Explore the vast range of titles available.

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.

Among the extensive genomic alterations in prostate cancer, phosphatase and tensin homolog (PTEN) deletion stands out as one of the most consistently observed events. PTEN loss in prostate tumors is primarily associated with cancer‐cell proliferation and survival through the activation of the phosphoinositide 3‐kinase (PI3K)—protein kinase B (AKT)—mechanistic target of rapamycin (mTOR) (PI3K–AKT–mTOR) signaling pathway. However, the use of PTEN as a robust biomarker in clinical practice is hampered by its complex epigenetic, transcriptional and post‐translational regulation. In situ protein assessment by immunohistochemistry (IHC) captures PTEN protein status, but it does not report on associated tumor microenvironment remodeling. Here, we undertook an approach that combined PTEN immunoreactivity analysis with high‐throughput transcriptional analysis to gain insights into the downstream functional effects of PTEN protein loss in primary tumors. Our extensive bioinformatic analyses highlighted stromal remodeling as a prominent cancer cell‐extrinsic process associated with PTEN loss. By extending our transcriptomic computational strategy to Pten loss‐driven murine prostate cancer, we validated the causal role of Pten in the stromal reaction observed in clinical specimens. Mechanistically, we provide experimental evidence for the activation of a paracrine program that encompasses enhanced transforming growth factor beta (TGF‐β) signaling and that is compatible with the secretome of PTEN‐deficient senescent cancer cells. Finally, our findings enable the sub‐stratification of tumors with PTEN loss based on their senescence‐associated stroma remodeling program to distinguish indolent from aggressive cases. Our study provides relevant biological context to the cellular and molecular alterations unleashed upon PTEN protein loss in prostate cancer. Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help stratify PTEN‐negative tumors according to clinical aggressiveness.

Clear cell renal cell carcinoma (ccRCC) is one of the most challenging neoplasms because of its phenotypic variability and intratumoral heterogeneity. Because of its variability, ccRCC is a good test bench for the application of new technological approaches to unveiling its intricacies. Multiplex immunofluorescence (mIF) is an emerging method that enables the simultaneous and detailed assessment of tumor and stromal cell subpopulations in a single tissue section. This novel approach represents a promising step forward for analyzing the microenvironmental cell composition and distribution across the tumor and understanding its possible interactions with tumor cells. This study provides the first characterization of the spatial distribution of fibroblast activation protein-α (FAP)-expressing cancer-associated fibroblasts (FAP + CAFs) in conjunction with lymphoid (CD4 + , CD8 + , CD4 + FOXP3 + , and CD20 +) and myeloid (CD68 +) cells in tissue sections from ccRCC in their early phases of evolution (n = 88). Both the tumor center and periphery were analyzed with mIF. FAP + CAFs and tumor-infiltrating lymphocytes (TILs) were significantly concentrated at the tumor periphery. Additionally, elevated percentages of FAP + CAFs were correlated with larger tumors and synchronous metastases. Increased levels of CD68 +  and CD4 + FOXP3 +  cells (above the 75th percentile) were linked to worse cancer-specific survival (CSS) in patients with ccRCC. Furthermore, significant correlations emerged among FAP + CAFs, TILs, and CD68 +  cells, and the co-occurrence of elevated FAP + CAFs, T-cytotoxic (CD8 +), T-regulatory (CD4 + FOXP3 +) cells, and macrophages (CD68 +) at the tumor center were independently associated with worse CSS. These findings suggest that FAP + CAFs contribute to the aggressiveness of ccRCC, and their role is potentially mediated by their ability to foster an immunosuppressive environment within the renal tumor microenvironment.

Background Metastatic hormone-naïve prostate cancer (mHNPC) is an infrequent form of this tumor type that is characterized by metastasis at the time of diagnosis and accounts for up to 50% of prostate cancer-related deaths. Despite the extensive characterization of localized and metastatic castration-resistant prostate cancer, the molecular characteristics of mHNPC remain largely unexplored. Results Here, we provide the first extensive transcriptomics characterization of primary tumor specimens from patients with mHNPC. We generate discovery and validation bulk and single-cell RNA-seq datasets and perform integrative computational analysis in combination with experimental studies. Our results provide unprecedented evidence of the distinctive transcriptional profile of mHNPC and identify stroma remodeling as a predominant feature of these tumors. Importantly, we discover a central role for the SRY-box transcription factor 11 (SOX11) in triggering a heterotypic communication that is associated with the acquisition of metastatic properties. Conclusions Our study will constitute an invaluable resource for a profound understanding of mHNPC that can influence patient management.

(1). Background: Immunohistochemical (IHC) evaluation of programmed death-1 (PD-1) and its ligand (PD-L1) is being used to evaluate advanced malignancies with potential response to immune checkpoint inhibitors. We evaluated both plasma and tissue expression of PD-1 and PD-L1 in the same cohort of patients, including non-metastatic and metastatic clear cell renal cell carcinoma (CCRCC). Concomitant plasma and tissue expression of PD-1 and PD-L1 was evaluated with emphasis on diagnostic and prognostic implications. (2) Methods: we analyzed PD-1 and PD-L1 IHC expression in tumor tissues and soluble forms (sPD-1 and sPD-L1) in plasma from 89 patients with CCRCC, of which 23 were metastatic and 16 received systemic therapy. The primary endpoint was evaluation of overall survival using Kaplan-Meier analysis and the Cox regression model. Plasma samples from healthy volunteers were also evaluated. (3) Results: Interestingly, sPD-1 and sPD-L1 levels were lower in cancer patients than in controls. sPD-1 and sPD-L1 levels and their counterpart tissue expression both at the tumor center and infiltrating front were not associated. Higher expression of both PD-1 and PD-L1 were associated with tumor grade, necrosis and tumor size. PD-1 was associated to tumor stage (pT) and PD-L1 to metastases. sPD-1 and sPD-L1 were not associated with clinico-pathological parameters, although both were higher in patients with synchronous metastases compared to metachronous ones and sPD-L1 was also higher for metastatic patients compared to non-metastatic patients. sPD-1 was also associated with the International Metastatic Renal Cell Cancer Database Consortium (IMDC) prognostic groups in metastatic CCRCC and also to the Morphology, Attenuation, Size and Structure (MASS) response criteria in metastatic patients treated with systemic therapy, mainly tyrosine-kinase inhibitors. Regarding prognosis, PD-L1 immunostaining at the tumor center with and without the tumor front was associated with worse survival, and so was sPD-L1 at a cut-off >793 ng/mL. Combination of positivity at both the tissue and plasma level increased the level of significance to predict prognosis. (4) Conclusions: Our findings corroborate the role of PD-L1 IHC to evaluate prognosis in CCRCC and present novel data on the usefulness of plasma sPD-L1 as a promising biomarker of survival in this neoplasia.

Background Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner. Methods We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples. Results We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920–0.952, p < 0.001). MetSCORE is also able to discriminate the intermediate phenotypes, identifying the early risk of MetS in a quantitative way and ranking individuals according to their risk of undergoing MetS (for general population) or according to the severity of the syndrome (for MetS patients). Conclusions We believe that MetSCORE may be an insightful tool for early intervention and lifestyle modifications, potentially preventing the aggravation of metabolic syndrome.

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.

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.

(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.

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.