Prediction of recurrence from metabolites and expression of TOP2A and EZH2 in prostate cancer patients treated with radiotherapy

BACKGROUND

The dual upregulation of TOP2A and EZH2 gene expression has been proposed as a biomarker for recurrence in prostate cancer patients to be treated with radical prostatectomy. A low tissue level of the metabolite citrate has additionally been connected to aggressive disease and recurrence in this patient group. However, for radiotherapy prostate cancer patients, few prognostic biomarkers have been suggested. The main aim of this study was to use an integrated tissue analysis to evaluate metabolites and expression of TOP2A and EZH2 as predictors for recurrence among radiotherapy patients.

METHODS

From 90 prostate cancer patients (56 received neoadjuvant hormonal treatment), 172 transrectal ultrasound-guided (TRUS) biopsies were collected prior to radiotherapy. Metabolic profiles were acquired from fresh frozen TRUS biopsies using high resolution-magic angle spinning MRS. Histopathology and immunohistochemistry staining for TOP2A and EZH2 were performed on TRUS biopsies containing cancer cells (n = 65) from 46 patients, where 24 of these patients (n = 31 samples) received hormonal treatment. Eleven radical prostatectomy cohorts of a total of 2059 patients were used for validation in a meta-analysis.

RESULTS

Among radiotherapy patients with up to 11 years of follow-up, a low level of citrate was found to predict recurrence, p = 0.001 (C-index = 0.74). Citrate had a higher predictive ability compared with individual clinical variables, highlighting its strength as a potential biomarker for recurrence. The dual upregulation of TOP2A and EZH2 was suggested as a biomarker for recurrence, particularly for patients not receiving neoadjuvant hormonal treatment, p = 0.001 (C-index = 0.84). While citrate was a statistically significant biomarker independent of hormonal treatment status, the current study indicated a potential of glutamine, glutamate and choline as biomarkers for recurrence among patients receiving neoadjuvant hormonal treatment, and glucose among patients not receiving neoadjuvant hormonal treatment.

CONCLUSION

Using an integrated approach, our study shows the potential of citrate and the dual upregulation of TOP2A and EZH2 as biomarkers for recurrence among radiotherapy patients.

Sample Preparation for Metabolite Detection in Mass Spectrometry Imaging

Metabolites reflect the biological state of cells and tissue, and metabolomics is therefore a field of high interest both to understand normal physiological functions and disease development. When studying heterogeneous tissue samples, mass spectrometry imaging (MSI) is a valuable tool as it conserves the spatial distribution of analytes on tissue sections. A large proportion of metabolites are, however, small and polar, making them vulnerable to delocalizing through diffusion during sample preparation. Here we present a sample preparation method optimized to limit diffusion and delocalization of small polar metabolites in fresh frozen tissue sections. This sample preparation protocol includes cryosectioning, vacuum frozen storage, and matrix application. The methods described were primely developed for matrix-assisted laser desorption/ionization (MALDI) MSI, but the protocol describing cryosectioning and vacuum freezing storage can also be applied before desorption electrospray ionization (DESI) MSI. Our vacuum drying and vacuum packing approach offers a particular advantage to limit delocalization and safe storage.

FunHoP analysis reveals upregulation of mitochondrial genes in prostate cancer

Mitochondrial activity in cancer cells has been central to cancer research since Otto Warburg first published his thesis on the topic in 1956. Although Warburg proposed that oxidative phosphorylation in the tricarboxylic acid (TCA) cycle was perturbed in cancer, later research has shown that oxidative phosphorylation is activated in most cancers, including prostate cancer (PCa). However, more detailed knowledge on mitochondrial metabolism and metabolic pathways in cancers is still lacking. In this study we expand our previously developed method for analyzing functional homologous proteins (FunHoP), which can provide a more detailed view of metabolic pathways. FunHoP uses results from differential expression analysis of RNA-Seq data to improve pathway analysis. By adding information on subcellular localization based on experimental data and computational predictions we can use FunHoP to differentiate between mitochondrial and non-mitochondrial processes in cancerous and normal prostate cell lines. Our results show that mitochondrial pathways are upregulated in PCa and that splitting metabolic pathways into mitochondrial and non-mitochondrial counterparts using FunHoP adds to the interpretation of the metabolic properties of PCa cells.

DNA methylation changes in response to neoadjuvant chemotherapy are associated with breast cancer survival

BACKGROUND

Locally advanced breast cancer is a heterogeneous disease with respect to response to neoadjuvant chemotherapy (NACT) and survival. It is currently not possible to accurately predict who will benefit from the specific types of NACT. DNA methylation is an epigenetic mechanism known to play an important role in regulating gene expression and may serve as a biomarker for treatment response and survival. We investigated the potential role of DNA methylation as a prognostic marker for long-term survival (> 5 years) after NACT in breast cancer.

METHODS

DNA methylation profiles of pre-treatment (n = 55) and post-treatment (n = 75) biopsies from 83 women with locally advanced breast cancer were investigated using the Illumina HumanMethylation450 BeadChip. The patients received neoadjuvant treatment with epirubicin and/or paclitaxel. Linear mixed models were used to associate DNA methylation to treatment response and survival based on clinical response to NACT (partial response or stable disease) and 5-year survival, respectively. LASSO regression was performed to identify a risk score based on the statistically significant methylation sites and Kaplan-Meier curve analysis was used to estimate survival probabilities using ten years of survival follow-up data. The risk score developed in our discovery cohort was validated in an independent validation cohort consisting of paired pre-treatment and post-treatment biopsies from 85 women with locally advanced breast cancer. Patients included in the validation cohort were treated with either doxorubicin or 5-FU and mitomycin NACT.

RESULTS

DNA methylation patterns changed from before to after NACT in 5-year survivors, while no significant changes were observed in non-survivors or related to treatment response. DNA methylation changes included an overall loss of methylation at CpG islands and gain of methylation in non-CpG islands, and these changes affected genes linked to transcription factor activity, cell adhesion and immune functions. A risk score was developed based on four methylation sites which successfully predicted long-term survival in our cohort (p = 0.0034) and in an independent validation cohort (p = 0.049).

CONCLUSION

Our results demonstrate that DNA methylation patterns in breast tumors change in response to NACT. These changes in DNA methylation show potential as prognostic biomarkers for breast cancer survival.

The genes controlling normal function of citrate and spermine secretion are lost in aggressive prostate cancer and prostate model systems

High secretion of the metabolites citrate and spermine is a unique hallmark for normal prostate epithelial cells, and is reduced in aggressive prostate cancer. However, the identity of the genes controlling this biological process is mostly unknown. In this study, we have created a gene signature of 150 genes connected to citrate and spermine secretion in the prostate. We have computationally integrated metabolic measurements with multiple transcriptomics datasets from the public domain, including 3826 tissue samples from prostate and prostate cancer. The accuracy of the signature is validated by its unique enrichment in prostate samples and prostate epithelial tissue compartments. The signature highlights genes AZGP1, ANPEP and metallothioneins with zinc-binding properties not previously studied in the prostate, and the expression of these genes are reduced in more aggressive cancer lesions. However, the absence of signature enrichment in common prostate model systems can make it challenging to study these genes mechanistically.

•

Novel 150 gene signature reflecting prostatic citrate and spermine secretion

•

Identified several zinc-binding proteins not previously investigated in the prostate

•

The signature is absent in prostate model systems

An optimized MALDI MSI protocol for spatial detection of tryptic peptides in fresh frozen prostate tissue

MALDI MS imaging (MSI) is a powerful analytical tool for spatial peptide detection in heterogeneous tissues. Proper sample preparation is crucial to achieve high quality, reproducible measurements. Here we developed an optimized protocol for spatially resolved proteolytic peptide detection with MALDI time‐of‐flight MSI of fresh frozen prostate tissue sections. The parameters tested included four different tissue washes, four methods of protein denaturation, four methods of trypsin digestion (different trypsin densities, sprayers, and incubation times), and five matrix deposition methods (different sprayers, settings, and matrix concentrations). Evaluation criteria were the number of detected and excluded peaks, percentage of high mass peaks, signal‐to‐noise ratio, spatial localization, and average intensities of identified peptides, all of which were integrated into a weighted quality evaluation scoring system. Based on these scores, the optimized protocol included an ice‐cold EtOH+H₂O wash, a 5 min heating step at 95°C, tryptic digestion incubated for 17h at 37°C and CHCA matrix deposited at a final amount of 1.8 μg/mm². Including a heat‐induced protein denaturation step after tissue wash is a new methodological approach that could be useful also for other tissue types. This optimized protocol for spatial peptide detection using MALDI MSI facilitates future biomarker discovery in prostate cancer and may be useful in studies of other tissue types.

OUP accepted manuscript

A rapid and cost-efficient tissue preparation protocol for laser ablation-inductively coupled plasma-mass spectrometry imaging (LA–ICP–MSI) has been developed within this study as an alternative to the current gold standard using fresh-frozen samples or other preparation techniques such as formalin fixation (FFix) and formalin-fixed paraffin-embedding (FFPE). Samples were vacuum dried at room temperature (RT) and stored in sealed vacuum containers for storage and shipping between collaborating parties. We compared our new protocol to established methods using prostate tissue sections investigating typical endogenous elements such as zinc, iron, and phosphorous with LA–ICP–MSI. The new protocol yielded comparable imaging results as fresh-frozen sections. FFPE sections were also tested due to the wide use and availability of FFPE tissue. However, the FFPE protocol and the FFix alone led to massive washout of the target elements on the sections tested in this work. Therefore, our new protocol presents an easy and rapid alternative for tissue preservation with comparable results to fresh-frozen sections for LA–ICP–MSI. It overcomes washout risks of commonly used tissue fixation techniques and does not require expensive and potentially unstable and time-critical shipping of frozen material on dry ice. Additionally, this protocol is likely applicable for several bioimaging approaches, as the dry condition may act comparable to other dehydrating fixatives, such as acetone or methanol, preventing degradation while avoiding washout effects.

FunHoP: Enhanced Visualization and Analysis of Functionally Homologous Proteins in Complex Metabolic Networks

Cytoscape is often used for visualization and analysis of metabolic pathways. For example, based on KEGG data, a reader for KEGG Markup Language (KGML) is used to load files into Cytoscape. However, although multiple genes can be responsible for the same reaction, the KGML-reader KEGGScape only presents the first listed gene in a network node for a given reaction. This can lead to incorrect interpretations of the pathways. Our new method, FunHoP, shows all possible genes in each node, making the pathways more complete. FunHoP collapses all genes in a node into one measurement using read counts from RNA-seq. Assuming that activity for an enzymatic reaction mainly depends upon the gene with the highest number of reads, and weighting the reads on gene length and ratio, a new expression value is calculated for the node as a whole. Differential expression at node level is then applied to the networks. Using prostate cancer as model, we integrate RNA-seq data from two patient cohorts with metabolism data from literature. Here we show that FunHoP gives more consistent pathways that are easier to interpret biologically. Code and documentation for running FunHoP can be found at https://github.com/kjerstirise/FunHoP.

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.

Detection of Recurrent Prostate Cancer With 18F-Fluciclovine PET/MRI

Objective

Simultaneous PET/MRI combines soft-tissue contrast of MRI with high molecular sensitivity of PET in one session. The aim of this prospective study was to evaluate detection rates of recurrent prostate cancer by ¹⁸F-fluciclovine PET/MRI.

Methods

Patients with biochemical recurrence (BCR) or persistently detectable prostate specific antigen (PSA), were examined with simultaneous ¹⁸F-fluciclovine PET/MRI. Multiparametric MRI (mpMRI) and PET/MRI were scored on a 3-point scale (1-negative, 2-equivocal, 3-recurrence/metastasis) and detection rates (number of patients with suspicious findings divided by total number of patients) were reported. Detection rates were further stratified based on PSA level, PSA doubling time (PSAdt), primary treatment and inclusion criteria (PSA persistence, European Association of Urology (EAU) Low-Risk BCR and EAU High-Risk BCR). A detailed investigation of lesions with discrepancy between mpMRI and PET/MRI scores was performed to evaluate the incremental value of PET/MRI to mpMRI. The impact of the added PET acquisition on further follow-up and treatment was evaluated retrospectively.

Results

Among patients eligible for analysis (n=84), 54 lesions were detected in 38 patients by either mpMRI or PET/MRI. Detection rates were 41.7% for mpMRI and 39.3% for PET/MRI (score 2 and 3 considered positive). There were no significant differences in detection rates for mpMRI versus PET/MRI. Disease detection rates were higher in patients with PSA≥1ng/mL than in patients with lower PSA levels but did not differ between patients with PSAdt above versus below 6 months. Detection rates in patients with primary radiation therapy were higher than in patients with primary surgery. Patients categorized as EAU Low-Risk BCR had a detection rate of 0% both for mpMRI and PET/MRI. For 15 lesions (27.8% of all lesions) there was a discrepancy between mpMRI score and PET/MRI score. Of these, 10 lesions scored as 2-equivocal by mpMRI were changed to a more definite score (n=4 score 1 and n=6 score 3) based on the added PET acquisition. Furthermore, for 4 of 10 patients with discrepancy between mpMRI and PET/MRI scores, the added PET acquisition had affected the treatment choice.

Conclusion

Combined ¹⁸F-fluciclovine PET/MRI can detect lesions suspicious for recurrent prostate cancer in patients with a range of PSA levels. Combined PET/MRI may be useful to select patients for appropriate treatment, but is of limited use at low PSA values or in patients classified as EAU Low-Risk BCR, and the clinical value of ¹⁸F-fluciclovine PET/MRI in this study was too low to justify routine clinical use.

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.

Cholesterol synthesis pathway genes in prostate cancer are transcriptionally downregulated when tissue confounding is minimized

BACKGROUND

The relationship between cholesterol and prostate cancer has been extensively studied for decades, where high levels of cellular cholesterol are generally associated with cancer progression and less favorable outcomes. However, the role of in vivo cellular cholesterol synthesis in this process is unclear, and data on the transcriptional activity of cholesterol synthesis pathway genes in tissue from prostate cancer patients are inconsistent.

METHODS

A common problem with cancer tissue data from patient cohorts is the presence of heterogeneous tissue which confounds molecular analysis of the samples. In this study we present a general method to minimize systematic confounding from stroma tissue in any prostate cancer cohort comparing prostate cancer and normal samples. In particular we use samples assessed by histopathology to identify genes enriched and depleted in prostate stroma. These genes are then used to assess stroma content in tissue samples from other prostate cancer cohorts where no histopathology is available. Differential expression analysis is performed by comparing cancer and normal samples where the average stroma content has been balanced between the sample groups. In total we analyzed seven patient cohorts with prostate cancer consisting of 1713 prostate cancer and 230 normal tissue samples.

RESULTS

When stroma confounding was minimized, differential gene expression analysis over all cohorts showed robust and consistent downregulation of nearly all genes in the cholesterol synthesis pathway. Additional Gene Ontology analysis also identified cholesterol synthesis as the most significantly altered metabolic pathway in prostate cancer at the transcriptional level.

CONCLUSION

The surprising observation that cholesterol synthesis genes are downregulated in prostate cancer is important for our understanding of how prostate cancer cells regulate cholesterol levels in vivo. Moreover, we show that tissue heterogeneity explains the lack of consistency in previous expression analysis of cholesterol synthesis genes in prostate cancer.

NMR-based metabolomics of biofluids in cancer

This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.

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.

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.

Metabolic markers in blood can separate prostate cancer from benign prostatic hyperplasia

Background:

An individualised risk-stratified screening for prostate cancer (PCa) would select the patients who will benefit from further investigations as well as therapy. Current detection methods suffer from low sensitivity and specificity, especially for separating PCa from benign prostatic conditions. We have investigated the use of metabolomics analyses of blood samples for separating PCa patients and controls with benign prostatic hyperplasia (BPH).

Methods:

Blood plasma and serum samples from 29 PCa patient and 21 controls with BPH were analysed by metabolomics analysis using magnetic resonance spectroscopy, mass spectrometry and gas chromatography. Differences in blood metabolic patterns were examined by multivariate and univariate statistics.

Results:

By combining results from different methodological platforms, PCa patients and controls were separated with a sensitivity and specificity of 81.5% and 75.2%, respectively.

Conclusions:

The combined analysis of serum and plasma samples by different metabolomics measurement techniques gave successful discrimination of PCa and controls, and provided metabolic markers and insight into the processes characteristic of PCa. Our results suggest changes in fatty acid (acylcarnitines), choline (glycerophospholipids) and amino acid metabolism (arginine) as markers for PCa compared with BPH.

Identification of metabolites from 2D (1)H-(13)C HSQC NMR using peak correlation plots

BACKGROUND

Identification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies. NMR spectroscopy is an excellent technique for analysis of mixtures of organic compounds and gives a detailed chemical fingerprint of most individual components above the detection limit. For the identification of individual metabolites in metabolomics, correlation or covariance between peaks in (1)H NMR spectra has previously been successfully employed. Similar correlation of 2D (1)H-(13)C Heteronuclear Single Quantum Correlation spectra was recently applied to investigate the structure of heparine. In this paper, we demonstrate how a similar approach can be used to identify metabolites in human biofluids (post-prostatic palpation urine).

RESULTS

From 50 (1)H-(13)C Heteronuclear Single Quantum Correlation spectra, 23 correlation plots resembling pure metabolites were constructed. The identities of these metabolites were confirmed by comparing the correlation plots with reported NMR data, mostly from the Human Metabolome Database.

CONCLUSIONS

Correlation plots prepared by statistically correlating (1)H-(13)C Heteronuclear Single Quantum Correlation spectra from human biofluids provide unambiguous identification of metabolites. The correlation plots highlight cross-peaks belonging to each individual compound, not limited by long-range magnetization transfer as conventional NMR experiments.

Gene signatures ESC, MYC and ERG-fusion are early markers of a potentially dangerous subtype of prostate cancer

Background

Good prognostic tools for predicting disease progression in early stage prostate cancer (PCa) are still missing. Detection of molecular subtypes, for instance by using microarray gene technology, can give new prognostic information which can assist personalized treatment planning. The detection of new subtypes with validation across additional and larger patient cohorts is important for bringing a potential prognostic tool into the clinic.

Methods

We used fresh frozen prostatectomy tissue of high molecular quality to further explore four molecular subtype signatures of PCa based on Gene Set Enrichment Analysis (GSEA) of 15 selected gene sets published in a previous study. For this analysis we used a statistical test of dependent correlations to compare reference signatures to signatures in new normal and PCa samples, and also explore signatures within and between sample subgroups in the new samples.

Results

An important finding was the consistent signatures observed for samples from the same patient independent of Gleason score. This proves that the signatures are robust and can surpass a normally high tumor heterogeneity within each patient. Our data did not distinguish between four different subtypes of PCa as previously published, but rather highlighted two groups of samples which could be related to good and poor prognosis based on survival data from the previous study.The poor prognosis group highlighted a set of samples characterized by enrichment of ESC, ERG-fusion and MYC + rich signatures in patients diagnosed with low Gleason score,. The other group consisted of PCa samples showing good prognosis as well as normal samples. Accounting for sample composition (the amount of benign structures such as stroma and epithelial cells in addition to the cancer component) was important to improve subtype assignments and should also be considered in future studies.

Conclusion

Our study validates a previous molecular subtyping of PCa in a new patient cohort, and identifies a subgroup of PCa samples highly interesting for detecting high risk PCa at an early stage. The importance of taking sample tissue composition into account when assigning subtype is emphasized.

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.

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.

A new method to provide a fresh frozen prostate slice suitable for gene expression study and MR spectroscopy

BACKGROUND

Fresh frozen tissue from radical prostatectomy specimens is highly valuable material for research on gene expression and cellular metabolites. The purpose of this study was to develop a standardized method to provide a representative high quality research sample from radical prostatectomy specimens without interfering with the routine histopathological procedure.

METHODS

A complete transversal slice is collected and snap-frozen before formalin fixation and routine processing of the remaining gland. The freezing preserves the original geometric shape, thus allowing subsampling of specific cell populations without thawing. RNA was extracted from 53 cylindrical subsamples (diameter 3 mm, thickness 2 mm) from 16 consecutive frozen slices. The histological pattern was evaluated by microscopy of a cryosection from sample before further analysis.

RESULTS

Using this novel harvesting method close to 400 slices have been collected. Whenever tumor was present in both adjacent surrounding hematoxylin-eosin sections, we found cancer in 88% of the frozen slices. The extracted RNA showed very high quality with a mean RNA integrity number of 9.16 (SD 0.53). The MR spectra showed metabolic profiles containing several resonances, which deserve further evaluation as possible biomarkers for prostate cancer. After MR analysis the RNA was still highly intact with a mean RNA integrity number of 8.40 (SD 1.53), which makes it possible to correlate transcriptomic and metabolomic profiles of the extracted samples.

CONCLUSION

We present a safe and standardized method for procurement of a high quality fresh frozen prostate slice, suitable for gene expression analysis and MR spectroscopy.

Alignment of high resolution magic angle spinning magnetic resonance spectra using warping methods

The peaks of magnetic resonance (MR) spectra can be shifted due to variations in physiological and experimental conditions, and correcting for misaligned peaks is an important part of data processing prior to multivariate analysis. In this paper, five warping algorithms (icoshift, COW, fastpa, VPdtw and PTW) are compared for their feasibility in aligning spectral peaks in three sets of high resolution magic angle spinning (HR-MAS) MR spectra with different degrees of misalignments, and their merits are discussed. In addition, extraction of information that might be present in the shifts is examined, both for simulated data and the real MR spectra. The generic evaluation methodology employs a number of frequently used quality criteria for evaluation of the alignments, together with PLS-DA to assess the influence of alignment on the classification outcome. Peak alignment greatly improved the internal similarity of the data sets. Especially icoshift and COW seem suitable for aligning HR-MAS MR spectra, possibly because they perform alignment segment-wise. The choice of reference spectrum can influence the alignment result, and it is advisable to test several references. Information from the peak shifts was extracted, and in one case cancer samples were successfully discriminated from normal tissue based on shift information only. Based on these findings, general recommendations for alignment of HR-MAS MRS data are presented. Where possible, observations are generalized to other data types (e.g. chromatographic data).

HR MAS MR spectroscopy in metabolic characterization of cancer

One of the central hallmarks of cancer is the rapid and infinite cellular proliferation. In order to cope with increased requirement for building blocks and energy, cancer cells develop abnormal metabolic properties. Detailed assessment of cancer cell metabolism can provide biological information for use in both drug discovery and development of personalized cancer therapy. Analysis of intact tissue using high resolution magic angle spinning (HR MAS) magnetic resonance spectroscopy (MRS) gives qualitative and quantitative metabolite measures with minimal sample preparation. Multivariate statistical methods are important tools for analysis of complex MR data and have in recent years been used for analysis of HR MAS data from intact tissue. HR MAS analysis of intact tissue allows combination of metabolomic data with genomic or proteomic data, and can therefore be used both for exploring the molecular biology of cancer and for clinical improvements in cancer diagnostics, prognostics and treatment planning. In this review, the basic concepts of HR MAS are presented, and its use in characterisation of cancer metabolism is discussed with specific focus on selected pathways such as choline metabolism and glycolysis. The use of HR MAS in analysis of amino acids and lipid metabolism in cancer is also reviewed. Finally, the expected role of HR-MAS in metabolic characterisation in the near future is discussed.

Magnetic resonance metabolomics of intact tissue: a biotechnological tool in cancer diagnostics and treatment evaluation

Personalized medicine is increasingly important in cancer treatment for its role in staging and its potential to improve stratification of patients. Different types of molecules, genes, proteins, and metabolites are being extensively explored as potential biomarkers. This review discusses the major findings and potential of tissue metabolites determined by high-resolution magic angle spinning magnetic resonance spectroscopy for cancer detection, characterization, and treatment monitoring.

Evaluation of lactate and alanine as metabolic biomarkers of prostate cancer using 1H HR-MAS spectroscopy of biopsy tissues

The goal of this study was to investigate the use of lactate and alanine as metabolic biomarkers of prostate cancer using (1)H high-resolution magic angle spinning (HR-MAS) spectroscopy of snap-frozen transrectal ultrasound (TRUS)-guided prostate biopsy tissues. A long-echo-time rotor-synchronized Carr-Purcell-Meiboom-Gill (CPMG) sequence including an electronic reference to access in vivo concentrations (ERETIC) standard was used to determine the concentrations of lactate and alanine in 82 benign and 16 malignant biopsies (mean 26.5% +/- 17.2% of core). Low concentrations of lactate (0.61 +/- 0.28 mmol/kg) and alanine (0.14 +/- 0.06 mmol/kg) were observed in benign prostate biopsies, and there was no significant difference between benign predominantly glandular (N = 54) and stromal (N = 28) biopsies between patients with (N = 38) and without (N = 44) a positive clinical biopsy. In biopsies containing prostate cancer there was a highly significant (P < 0.0001) increase in lactate (1.59 +/- 0.61 mmol/kg) and alanine (0.26 +/- 0.07 mmol/kg), and minimal overlap with lactate concentrations in benign biopsies. This study demonstrates for the first time very low concentrations of lactate and alanine in benign prostate biopsy tissues. The significant increase in the concentration of both lactate and alanine in biopsy tissue containing as little as 5% cancer could be exploited in hyperpolarized (13)C spectroscopic imaging (SI) studies of prostate cancer patients.

The effect of single and repeated UVB radiation on rabbit cornea

BACKGROUND

Cumulative effect of ultraviolet radiation (UVR) is an important aspect of UV corneal damage. The purpose of this study was to apply high resolution magic angle spinning proton nuclear magnetic resonance (HR-MAS 1H NMR) spectroscopy to evaluate the effect of single and repeated UV radiation exposure of the same overall dose on the rabbit cornea.

METHODS

Corneal surfaces of 24 normal rabbit eyes were examined for the effects of UVB exposure (312 nm). In the first group (UVB1), animals were irradiated with a single dose (3.12 J/cm2; 21 min) of UVB radiation. The animals in the second group (UVB2) were irradiated three times for 7 min every other day (dose of 1.04 J/cm2; days 1, 3, 5) to give the same overall dose (3.12 J/cm2). The third group served as an untreated control group. One day after the last irradiation, the animals were sacrificed, and the corneas were removed and frozen. HR-MAS 1H NMR spectra from intact corneas were obtained. Special grouping patterns among the tissue samples and the relative percentage changes in particular metabolite concentrations were evaluated using modern statistical methods (multivariate analysis, one-way ANOVA).

RESULTS

The metabolic profile of both groups of UVB-irradiated samples was significantly different from the control corneas. Substantial decreases in taurine, hypo-taurine and choline-derivatives concentrations and substantial elevation in glucose and betaine levels were observed following the UVR exposure. There was no significant difference between the effect of a single and repeated UVB irradiation of the same overall dose.

CONCLUSIONS

For the first time, the effects of single and repeated UVR doses on the metabolic profile of the rabbit cornea were analysed and compared. The combination of HR-MAS 1H NMR spectroscopy and modern statistical methods (multivariate analysis, one-way ANOVA) proved suitable to assess the overall view of the metabolic alterations in the rabbit corneal tissue following UVB radiation exposure.

Biological response in various compartments of the rat lens after in vivo exposure to UVR-B analyzed by HR-MAS 1H NMR spectroscopy

PURPOSE

The purpose of the present study was to investigate metabolic changes in different compartments of the rat lens (anterior, nuclear, posterior, and equatorial) after exposure to an acute double threshold dose of ultraviolet-B radiation (UVR-B) by using high-resolution magic angle spinning (HR-MAS) (1)H nuclear magnetic resonance (NMR) spectroscopy and pattern recognition (PR) METHODS: methods. One eye in each of 28 6-week-old female albino Sprague-Dawley rats was exposed to in vivo 7.5 kJ/m2 UVR-B for 15 minutes. The contralateral eye was left unexposed. One week after irradiation, all rats were killed, and both lenses were isolated. Each lens was cored by a trephine, and the cylinder was sliced into three portions (anterior, nuclear, and posterior). The lens material that remained after the coring process was analyzed as the equatorial region. Analysis of lens metabolism was performed by HR-MAS 1H NMR spectroscopy (14.1 T; Avance DRX600; Bruker BioSpin GmbH, Rheinstetten, Germany), and the metabolic profiles were statistically analyzed by the PR method of principal component analysis (PCA).

RESULTS

Metabolic differences were detected among the compartments in the lens, both in samples from the contralateral nonexposed lenses and in samples from lenses exposed to in vivo UVR-B. In the rat lens, exposure to UVR-B caused changes in GSH, phosphocholine, myo-inositol, succinate, formate, and adenosine triphosphate (ATP)/adenosine diphosphate (ADP) and in levels of the amino acids phenylalanine, taurine, hypo-taurine, tyrosine, alanine, valine, isoleucine, and glutamate, that varied among lens compartments.

CONCLUSIONS

HR-MAS 1H NMR spectroscopy, combined with PR methods (PCA), is effective for analysis of separate parts of the intact rat lens. To understand the biochemistry of the lens, it is important to divide the lens into sections, representing functionally and anatomically distinct compartments.

Biochemical changes in selenite cataract model measured by high-resolution MAS H NMR spectroscopy

PURPOSE

To correlate certain levels of lens opacification with high-resolution magic-angle spinning proton nuclear magnetic resonance (HR-MAS (1)H NMR) spectroscopy analysis of the biochemical changes in rat lenses in a selenite cataract model.

METHODS

Selenite cataract was induced by injecting 13-day-old Sprague-Dawley rat pups with a single subcutaneous dose of sodium selenite (3.28 mg/kg in 0.9% sodium chloride solution). Lens opacification was observed using a photographic slit-lamp microscope at selected time-points 3, 6 and 9 days after selenite injection and was then graded (levels 0, 1 and 2). The animals were killed after the slit-lamp microscopy, lenses were removed and HR-MAS (1)H NMR spectra from intact lenses were obtained. Relative changes in metabolite concentrations were determined after comparison with matched lenses from untreated animals.

RESULTS

Photographic slit-lamp microscopy revealed different stages of cataract in all animals treated with selenite. In the high quality HR-MAS (1)H NMR spectra of the lenses, more than 30 different metabolites were identified in each lens. With the exception of taurine, the concentrations of all amino acids showed a significant increase (p < 0.05) in the second level of cataract. By contrast, glutathione (GSH), succinate and phosphocholine concentrations were significantly reduced.

CONCLUSIONS

For the first time, this study demonstrates the potential to correlate the level of lens opacification with the biochemical changes obtained with HR-MAS (1)H NMR spectroscopy analysis in a selenite cataract model.

Effect of UVA and UVB Irradiation on the Metabolic Profile of Rabbit Cornea and Lens Analysed by HR-MAS 1H NMR Spectroscopy

PURPOSE

The aim of the study was to investigate the metabolic profiles of intact rabbit corneas and lenses exposed to UVA and UVB radiation by using high-resolution (HR) magic angle spinning (MAS) (1)H nuclear magnetic resonance (NMR) spectroscopy and pattern recognition methods.

METHODS

Adult albino rabbits were exposed to UVA (366 nm, 0.589 J/cm(2)) or UVB (312 nm, 1.667 J/cm(2)) radiation for 8 min, once a day for 5 days. Three days after the last irradiation day, samples of corneas and lenses were dissected. HR-MAS (1)H NMR spectroscopy combined with pattern recognition methods (principal component analysis and soft independent modelling of class analogy) and one-way ANOVA were applied to obtain metabolic information from intact corneal and lens tissue.

RESULTS

UVB irradiation caused statistically significant metabolic changes in the rabbit corneas. A decrease in metabolites as ascorbate (84%), myo-inositol (59%), hypotaurine (91%) and choline (76%) was observed. Exposure to UVA radiation caused no significant metabolic alteration in this tissue. The metabolic profile of the rabbit lenses showed no detectable changes after UVA or UVB exposure.

CONCLUSIONS

The combination of HR-MAS (1)H NMR spectroscopy and multivariate methods proved effective to analyse intact corneal and lens tissue after exposure to UV radiation of different wavelengths. By avoiding extraction methods and obtaining complete metabolic profiles from one sample, HR-MAS (1)H NMR spectroscopy provided important information about metabolic alteration occurring in rabbit corneal and lens tissue after UV exposure.

Effect of UV-A and UV-B Irradiation on the Metabolic Profile of Aqueous Humor in Rabbits Analyzed by 1H NMR Spectroscopy

PURPOSE

This study was conducted to investigate metabolic changes in aqueous humor from rabbit eyes exposed to either UV-A or -B radiation, by using (1)H nuclear magnetic resonance (NMR) spectroscopy and unsupervised pattern recognition

METHODS

methods. Both eyes of adult albino rabbits were irradiated with UV-A (366 nm, 0.589 J/cm(2)) or UV-B (312 nm, 1.667 J/cm(2)) radiation for 8 minutes, once a day for 5 days. Three days after the last irradiation, samples of aqueous humor were aspirated, and the metabolic profiles analyzed with (1)H NMR spectroscopy. The metabolic concentrations in the exposed and control materials were statistically analyzed and compared, with multivariate methods and one-way ANOVA.

RESULTS

UV-B radiation caused statistically significant alterations of betaine, glucose, ascorbate, valine, isoleucine, and formate in the rabbit aqueous humor. By using principal component analysis, the UV-B-irradiated samples were clearly separated from the UV-A-irradiated samples and the control group. No significant metabolic changes were detected in UV-A-irradiated samples.

CONCLUSIONS

This study demonstrates the potential of using unsupervised pattern recognition methods to extract valuable metabolic information from complex (1)H NMR spectra. UV-B irradiation of rabbit eyes led to significant metabolic changes in the aqueous humor detected 3 days after the last exposure.