Kirsten Margrete Selnæs

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.

Peripheral zone prostate cancer localization by multiparametric magnetic resonance at 3 T: unbiased cancer identification by matching to histopathology.

ObjectivesThe aim of this study was to assess the diagnostic accuracy of peripheral zone prostate cancer localization by multiparametric magnetic resonance (MR) at 3 T using segmental matching of histopathology and MR images to avoid bias by image features in selection of cancer and noncancer regions. Materials and MethodsForty-eight patients underwent multiparametric MR imaging (MRI) on a 3 T system using a phased array body coil and spine coil elements for signal detection before prostatectomy. The examination included T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), dynamic contrast-enhanced imaging (DCE-MRI), and MR spectroscopic imaging (MRSI). Histopathology slides were correlated to T2W images and a stringent matching procedure was performed to define cancer and noncancer areas of the peripheral zone without influence of the MR image appearance. Mean T2W signal intensity, apparent diffusion coefficient, area under the enhancement curve, and choline + creatine-to-citrate signal ratio were calculated for cancer and noncancer areas. Receiver operating characteristic (ROC) analysis was performed on MR-derived parameters from the selected areas. Logistic regression was used to create models based on best combination of parameters. A simplified approach assigning a parametric score to each segment based on cutoff values from ROC analysis was also explored. ResultsBy using the stringent matching procedure, 138 noncancer and 41 cancer segments were selected in the T2W images and transferred to the images of the other MR methods. A significant difference between mean values in cancer and noncancer segments was observed for all MR parameters analyzed (P < 0.001). Apparent diffusion coefficient was the best performing single parameter, with an area under the ROC curve Az,DWI of 0.90 for prostate cancer detection. Any combination of T2WI, DWI, and DCE-MRI was significantly better than T2WI alone in separating cancer from noncancer segments (Az,T2WI + DWI + DCE-MRI = 0.94, Az,T2WI + DWI = 0.92, Az,T2WI + DCE-MRI = 0.91, Az,T2WI = 0.85). The combination of T2WI and MRSI was also better than T2WI alone (Az, T2WI + MRSI = 0.90); however, the logistic regression models including MRSI did not have significant parameters. The simplified approach combining all parameters gave similar results to logistic regression combining all parameters (Az = 0.95 and 0.97, respectively). ConclusionBy selecting histopathology defined cancer and noncancer areas without influence of image contrast, this study objectively reveals that all investigated MR parameters have the ability to separate cancer from noncancer areas in the peripheral zone individually and that any combination is better than T2WI alone.

Discrimination of Patients with Microsatellite Instability Colon Cancer using 1H HR MAS MR Spectroscopy and Chemometric Analysis

The primary aim of this study was to analyze human colon cancer and normal adjacent tissue using (1)H HR MAS MR spectroscopy and chemometric analyses, evaluating possible biomarkers for colon cancer. The secondary aim was to investigate metabolic profiles of tissue samples (n = 63, 31 patients) with microsatellite instability (MSI-H) compared to microsatellite stable (MSS) colon tissue. Our hypothesis was that this method may provide an alternative to MSI genotyping. Cancer samples were clearly separated from normal adjacent mucosa by 100% accuracy. Several metabolites such as lactate, taurine, glycine, myo-inositol, scyllo-inositol, phosphocholine (PC), glycerophosphocholine (GPC), creatine, and glucose were identified as potential biomarkers for cancer detection. Adenomas (n = 4) were also separated from cancer and normal samples mainly based on higher GPC and PC levels. Interestingly, metabolic differences in normal colon mucosa between MSI-H and MSS patients were observed. MSI status was validated with 80% accuracy with a sensitivity and specificity of 79% and 82%, respectively, including both cancer and normal samples The metabolic differences between MSI-H and MSS may be very interesting in the early detection of cancer development and of high clinical importance in the work of improving diagnosis and characterization of colon cancer.

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results

AbstractPurposeTo evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers.Materials and Methods3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (Ktrans and Ve) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically.ResultsASM and entropy correlated significantly (p < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The textural features correlated insignificantly with Ktrans and Ve. GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, Ktrans, and Ve. The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets.ConclusionT2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers.Key Points• T2W MRI-derived textural features correlate significantly with Gleason score and ADC. • T2W MRI-derived textural features differentiate Gleason score 3+4 from 4+3 cancers. • T2W image textural features could augment tumour characterization.

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. Spearmans 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. Copyright

A novel non-canonical Wnt signature for prostate cancer aggressiveness

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

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

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

A PET/MRI study towards finding the optimal [18F]Fluciclovine PET protocol for detection and characterisation of primary prostate cancer

Purpose[18F]Fluciclovine PET imaging shows promise for the assessment of prostate cancer. The purpose of this PET/MRI study is to optimise the PET imaging protocol for detection and characterisation of primary prostate cancer, by quantitative evaluation of the dynamic uptake of [18F]Fluciclovine in cancerous and benign tissue.MethodsPatients diagnosed with high-risk primary prostate cancer underwent an integrated [18F]Fluciclovine PET/MRI exam before robot-assisted radical prostatectomy with extended pelvic lymph node dissection. Volumes-of-interest (VOIs) of selected organs (prostate, bladder, blood pool) and sub-glandular prostate structures (tumour, benign prostatic hyperplasia (BPH), inflammation, healthy tissue) were delineated on T2-weighted MR images, using whole-mount histology samples as a reference. Three candidate windows for optimal PET imaging were identified based on the dynamic curves of the mean and maximum standardised uptake value (SUVmean and SUVmax, respectively). The statistical significance of differences in SUV between VOIs were analysed using Wilcoxon rank sum tests (p<0.05, adjusted for multiple testing).ResultsTwenty-eight (28) patients [median (range) age: 66 (55-72) years] were included. An early (W1: 5-10 minutes post-injection) and two late candidate windows (W2: 18-23; W3: 33-38 minutes post-injection) were selected. Late compared with early imaging was better able to distinguish between malignant and benign tissue [W3, SUVmean: tumour vs. BPH 2.5 vs. 2.0 (p<0.001), tumour vs. inflammation 2.5 vs. 1.7 (p<0.001), tumour vs. healthy tissue 2.5 vs. 2.0 (p<0.001); W1, SUVmean: tumour vs. BPH 3.1 vs. 3.1 (p=0.771), tumour vs inflammation 3.1 vs. 2.2 (p=0.021), tumour vs. healthy tissue 3.1 vs. 2.5 (p<0.001)] as well as between high-grade and low/intermediate-grade tumours (W3, SUVmean: 2.6 vs. 2.1 (p=0.040); W1, SUVmean: 3.1 vs. 2.8 (p=0.173)). These differences were relevant to the peripheral zone, but not the central gland.ConclusionLate-window [18F]Fluciclovine PET imaging shows promise for distinguishing between prostate tumours and benign tissue and for assessment of tumour aggressiveness.

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.