Urine contains extracellular vesicles (EVs) that concentrate molecules and protect them from degradation. Thus, isolation and characterisation of urinary EVs could increase the efficiency of biomarker discovery. We have previously identified proteins and RNAs with differential abundance in urinary EVs from prostate cancer (PCa) patients compared to benign prostate hyperplasia (BPH). Here, we focused on the analysis of the metabolites contained in urinary EVs collected from patients with PCa and BPH. Targeted metabolomics analysis of EVs was performed by ultra-high-performance liquid chromatography-mass spectrometry. The correlation between metabolites and clinical parameters was studied, and metabolites with differential abundance in PCa urinary EVs were detected and mapped into cellular pathways. We detected 248 metabolites belonging to different chemical families including amino acids and various lipid species. Among these metabolites, 76 exhibited significant differential abundance between PCa and BPH. Interestingly, urine EVs recapitulated many of the metabolic alterations reported in PCa, including phosphathidylcholines, acyl carnitines, citrate and kynurenine. Importantly, we found elevated levels of the steroid hormone, 3beta-hydroxyandros-5-en-17-one-3-sulphate (dehydroepiandrosterone sulphate) in PCa urinary EVs, in line with the potential elevation of androgen synthesis in this type of cancer. This work supports urinary EVs as a non-invasive source to infer metabolic changes in PCa.

(1) Background: Renal cancer is one of the most frequent malignancies in Western countries, with an unpredictable clinical outcome, partly due to its high heterogeneity and the scarcity of reliable biomarkers of tumour progression. (Pro)renin receptor (PRR) is a novel receptor of the renin-angiotensin system (RAS) that has been associated with the development and progression of some solid tumours by RAS-dependent and -independent mechanisms. (2) Methods: In this study, we analysed the immunohistochemical expression of PRR at the centre and border in a series of 83 clear-cell renal cell (CCRCCs), 19 papillary (PRCC) and 7 chromophobe (ChRCC) renal cell carcinomas, and the benign tumour renal oncocytoma (RO, n = 11). (3) Results: PRR is expressed in all the tumour subtypes, with higher mean staining intensity in ChRCCs and ROs. A high expression of PRR at the tumour centre and at the infiltrative front of CCRCC tissues is significantly associated with high grade, tumour diameter, local invasion and stage, and with high mortality risk by UCLA integrated staging system (UISS) scale. (4) Conclusions: These findings indicate that PRR is associated with the development and progression of renal tumours. Its potential as a novel biomarker for RCC diagnosis/prognosis and as a promising therapeutic target should be taken into account in the future.

Glycine N-Methyltransferase (GNMT) is a metabolic enzyme that integrates metabolism and epigenetic regulation. The product of GNMT, sarcosine, has been proposed as a prostate cancer biomarker. This enzyme is predominantly expressed in the liver, brain, pancreas, and prostate tissue, where it exhibits distinct regulation. Whereas genetic alterations in GNMT have been associated to prostate cancer risk, its causal contribution to the development of this disease is limited to cell line-based studies and correlative human analyses. Here we integrate human studies, genetic mouse modeling, and cellular systems to characterize the regulation and function of GNMT in prostate cancer. We report that this enzyme is repressed upon activation of the oncogenic Phosphoinositide-3-kinase (PI3K) pathway, which adds complexity to its reported dependency on androgen signaling. Importantly, we demonstrate that expression of GNMT is required for the onset of invasive prostate cancer in a genetic mouse model. Altogether, our results provide further support of the heavy oncogenic signal-dependent regulation of GNMT in prostate cancer.

Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique's spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.

Activation of the PTEN-PI3K-mTORC1 pathway consolidates metabolic programs that sustain cancer cell growth and proliferation. Here we show that mechanistic target of rapamycin complex 1 (mTORC1) regulates polyamine dynamics, a metabolic route that is essential for oncogenicity. By using integrative metabolomics in a mouse model and human biopsies of prostate cancer, we identify alterations in tumours affecting the production of decarboxylated S-adenosylmethionine (dcSAM) and polyamine synthesis. Mechanistically, this metabolic rewiring stems from mTORC1-dependent regulation of S-adenosylmethionine decarboxylase 1 (AMD1) stability. This novel molecular regulation is validated in mouse and human cancer specimens. AMD1 is upregulated in human prostate cancer with activated mTORC1. Conversely, samples from a clinical trial with the mTORC1 inhibitor everolimus exhibit a predominant decrease in AMD1 immunoreactivity that is associated with a decrease in proliferation, in line with the requirement of dcSAM production for oncogenicity. These findings provide fundamental information about the complex regulatory landscape controlled by mTORC1 to integrate and translate growth signals into an oncogenic metabolic program.

Prostate cancer is among the most frequent cancers in men, and despite its high rate of cure, the high number of cases results in an elevated mortality worldwide. Importantly, prostate cancer incidence is dramatically increasing in western societies in the past decades, suggesting that this type of tumor is exquisitely sensitive to lifestyle changes. Prostate cancer frequently exhibits alterations in the PTEN gene (inactivating mutations or gene deletions) or at the protein level (reduced protein expression or altered sub-cellular compartmentalization). The relevance of PTEN in this type of cancer is further supported by the fact that the sole deletion of PTEN in the murine prostate epithelium recapitulates many of the features of the human disease. In order to study the molecular alterations in prostate cancer, we need to overcome the methodological challenges that this tissue imposes. In this review we present protocols and methods, using PTEN as proof of concept, to study different molecular characteristics of prostate cancer.

The urea cycle (UC) is the main pathway by which mammals dispose of waste nitrogen. We find that specific alterations in the expression of most UC enzymes occur in many tumors, leading to a general metabolic hallmark termed "UC dysregulation" (UCD). UCD elicits nitrogen diversion toward carbamoyl-phosphate synthetase2, aspartate transcarbamylase, and dihydrooratase (CAD) activation and enhances pyrimidine synthesis, resulting in detectable changes in nitrogen metabolites in both patient tumors and their bio-fluids. The accompanying excess of pyrimidine versus purine nucleotides results in a genomic signature consisting of transversion mutations at the DNA, RNA, and protein levels. This mutational bias is associated with increased numbers of hydrophobic tumor antigens and a better response to immune checkpoint inhibitors independent of mutational load. Taken together, our findings demonstrate that UCD is a common feature of tumors that profoundly affects carcinogenesis, mutagenesis, and immunotherapy response.

Extracellular vesicles (EV) are emerging structures with promising properties for intercellular communication. In addition, the characterization of EV in biofluids is an attractive source of non-invasive diagnostic, prognostic and predictive biomarkers. Here we show that urinary EV (uEV) from prostate cancer (PCa) patients exhibit genuine and differential physical and biological properties compared to benign prostate hyperplasia (BPH). Importantly, transcriptomics characterization of uEVs led us to define the decreased abundance of Cadherin 3, type 1 (CDH3) transcript in uEV from PCa patients. Tissue and cell line analysis strongly suggested that the status of CDH3 in uEVs is a distal reflection of changes in the expression of this cadherin in the prostate tumor. CDH3 was negatively regulated at the genomic, transcriptional, and epigenetic level in PCa. Our results reveal that uEVs could represent a non-invasive tool to inform about the molecular alterations in PCa.

Urine sample analysis is irreplaceable as a non-invasive method for disease diagnosis and follow-up. However, in urine samples, non-degraded protein and RNA may be only found in urinary extracellular vesicles (uEVs). In recent years, various methods of uEV enrichment using low volumes of urine and unsophisticated equipment have been developed, with variable success. We compared the results of the differential ultracentrifugation procedure with 4 of these methods. The methods tested were a lectin-based purification, Exoquick (System Biosciences), Total Exosome Isolation from Invitrogen and an in-house modified procedure employing the Exosomal RNA Kit from Norgen Biotek Corp. The analysis of selected gene transcripts and protein markers of extracellular vesicles (EVs) revealed that each method isolates a different mixture of uEV protein markers. In our conditions, the extraction with Norgen's reagent achieved the best performance in terms of gene transcript and protein detection and reproducibility. By using this method, we were able to detect alterations of EVs protein markers in urine samples from prostate cancer adenoma patients. Taken together, our results show that the isolation of uEVs is feasible from small volumes of urine and avoiding ultracentrifugation, making easier the analysis in a clinical facility. However, caution should be taken in the selection of the enrichment method since they have a differential affinity for protein uEVs markers and by extension for different subpopulation of EVs.

Prostate cancer (PCa) is the second most common cancer of men and is typically slow-growing and asymptomatic. The use of blood PSA as a screening method has greatly improved PCa diagnosis, but high levels of false positives has raised much interest in alternative biomarkers. We used next-generation sequencing (NGS) to elucidate the urinary transcriptome of whole urine collected from high-stage and low-stage PCa patients as well as from patients with the confounding diagnosis of benign hyperplasia (BPH). We identified and validated five differentially expressed protein-coding genes (FTH1 BRPF1, OSBP, PHC3, and UACA) in an independent validation cohort of small-volume (1 mL) centrifuged urine (n = 94) and non-centrifuged urine (n = 84) by droplet digital (dd)PCR. These biomarkers were able to discriminate between BPH and PCa patients and healthy controls using either centrifuged or non-centrifuged whole urine samples, suggesting that the urinary transcriptome is a valuable source of non-invasive biomarkers for PCa that warrants further investigation.