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.

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 120 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells are associated with myeloid inflammation previously linked to androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

Reactive stroma is a tissue feature commonly observed in the tumor microenvironment of prostate cancer and has previously been associated with more aggressive tumors. The aim of this study was to detect differentially expressed genes and metabolites according to reactive stroma content measured on the exact same prostate cancer tissue sample. Reactive stroma was evaluated using histopathology from 108 fresh frozen prostate cancer samples gathered from 43 patients after prostatectomy (Biobank1). A subset of the samples was analyzed both for metabolic (n = 85) and transcriptomic alterations (n = 78) using high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) and RNA microarray, respectively. Recurrence-free survival was assessed in patients with clinical follow-up of minimum five years (n = 38) using biochemical recurrence (BCR) as endpoint. Multivariate metabolomics and gene expression analysis compared low (≤15%) against high reactive stroma content (≥16%). High reactive stroma content was associated with BCR in prostate cancer patients even when accounting for the influence of Grade Group (Cox hazard proportional analysis, p = 0.013). In samples with high reactive stroma content, metabolites and genes linked to immune functions and extracellular matrix (ECM) remodeling were significantly upregulated. Future validation of these findings is important to reveal novel biomarkers and drug targets connected to immune mechanisms and ECM in prostate cancer. The fact that high reactive stroma grading is connected to BCR adds further support for the clinical integration of this histopathological evaluation.

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+H ₂ O 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/mm ² . 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.

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.

Prostate tumor heterogeneity is a major obstacle when studying the biological mechanisms of molecular markers. Increased gene expression levels of secreted frizzled-related protein 4 (SFRP4) is a biomarker in aggressive prostate cancer. To understand how SFRP4 relates to prostate cancer we performed comprehensive spatial and multiomics analysis of the same prostate cancer tissue samples. The experimental workflow included spatial transcriptomics, bulk transcriptomics, proteomics, DNA methylomics and tissue staining. SFRP4 mRNA was predominantly located in cancer stroma, produced by fibroblasts and smooth muscle cells, and co-expressed with extracellular matrix components. We also confirmed that higher SFRP4 gene expression is associated with cancer aggressiveness. Gene expression of SFRP4 was affected by gene promotor methylation. Surprisingly, the high mRNA levels did not reflect SFRP4 protein levels, which was much lower. This study contributes previously unknown insights of SFRP4 mRNA in the prostate tumor environment that potentially can improve diagnosis and treatment.