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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.

Newly growing evidence highlights the essential role that epitranscriptomic marks play in the development of many cancers; however, little is known about the role and implications of altered epitranscriptome deposition in prostate cancer. Here, we show that the transfer RNA N 7 -methylguanosine (m 7 G) transferase METTL1 is highly expressed in primary and advanced prostate tumours. Mechanistically, we find that METTL1 depletion causes the loss of m 7 G tRNA methylation and promotes the biogenesis of a novel class of small non-coding RNAs derived from 5'tRNA fragments. 5'tRNA-derived small RNAs steer translation control to favour the synthesis of key regulators of tumour growth suppression, interferon pathway, and immune effectors. Knockdown of Mettl1 in prostate cancer preclinical models increases intratumoural infiltration of pro-inflammatory immune cells and enhances responses to immunotherapy. Collectively, our findings reveal a therapeutically actionable role of METTL1-directed m 7 G tRNA methylation in cancer cell translation control and tumour biology.

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.

Bladder cancer is one of the most common cancers and, together with prostate carcinoma, accounts for the majority of the malignancies of the genitourinary tract. Since prognosis ameliorates with early detection, it will be beneficial to have a repertoire of diagnostic markers that could complement the current diagnosis protocols. Recently, cell-secreted extracellular vesicles have received great interest as a source of low invasive disease biomarkers because they are found in many body fluids, including urine. The current work describes a pilot study to generate an array-based catalogue of mRNA associated to urinary vesicles, and also a comparison with samples obtained from bladder cancer patients. After an analysis of presence/absence of transcripts in bladder cancer EVs, a list of genes was selected for further validation using PCR technique. We found four genes differentially expressed in cancer samples. LASS2 and GALNT1 were present in cancer patients, while ARHGEF39 and FOXO3 were found only in non-cancer urinary vesicles. Previous studies have pointed to the involvement of those genes in tumour progression and metastasis.

The dysregulation of gene expression is an enabling hallmark of cancer. Computational analysis of transcriptomics data from human cancer specimens, complemented with exhaustive clinical annotation, provides an opportunity to identify core regulators of the tumorigenic process. Here we exploit well-annotated clinical datasets of prostate cancer for the discovery of transcriptional regulators relevant to prostate cancer. Following this rationale, we identify Microphthalmia-associated transcription factor (MITF) as a prostate tumor suppressor among a subset of transcription factors. Importantly, we further interrogate transcriptomics and clinical data to refine MITF perturbation-based empirical assays and unveil Crystallin Alpha B (CRYAB) as an unprecedented direct target of the transcription factor that is, at least in part, responsible for its tumor-suppressive activity in prostate cancer. This evidence was supported by the enhanced prognostic potential of a signature based on the concomitant alteration of MITF and CRYAB in prostate cancer patients. In sum, our study provides proof-of-concept evidence of the potential of the bioinformatics screen of publicly available cancer patient databases as discovery platforms, and demonstrates that the MITF-CRYAB axis controls prostate cancer biology.

Urine extracellular vesicles are a valuable low-invasive source of information, especially for the cells of the genitourinary tract. In the search for biomarkers, different techniques have been developed to isolate and characterize the cargo of these vesicles. In the present work, we compare five of these different isolation methods (three commercial isolation kits, ultracentrifugation, and lectin-based purification) and perform miRNA profiling using a multiplex miRNA assay. The results showed high correlation through all isolation techniques, and 48 out of 68 miRNAs were detected above the detection limit at least 10 times. The results obtained by multiplex assay were validated through Taqman qPCR. In addition, using this technique combined with a clinically friendly extracellular vesicle (uEV)-enrichment method, we performed the analysis of selected miRNAs in urine from patients affected with bladder cancer, benign prostate hyperplasia, or prostate cancer. Importantly, we found that those miRNAs could be detected in almost 100% of the samples, and no significant differences were observed between groups. Our results support the feasibility of analyzing exosomes-associated miRNAs using a methodology that requires a small volume of urine and is compatible with a clinical environment and high-throughput analysis.

mTOR complex 1 signalling regulates polyamine metabolism and thereby promotes tumorigenesis, through regulation of the stability of a key enzyme, AMD1. Cell proliferation in prostate cancer The mTOR pathway regulates multiple metabolic pathways in cancers but knowledge of how oncogenic signals regulate polyamine production, which is important in spreading cancer cells, is limited. Arkaitz Carracedo and colleagues add to the existing knowledge. Using a mixture of metabolic analysis techniques, they show that mTOR signalling regulates polyamine metabolism and thereby promotes tumorigenesis through regulation of the stability of a key enzyme, AMD1. They validated this pathway in mouse and human cancer specimens and found that ADM1 is upregulated in prostate cancer specimens with activated mTORC1. This adds to the complexity of cancer cell metabolism and offers new therapeutic avenues. Activation of the PTEN–PI3K–mTORC1 pathway consolidates metabolic programs that sustain cancer cell growth and proliferation 1 , 2 . 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 3 and human biopsies 4 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 5 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.

Cellular transformation and cancer progression is accompanied by changes in the metabolic landscape. Master co-regulators of metabolism orchestrate the modulation of multiple metabolic pathways through transcriptional programs, and hence constitute a probabilistically parsimonious mechanism for general metabolic rewiring. Here we show that the transcriptional co-activator peroxisome proliferator-activated receptor gamma co-activator 1α (PGC1α) suppresses prostate cancer progression and metastasis. A metabolic co-regulator data mining analysis unveiled that PGC1α is downregulated in prostate cancer and associated with disease progression. Using genetically engineered mouse models and xenografts, we demonstrated that PGC1α opposes prostate cancer progression and metastasis. Mechanistically, the use of integrative metabolomics and transcriptomics revealed that PGC1α activates an oestrogen-related receptor alpha (ERRα)-dependent transcriptional program to elicit a catabolic state and metastasis suppression. Importantly, a signature based on the PGC1α–ERRα pathway exhibited prognostic potential in prostate cancer, thus uncovering the relevance of monitoring and manipulating this pathway for prostate cancer stratification and treatment. Torrano et al.  use bioinformatics analyses to identify PGC1α as a transcriptional regulator of a metabolic program downstream of ERRα that opposes metastatic dissemination in prostate cancer.

Background: Metabolomics is an omics discipline with high potential to identify new biomarkers, but it is limited to metabolites, lacking of information on the context and/or integration into metabolic pathways. Previously, using metabolomics data obtained from urine EVs, we identified altered metabolites between prostate cancer (PCa) patients and benign hyperplasia (BPH) patients. In the current work, we developed a bioinformatics workflow to identify gene-encoding proteins involved in the metabolism of those metabolites and to map them into metabolic pathways. Using publicly available, gene expression for prostate cancer datasets, we identified several genes which regulation was altered, in agreement with the alterations observed at the metabolite level. Methods: R scripts were developed for retrieving information from KEGG and HMDB database, specifically, enzymes and genes related to the metabolites of interest. Combining both genes and metabolites lists, the script searched for metabolic pathway that could be altered. Finally, gene expression data was analysed in available databases for those genes of interest. Results: We detected 76 metabolites that were significantly different between prostate cancer and benign prostate hyperplasia. We identified 149 enzymes involved in the metabolism of those metabolites. From them, the levels of their encoding genes were evaluated in the PCa gene expression data sets. As a result, the levels of 7 gene-encoding enzymes were found altered in PCa and were in concordance with the metabolite levels observed in urinary EVs. Our results indicate that steroid hormones, leukotriene and prostaglandin, linoleate, glycerophospholipid and tryptophan metabolisms and urea and TCA cycles, are altered in PCa. Summary/conclusion: In this work, we demonstrated that bioinformatics tools applied for combining of metabolomics and gene expression data are able to identify metabolic pathways that help to explain the metabolic phenotype of PCa, and provide novel therapeutics targets. This work also supports the study of urinary EVs as surrogate metabolic non-invasive markers for PCa tissue metabolism.

Artificially induced translocation stocks have been used to physically map the barley genome; however, natural translocations are extremely uncommon in cultivated genotypes. Albacete is a barley variety widely grown in recent decades in Spain and carrying a reciprocal translocation which obviously does not affect its agronomical fitness. This translocation has been characterized by a combination of cytological and molecular genetic approaches. Firstly, recombination frequencies between markers on chromosomes 1H and 3H were estimated to determine the boundaries of the reciprocal interchange. Secondly, 1H-3H wheat barley telosome addition lines were used to assign selected markers to chromosome arms. Thirdly, fluorescence in situ hybridization (FISH) with rDNA probes (5S and 18S-5.8S-26S) and microsatellite probes [(ACT)(5), (AAG)(5) and (CAG)(5)] was used to determine the locations of the translocation breakpoints more precisely. Fourthly, fine-mapping of the regions around the translocation breakpoints was used to increase the marker density for comparative genomics. The results obtained in this study indicate that the translocation is quite large with breakpoints located on the long arms of chromosomes 1H and 3H, between the pericentromeric (AAG)(5) bands and above the (ACT)(5) interstitial distal bands, resulting in the reciprocal translocation 1HS.1HL-3HL and 3HS.3HL-1HL. The gene content around the translocation breakpoints could be inferred from syntenic relationships observed among different species from the grass family Poaceae (rice, Sorghum and Brachypodium) and was estimated at approximately 1,100 and 710 gene models for 1H and 3H, respectively. Duplicated segments between chromosomes Os01 and Os05 in rice derived from ancestral duplications within the grass family overlap with the translocation breakpoints on chromosomes 1H and 3H in the barley variety Albacete