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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.

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.

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.

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.

Renal cell carcinoma (RCC) ranks among the most prevalent malignancies in Western countries, marked by its notable heterogeneity, which contributes to an unpredictable clinical trajectory. The insufficiency of dependable biomarkers adds complexity to assessing this tumor progression. Imbalances of several components of the intrarenal renin–angiotensin system (iRAS) significantly impact patient prognoses and responses to first-line immunotherapies. In this study, we analyzed the immunohistochemical expression of the Mas-related G-protein-coupled receptor D (MrgD), which recognizes the novel RAS peptide alamandine (ALA), in a series of 87 clear cell renal cell (CCRCCs), 19 papillary (PRCC), 7 chromophobe (ChRCC) renal cell carcinomas, and 11 renal oncocytomas (RO). MrgD was expressed in all the renal tumor subtypes, with a higher mean staining intensity in the PRCCs, ChRCCs, and ROs. A high expression of MrgD at the tumor center and at the infiltrative front of CCRCC tissues was significantly associated with a high histological grade, large tumor diameter, local invasion, and locoregional node and distant metastasis. Patients with worse 5-year cancer-specific survival and a poorer response to antiangiogenic tyrosine-kinase inhibitors (TKIs) showed higher MrgD expression at the center of their primary tumors. These findings suggest a possible role of MrgD in renal carcinogenetic processes. Further studies are necessary to unveil its potential as a novel biomarker for CCRCC prognosis and response to frontline therapies.

Metabolic reprogramming is a hallmark of cancer, and the field has predominantly focused on investigating metabolic alterations in tumour cells. However, the relevance, mechanism and consequences of metabolic adaptations in stromal cells remain understudied. Here, we identify aspartoacylase (ASPA) as a metabolic enzyme consistently repressed in tumour stroma and cancer-associated fibroblasts (CAFs). Importantly, we report a reciprocal crosstalk between ASPA and Transforming Growth Factor Beta (TGFβ) signalling that influences fibroblast behaviour. TGFβ suppresses ASPA expression in fibroblasts, whereas ASPA restrains TGFβ-dependent myofibroblast conversion, extracelullar cell matrix (ECM) remodelling, angiogenesis and pro-tumoral macrophage phenotypes. Analyses of human specimens revealed a strong negative prognostic value for ASPA in different tumour types, associated with TGFβ signalling levels and the generation of aggressive pro-tumoral responses. Our findings unveil ASPA expression in fibroblasts as a gatekeeper of TGFβ responses and activation in cancer progression. Metabolic alterations in tumor stromal cells remain to be understood. Here the authors identify Aspartoacylase (ASPA) as a metabolic enzyme consistently repressed in cancer-associated fibroblasts (CAFs) across different cancer types, highlighting reciprocal negative regulation between ASPA and TGFβ signalling in governing CAF activation and cancer progression.

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.

Among the extensive genomic alterations in prostate cancer, the genomic deletion of PTEN stands out as one of the most consistently observed and confirmed alteration. PTEN loss in prostate tumors is primarily associated with cancer cell proliferation and survival through the activation of the PI3K-AKT-mTOR signalling pathway. However, its use as a robust biomarker in the clinical practice is hampered by the complex epigenetic, transcriptional and post-translational regulation. Here, we undertook an approach that combined in situ assessment of PTEN protein with transcriptional surrogates of its activity to gain insights into the downstream functional effects of PTEN loss in primary tumors. Our extensive bioinformatic analyses, including the integration with single-cell RNA-Seq approaches in a new clinical cohort, highlighted stroma remodeling as the major cancer cell-extrinsic process associated with PTEN loss. By applying similar computational strategy on the transcriptomic data generated from primary prostate tumors of genetically engineered Pten knock-out mouse models, we validated the causal role of Pten in the stromal reaction observed in clinical specimens. Mechanistically, we provide evidence for the activation of a paracrine program that encompasses enhanced TGF-β signalling and that is compatible with the secretome of PTEN-deficient senescent cancer cells. Our study provides relevant biological context to the cellular and molecular alterations unleashed upon PTEN protein loss.Competing Interest StatementThe authors have declared no competing interest.

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.

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