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

Abstract

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.

Keywords: 1H HRMAS NMR; Gleason score; Metabolomics; Prostate cancer; TMPRSS2-ERG.

Fig. 1

A flowchart depicting the outline of the study. Workflow and steps evolved for the metabolomic study conducted on tissue samples using ¹H HR MAS NMR, ¹H NMR, ³¹P NMR data and LC-MS (+/−) approaches are shown

Fig. 2

Tissue metabolomics multivariate analysis of prostate cancer. OPLS-DA score plots of benign samples (green dots) and malignant samples (brown dots) a. ¹H HR MAS NMR data, b. ¹H NMR data, c. ³¹P NMR data, d. LC-MS (+) data, e. LC-MS (−) data

Fig. 3

Tissue metabolomics multivariate analysis of Gleason scores. OPLS-DA score plots of Gleason score = 6 samples (orange dots) and Gleason score ≥ 7 samples (red dots) a. ¹H HR MAS NMR data, b. ¹H NMR data, c. ³¹P NMR data, d. LC-MS (+) data, e. LC-MS (−) data

Fig. 4

Metabolomics pathway network map of significantly altered metabolites in prostate cancer compared to benign prostate and additionally high Gleason score compared to low Gleason score. Metabolites significantly increased in PC are marked on red, significantly decreased in PC are marked on blue. Metabolites significantly increased and decreased in Gleason score ≥ 7 compared to Gleason score = 6 are represented by red and blue arrows, respectively

Fig. 5

Common significant metabolites discriminating malignant samples from benign samples and high Gleason score compared to low Gleason score. Box and whisker plots illustrating normalized intensities differences between benign samples (green box), PC Gleason score = 6 (yellow box) and PC Gleason score ≥ 7 (orange box)

Fig. 6

Tissue metabolomics multivariate analysis of ERG-positive PC and ERG-negative PC. a. OPLS-DA score plots of ERG-negative samples (bleu dots) and ERG-positive samples (red dots) of ¹H HR MAS NMR data, b. Plot obtained after performing a random permutation test with 200 permutations on OPLS-DA model of ¹H HR MAS NMR data, c. OPLS-DA score plots of ERG-negative samples (bleu dots) and ERG-positive samples (red dots) of LC-MS (+) data, d. Plot obtained after performing a random permutation test with 200 permutations on OPLS-DA model of LC-MS (+) data

Fig. 7

Combined proteomics and metabolomics pathway network map of significantly altered metabolites and proteins in ERG-positive prostate cancer compared to ERG-negative prostate cancer. Metabolites significantly increased in ERG-positive PC are marked on red, significantly decreased in ERG-positive PC are marked on blue. Significantly altered proteins are presented on box and whisker plots illustrating normalized intensities differences between benign samples (green box), ERG-negative PC (blue box) and ERG-positive PC (red box)