Clinical Implications of (Pro)renin Receptor (PRR) Expression in Renal Tumours

(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.The work was funded by the Basque Government (ELKARTEK KK2018-00090 and KK-2020/00069)

Soluble PD-L1 Is an Independent Prognostic Factor in Clear Cell Renal Cell Carcinoma

(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.The work was funded by the Basque Government (ELKARTEK KK2018-00090 and KK-2020/00069)

Metabolic alterations in urine extracellular vesicles are associated to prostate cancer pathogenesis and progression

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 ultrahigh- 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.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 ultrahigh- 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

Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma

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.The work was funded by the Basque Government (IT971-16, IT1162-19, and ELKARTEK KK2018-00090) and has been developed as a Ph.D. project of LMS, who is the recipient of a Predoctoral Fellowship from the Spanish Government (BES- 2016-078721) . The authors are grateful to SGiker Lipidomic Service (UPV/EHU, MICINN, GV/EG, ESF) for the expert advice and technical and human support in MALDI and HPLC- MS analysis

Integrative analysis of transcriptomics and clinical data uncovers the tumor- suppressive activity of MITF in prostate cancer

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

Transcriptomic profiling of urine extracellular vesicles reveals alterations of CDH3 in prostate cancer

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

PI3K-regulated Glycine N-methyltransferase is required for the development of prostate cancer

[EN] 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.We are grateful to the Carracedo lab for valuable input, to Drs. Ana M. Aransay, James D. Sutherland and F. Elortza for technical advice, and Drs. Michelle Clasquin, Katie Sellers and Katya Marjon at Agios Pharmaceuticals for performing, processing and analyzing the metabolomics experiments. We thank the Basque Biobank for Research (BIOEF) for the support with prostate specimen acquisition and management. A.A-A. was funded by the Basque Government (predoctoral fellowship). V.T. is funded by Fundación Vasca de Innovación e Investigación Sanitarias, BIOEF (BIO15/CA/052), the AECC J.P. Bizkaia, the Basque Department of Health (2016111109) and the MICINN RTI2018-097267-B-I00. I.M. is supported by Fundación Cris Contra el Cáncer (PR_TPD_2020-19). The work of A. Carracedo is supported by the Basque Department of Industry, Tourism and Trade (Elkartek), the department of education (IKERTALDE IT1106-16) and health (RIS3), the BBVA foundation, the MICINN (SAF2016-79381-R; PID2019-108787RB-I00 (FEDER/EU); Severo Ochoa Excellence Accreditation SEV-2016-0644; Excellence Networks RED2018-102769-T), the AECC (GCTRA18006CARR), Vencer el Cáncer Foundation, La Caixa Foundation (ID 100010434), under the agreement LCF/PR/HR17/ and the European Research Council (Starting Grant 336343, PoC 754627, Consolidator Grant 819242). CIBERONC was co-funded with FEDER funds and funded by ISCIII. We are grateful for the support of Mondravember and Movembergara. A.E. was supported by MCIN/AEI/10.13039/501100011033 and the EU programme NextGenerationEU/PRTR (IJC2020-043583-I). The work of JM Mato was supported by NIH grant R01CA172086 and SAF2017-88041-R. EB is funded by the MICINN (BFU2016-76872-R (FEDER/EU), PID2019-108112RB-I00, and Excellence Networks SAF2017-90794-REDT)

The metabolic co-regulator PGC1α suppresses prostate cancer metastasis

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