (1)H nuclear magnetic resonance ((1)H-NMR) based assay, which is a highly sensitive and non-destructive method for biomarker identification in biological systems. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) were applied to analyse (1)H-NMR profiling data to identify potential biomarkers.

RESULTS

The constructed OPLS-DA model achieved an excellent separation of the esophageal cancer tissues and normal mucosae. Excellent separation was obtained between the different stages of esophageal cancer tissues (stage II = 28; stage III = 45 and stage IV = 16) and normal mucosae. A total of 45 metabolites were identified, and 12 of them were closely correlated with the stage of esophageal cancer. The downregulation of glucose, AMP and NAD, upregulation of formate indicated the large energy requirement due to accelerated cell proliferation in esophageal cancer. The increases in acetate, short-chain fatty acid and GABA in esophageal cancer tissue revealed the activation of fatty acids metabolism, which could satisfy the need for cellular membrane formation. Other modified metabolites were involved in choline metabolic pathway, including creatinine, creatine, DMG, DMA and TMA. These 12 metabolites, which are involved in energy, fatty acids and choline metabolism, may be associated with the progression of human esophageal cancer.

CONCLUSION

Our findings firstly identify the distinguishing metabolites in different stages of esophageal cancer tissues, indicating the attribution of metabolites disturbance to the progression of esophageal cancer. The potential biomarkers provide a promising molecular diagnostic approach for clinical diagnosis of human esophageal cancer and a new direction for the mechanism study.

In vivo (1) H MR spectroscopic imaging of aggressive prostate cancer: can we detect lactate?

PURPOSE

A semi-LASER sequence was optimized for in vivo lactate detection in the prostate.

METHODS

The ethical committee waived the need for informed consent to measure 17 patients with high grade prostate cancer on a 3T system. A semi-LASER sequence was used with an echo time of 144 ms and optimized interpulse timing for a spectral citrate shape with high signal intensity. An LCModel basis set was developed for fitting choline, creatine, spermine, citrate, and lactate and was used to fit all spectra in tumor-containing voxels. For patients without detectable lactate, the minimal detectable lactate concentration was determined by adding in all spectra of tumor tissue a simulated lactate signal. The amplitude of the simulated lactate signal was iteratively decreased until its fit reached a Cramér Rao lower bound >20%, which was then set as the patient-specific detection limit.

RESULTS

In none of the patients a convincing lactate signal was found. We estimated that on average the lactate levels in high grade prostate cancer are below 1.5 mM (range 0.9-3.5 mM), Interestingly, in one patient with extensive necrosis in the tumor biopsy samples (Gleason score 5+5), large lipid resonances were observed, which originated from the tumor.

CONCLUSION

The minimal detectable lactate concentration of 1.5 mM in high grade prostate cancer indicates that if lactate is increased it remains at low concentrations.

Study of metabonomic profiles of human esophageal carcinoma by use of high-resolution magic-angle spinning 1H NMR spectroscopy and multivariate data analysis

Esophageal carcinoma (EC) is one of the most common malignant tumors. EC survival has remained disappointingly low because of the high malignancy of esophageal cancer and the lack of obvious clinical symptoms at an early stage. Early diagnosis is often difficult because the small tumor nodules are frequently missed. Metabonomics based on high-resolution magic-angle spinning (HRMAS) NMR has been popular for tumor detection because it is highly sensitive, provides rich biochemical information and requires no sample pretreatment. (1)H HRMAS spectra of non-involved adjacent esophageal tissues and of well differentiated and moderately differentiated esophageal carcinoma tumors were recorded and analyzed by use of multivariate and statistical analysis techniques. Moderately differentiated EC tumors were found to have increased total choline, alanine, and glutamate and reduced creatine, myo-inositol, and taurine compared with non-involved adjacent tissues. Moreover, clear differences between the metabonomic profiles of EC tissues enabled tumor differentiation. Furthermore, the integral Gly/MI ratio for samples of different tissue types were statistically significantly different; this was sufficient both for distinguishing non-involved tissues from esophageal carcinoma and for classification of well differentiated and moderately differentiated EC tumors.

1H NMR analysis of choline metabolites in fine-needle-aspirate biopsies of breast cancer

OBJECT

The relative amounts of choline (Cho), phosphocholine (PC), and glycerophosphocholine (GPC) may be sensitive indicators of breast cancer and the degree of malignancy. Here we implement some simple modifications to a previously developed (1)H NMR analysis of fine-needle-aspirate (FNA) biopsies designed to yield sufficient spectral resolution of Cho, PC, and GPC for usable relative quantitation of these metabolites.

MATERIALS AND METHODS

FNA biopsies of eighteen breast lesions were examined using our modified procedure for direct (1)H NMR at 400 MHz. Resonances of choline metabolites and potential interferences were fit using the computer program NUTS.

RESULTS

Quantitation of PC, GPC, and Cho relative to each other and to (phospho)creatine was obtained for eleven confirmed cases of infiltrating ductal carcinoma. Reliable results could not be obtained for the remaining cases primarily due to interference from lidocaine anesthetic.

CONCLUSION

Some simple modifications of a previously developed (1)H NMR analysis of FNAs yielded sufficient spectral resolution of Cho, PC, and GPC to permit usable relative quantitation at 400 MHz. In 9 of the 11 quantified cases the sum of GPC and Cho exceeded 42 % of the total choline-metabolite peak area.

Changes in gene transcription underlying the aberrant citrate and choline metabolism in human prostate cancer samples

PURPOSE

Low concentrations of citrate and high concentrations of choline-containing compounds (ChoCC) are metabolic characteristics observed by magnetic resonance spectroscopy of prostate cancer tissue. The objective was to investigate the gene expression changes underlying these metabolic aberrations to find regulatory genes with potential for targeted therapies.

EXPERIMENTAL DESIGN

Fresh frozen samples (n = 133) from 41 patients undergoing radical prostatectomy were included. Histopathologic evaluation was carried out for each sample before a metabolic profile was obtained with high-resolution magic angle spinning (HR-MAS) spectroscopy. Following the HR-MAS, RNA was extracted from the same sample and quality controlled before carrying out microarray gene expression profiling. A partial least square statistical model was used to integrate the data sets to identify genes whose expression show significant covariance with citrate and ChoCC levels.

RESULTS

Samples were classified as benign, n = 35; cancer of low grade (Gleason score 6), n = 24; intermediate grade (Gleason score 7), n = 41; or high grade (Gleason score ≥ 8), n = 33. RNA quality was high with a mean RNA Integrity Number score of 9.1 (SD 1.2). Gene products predicting significantly a reduced citrate level were acetyl citrate lyase (ACLY, P = 0.003) and m-aconitase (ACON, P < 0.001). The two genes whose expression most closely accompanied the increase in ChoCC were those of phospholipase A2 group VII (PLA2G7, P < 0.001) and choline kinase α (CHKA, P = 0.002).

CONCLUSIONS

By integrating histologic, transcriptomic, and metabolic data, our study has contributed to an expanded understanding of the mechanisms underlying aberrant citrate and ChoCC levels in prostate cancer.

Magnetic resonance spectroscopy: a promising tool for the diagnostics of human prostate cancer?

BACKGROUND

Prostate cancer (CaP) is one of the topmost diagnosed malignant diseases worldwide. In developed countries, early cancer detection methods have led to an increase of incidence rates over the last decades; however, with great variance of the prognosis. There is no diagnostic tool for an exact prediction of tumor aggressiveness, thus there is a lack of adequate and optimal treatment planning.

METHODS

Electronic databases (Medline, PubMed) were scanned for scientific literature. Basic concepts of magnetic resonance spectroscopy (MRS), important results and its clinical applications were extracted and reviewed in this article.

CONCLUSIONS

MRS provides crucial information about the metabolic status of human prostate samples while preserving the specimens for further investigations. Single metabolites and metabolomic profiles can be quantified to distinguish benign from malignant tissue and to predict aggressiveness, such as the recurrence rates of CaP. Studies are also anticipating that MRS might be beneficially applicable for in vivo investigations in the future.

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.

Correlation of phospholipid metabolites with prostate cancer pathologic grade, proliferative status and surgical stage - impact of tissue environment

This study investigates the relationship between phospholipid metabolite concentrations, Gleason score, rate of cellular proliferation and surgical stage in malignant prostatectomy samples by performing one- and two-dimensional, high-resolution magic angle spinning, total correlation spectroscopy, pathology and Ki-67 staining on the same surgical samples. At radical prostatectomy, surgical samples were obtained from 49 patients [41 with localized TNM stage T1 and T2, and eight with local cancer spread (TNM stage T3)]. Thirteen of the tissue samples were high-grade prostate cancer [Gleason score: 4 + 3 (n = 7); 4 + 4 (n = 6)], 22 low-grade prostate cancer [Gleason score: 3 + 3 (n = 17); 3 + 4 (n = 5)] and 14 benign prostate tissues. This study demonstrates that high-grade prostate cancer shows significantly higher Ki-67 staining and concentrations of phosphocholine (PC) and glycerophosphocholine (GPC) than does low-grade prostate cancer (2.4 ± 2.8% versus 7.6 ± 3.5%, p < 0.005, and 0.671 ± 0.461 versus 1.87 ± 2.15 mmolal, p < 0.005, respectively). In patients with local cancer spread, increases in [PC + GPC + PE + GPE] (PE, phosphoethanolamine; GPE, glycerophosphoethanolamine] and Ki-67 index approached significance (4.2 ± 2.5 versus 2.7 ± 2.4 mmolal, p = 0.07, and 5.3 ± 3.8% versus 2.9 ± 3.8%, p = 0.07, respectively). PC and Ki-67 were significantly lower and GPC higher in prostate tissues when compared with cell cultures, presumably because of a lack of important stromal-epithelial interactions in cell cultures. The findings of this study will need to be validated in a larger cohort of surgical patients with clinical outcome data, but support the role of in vivo (1)H MRSI in discriminating between low- and high-grade prostate cancer based on the magnitude of elevation of the in vivo total choline resonance.

A decade in prostate cancer: from NMR to metabolomics

Over the past 30 years, continuous progress in the application of nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopic imaging (MRSI) to the detection, diagnosis and characterization of human prostate cancer has turned what began as scientific curiosity into a useful clinical option. In vivo MRSI technology has been integrated into the daily care of prostate cancer patients, and innovations in ex vivo methods have helped to establish NMR-based prostate cancer metabolomics. Metabolomic and multimodality imaging could be the future of the prostate cancer clinic--particularly given the rationale that more accurate interrogation of a disease as complex as human prostate cancer is most likely to be achieved through paradigms involving multiple, instead of single and isolated, parameters. The research and clinical results achieved through in vivo MRSI and ex vivo NMR investigations during the first 11 years of the 21st century illustrate areas where these technologies can be best translated into clinical practice.

In vivo assessment of prostate cancer aggressiveness using magnetic resonance spectroscopic imaging at 3 T with an endorectal coil

BACKGROUND

One of the most important clinical challenges in prostate cancer (PCa) management is an in vivo assessment of cancer aggressiveness.

OBJECTIVE

To validate the performance of magnetic resonance (MR) spectroscopic imaging (MRSI) of the prostate at 3 T for the purpose of assessing tumour aggressiveness based on the ratio of choline plus creatine to citrate (Cho+Cr/Cit) and of choline to creatine (Cho/Cr), using the Gleason score of the radical prostatectomy (RP) specimen as the gold standard.

DESIGN, SETTING, AND PARTICIPANTS

A total of 43 biopsy-proven PCa patients with 53 clinically relevant tumour foci were retrospectively included in this study.

MEASUREMENTS

Patients underwent MR imaging and MRSI examination followed by RP. From MRSI, all spectroscopy voxels containing tumour were selected by a radiologist guided by the prostatectomy histopathology map only. For each tumour, two spectroscopists determined the maximum Cho+Cr/Cit, Cho/Cr, and malignancy rating using a standardised threshold approach, incorporating both metabolic ratios. The maximum Cho+Cr/Cit, Cho/Cr, and malignancy ratings showed a relation to tumour aggressiveness and so were used to differentiate among tumour aggressiveness classes.

RESULTS AND LIMITATIONS

The maximum Cho+Cr/Cit ratio, maximum Cho/Cr ratio, and malignancy rating of a standardised threshold approach separated low-grade from higher-grade tumours, with areas under the receiver operating characteristic (ROC) curves of 0.70, 0.74, and 0.78, respectively.

CONCLUSIONS

MRSI offers possibilities for an in vivo, noninvasive assessment of PCa aggressiveness. The combination of the different metabolite ratios was used with promising results for discrimination among different aggressiveness classes.

H HRMAS NMR Derived Bio-markers Related to Tumor Grade, Tumor Cell Fraction, and Cell Proliferation in Prostate Tissue Samples

A high-resolution magic angle spinning NMR spectroscopic approach is presented for evaluating the occurrence, amount and aggressiveness of cancer in human prostate tissue samples. Using this technique, key metabolites in malignant and non-malignant samples (n = 149) were identified, and patterns of their relative abundance were analyzed by multivariate statistical methods. Ratios of various metabolites – including (glycerophophorylcholine + phosphorylcholine)/creatine, myo-inositol/scyllo-inositol, scyllo-inositol/creatine, choline/creatine, and citrate/creatine – correlated with: i) for non-malignant tissue samples, the distance to the nearest tumor and its Gleason score and; ii) the fraction of tumor cells present in the sample; and iii) tumor cell proliferation (Ki67 labelling index). This NMR-based approach allows the extraction of information that could be useful for developing novel diagnostic methods for prostate cancer.

Metabolomics: a novel approach to early and noninvasive prostate cancer detection

Prostate cancer (PCa) is the most commonly diagnosed visceral cancer in men and is responsible for the second highest cancer-related male mortality rate in Western countries, with increasing rates being reported in Korea, Japan, and China. Considering the low sensitivity of prostate-specific antigen (PSA) testing, it is widely agreed that reliable, age-independent markers of the presence, nature, and progression of PCa are required to facilitate diagnosis and timely treatment. Metabolomics or metabonomics has recently emerged as a novel method of PCa detection owing to its ability to monitor changes in the metabolic signature, within biofluids or tissue, that reflect changes in phenotype and function. This review outlines the physiology of prostate tissue and prostatic fluid in health and in malignancy in relation to metabolomics as well as the principles underlying the methods of metabolomic quantification. Promising metabolites, metabolic profiles, and their correlation with the presence and stage of PCa are summarized. Application of metabolomics to biofluids and in vivo quantification as well as the direction of current research in supplementing and improving current methods of detection are discussed. The current debate in the urology literature on sarcosine as a potential biomarker for PCa is reviewed and discussed. Metabolomics promises to be a valuable tool in the early detection of PCa that may enable earlier treatment and improved clinical outcomes.

Characterizing Human Cancer Metabolomics with ex vivo 1H HRMAS MRS

Publications of proton high resolution magic angle spinning (1 H HRMAS) magnetic resonance spectroscopy (MRS) and its role in identification of metabolic markers for human cancer reported between 2005 and 2009 are reviewed according the anatomic sites of cancer: lung, breast, prostate, brain, colorectal, and cervical. Limited and insufficient screening options for the general public have indicated a need for more advanced tests that can identify and locate cancer at an early stage. 1 H HRMAS MRS is a valuable tool that can elucidate relevant biological metabolite information that is being used to distinguish cancer from benign tissue, and even classify types of tumors. Researchers are working to translate this ex vivo spectroscopy information into an in vivo system that could be implemented in cancer clinics. For instance, in the case of lung cancer, the goal is to identify the at risk population through a simple blood test, which would be the first level of screening. From these tests, patients identified as at risk will be able to undergo further non-invasive radiological testing for diagnostic purposes. Not only will this ex vivo technology become a valuable diagnostic tool, it will also provide a way to monitor treatments on an individual basis so they can be adjusted accordingly for the best possible outcome.