Search Results (141)

Background: Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer subtype and, in most cases, it is incidentally diagnosed, as early-stage disease is often asymptomatic. Therefore, the identification of stable, noninvasive biomarkers is a major unmet clinical need. Urinary microRNAs (miRNAs) have emerged as promising candidates since they are extraordinarily stable in urine and show a close relationship with tumour biology. Methods: In this study, urinary expression levels of five miRNAs (miR-15a, miR-15b, miR-16, miR-210, and miR-let-7b) were analysed in RCC patients before surgery, 5 days after, and one month after surgery, and compared to healthy controls. Results: Non-parametric analyses revealed significant postoperative decreases for miR-15a (p = 0.002), miR-16 (p = 0.025), miR-210 (p = 0.030), and in the overall miRNA Sum (p = 0.002), suggesting that these miRNAs are directly linked to tumour presence. In the comparison between preoperative and one-month postoperative samples, miR-let-7b (p = 0.049) and the global miRNA Sum (p = 0.037) remained significantly reduced after intervention, indicating a partial normalisation of urinary miRNA profiles. Correlation analyses demonstrated positive associations between specific miRNAs and clinical parameters such as age, ischemia time, and surgical time, reinforcing their potential relevance to tumour biology and treatment response. Conclusions: These findings support urinary miRNAs as promising, minimally invasive biomarkers for ccRCC diagnosis and postoperative monitoring. Full article

Introduction: Radiotracer-based nuclear imaging, including positron emission tomography (PET) and single-photon emission computed tomography (SPECT), can complement conventional cross-sectional imaging in renal cell carcinoma (RCC) by providing biological characterisation of tumour metabolism, angiogenesis, hypoxia, and the tumour microenvironment. While computed tomography (CT) and magnetic resonance imaging (MRI) remain the diagnostic standard, accumulating evidence suggests that selected nuclear imaging techniques may offer incremental value in specific clinical scenarios. Methods: A narrative literature review was performed using PubMed, Embase, and Web of Science to identify preclinical, retrospective, and prospective studies evaluating PET and SPECT radiotracers in localised and metastatic RCC. Priority was given to meta-analyses, multicentre prospective trials, and studies with histopathological correlation. Results: [¹⁸F]fluorodeoxyglucose (FDG) PET/CT demonstrates limited sensitivity for primary renal tumours (pooled sensitivity of approximately 60%) but performs substantially better in metastatic and recurrent disease (pooled sensitivity and specificity of approximately 85–90%), where uptake correlates with tumour grade, progression-free survival, and overall survival. [^99mTc]sestamibi SPECT/CT differentiates oncocytoma and hybrid oncocytic/chromophobe tumours from malignant RCC with pooled sensitivity and specificity of around 85–90%, supporting its role in evaluating indeterminate renal masses rather than staging. Prostate-specific membrane antigen (PSMA) PET/CT shows high detection rates in clear-cell RCC, particularly in metastatic disease, with reported sensitivities of approximately 85–90% and management changes in up to 40–50% of selected cohorts. Carbonic anhydrase IX (CAIX)-targeted PET/CT enables the biologically specific visualisation of clear-cell RCC, achieving sensitivities and specificities in the range of 85–90% in prospective phase II and III trials for primary tumour characterisation. Fibroblast activation protein inhibitor (FAPI) PET/CT demonstrates high tumour-to-background uptake in early RCC studies, but evidence remains preliminary, with small cohorts and recognised non-specific uptake in benign inflammatory and fibrotic conditions. Conclusions: Radiotracer-based nuclear imaging provides complementary, biology-driven insights in RCC that extend beyond anatomical assessment. While most modalities remain adjunctive or investigational and are not recommended for routine use, selective application in carefully chosen clinical scenarios may enhance tumour characterisation, prognostication, and personalised treatment planning. Full article

Clear cell renal cell carcinoma is the most common histological type of renal cancer, which is a common cancer type usually associated with a long clinical course. During this course, various metastatic sites can be observed. In this review, we have focused on metastases to the thyroid gland. We conducted research in three medical databases, including PubMed, Scopus, and Web of Science, using the same search algorithm. Our inclusion criteria focused on case reports and case series studies since 2011, covering therapeutic strategies for the primary and/or metastatic disease, as well as subsequent follow-up data. Studies with insufficient or uncertain data, or written in a language other than English, were excluded. An analysis of 510 articles from PubMed, 1729 from Scopus, and 649 from Web of Science, after application of inclusion and exclusion criteria, resulted in 77 reports, analyzing 189 patients. A description of the clinical, pathological, ancillary, and follow-up data, in the light of recent therapeutic schemes, was attempted. Our results suggest that metastases’ imaging features comprised more commonly a solitary nodule with a median size of 3.5 cm and worrisome features in ultrasonography, such as heterogeneity, hypoechogenicity, partially solid configuration, and variable internal vascularization. Histological and immunohistochemical examination of the lesion is necessary because these findings are not specific. Common non-thyroid metastases are seen in the urogenital system, lungs, and pancreas. We calculated the restricted mean survival from primary diagnosis at 274.6 months (95% CI: 264.3–285.0 months) and the restricted mean survival from thyroid metastases treatment at 93.9 months (95% CI: 65.3–122.4 months). Results regarding how patient characteristics affect these survival numbers were statistically nonsignificant (p > 0.05). Full article

Chromophobe renal cell carcinoma (chRCC) is a distinct subtype of non–clear cell renal cell carcinoma (ncRCC), arising from intercalated cells of the distal nephron collecting ducts. No standard treatments are specifically approved for chRCC, which is further hindered by lack of a universally accepted grading system. This study sought to find molecular drivers that may aid in the diagnosis or development of treatments for chRCC. A retrospective analysis of chRCC was conducted using data from the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) repository, accessed through cBioPortal (version 17.0-public) on 21 July 2025. The study examined recurrent somatic mutations and assessed co-occurrence with Benjamini–Hochberg False Discovery Rate (FDR) correction. Additional analyses evaluated mutation by sex and race, with significance set at p < 0.05. The cohort included 180 tumor samples from 170 chRCC patients. Most patients were adults (n = 167, 98.2%) and White (n = 115, 67.6%). Recurrent alterations occurred in genes part of the p53, PI3K/mTOR, Hippo, and NOTCH signaling pathway. Exploratory demographic analyses identified isolated single-patient mutations in select genes across sex and race; however, these rare events are not interpretable as population-level differences. This study provides a comprehensive genomic profile of chRCC across multiple demographic categories. Full article

FDG PET/CT often underperforms in characterizing hyper-enhancing, FDG-non-avid renal masses. We present two cases illustrating the potential of ⁶⁸Ga-NY104, a novel small-molecule tracer targeting carbonic anhydrase IX (CAIX), for this differential diagnosis. Both patients presented with a hyper-enhancing right renal mass suspicious for clear cell renal carcinoma (ccRCC) and subsequently underwent both ¹⁸F-FDG and ⁶⁸Ga-NY104 PET/CT, with histopathology and CAIX immunohistochemistry (IHC) as the reference standard. On ¹⁸F-FDG, both lesions were non-avid (SUVmax 2.6 and 2.2, Tumor-to-Liver Ratio [TLR] 0.87 and 0.69, respectively). However, on ⁶⁸Ga-NY104 PET/CT, Patient 1 (a 65-year-old man) showed intense, homogeneous uptake (SUVmax 26.0, TLR 4.64), while Patient 2 (a 67-year-old woman) showed negligible uptake (SUVmax 2.5, TLR 0.68). It was consistent with histopathology and IHC results that Patient 1 was CAIX-positive ccRCC, while Patient 2 was CAIX-negative hemangioma. Our preliminary cases suggest the potential utility of CAIX-targeted PET/CT imaging with ⁶⁸Ga-NY104 in differentiating ccRCC from benign mimickers like renal hemangioma, which warrants further prospective evaluation. Full article

Non-clear cell renal cell carcinoma (nccRCC) constitutes a biologically diverse category of renal malignancies. The 2022 WHO classification framework has significantly evolved to incorporate molecularly defined entities alongside traditional histologic subtypes, reflecting the growing recognition of distinct pathogenic drivers. Current therapeutic paradigms for advanced disease remain suboptimal, with treatment strategies often extrapolated from clear cell renal cell carcinoma (ccRCC). In this review, we highlight transformative multi-omics approaches to address nccRCC’s profound heterogeneity, which enables molecular stratification beyond conventional pathology, identifying novel subtypes characterized by unique immune microenvironment features, metabolic profiles, and genomic instability patterns. This molecular reclassification provides a foundational framework for precision oncology, facilitating patient selection for targeted therapies and immunomodulatory strategies. Advancements in multi-omics subtyping represent a pivotal shift toward biologically guided clinical management and underscore the imperative for biomarker-driven therapeutic development in nccRCC. Full article

Background: Artificial intelligence (AI) has the potential to significantly enhance clinical decision-making in oncology. However, its application in renal cell carcinoma (RCC) remains limited. The ART (Artificial Intelligence in Renal Tumors) project is a Spanish, multi-institutional initiative aimed at developing a dynamic, transcriptomics-based AI model to guide systemic treatment decisions for patients with metastatic RCC (mRCC). Objective: The aim of this paper is to present the rationale, methodology, and early implementation challenges of the ART project, as discussed during a dedicated Think Tank session at the 2025 International Kidney Cancer Symposium Europe (IKCSEU25), and to gather expert insights on its clinical and regulatory viability. Design, Setting, and Participants: The ART project includes three phases: (1) retrospective algorithm training using clinical and transcriptomic data from completed trials; (2) a prospective, non-interventional study collecting multi-omic and clinical data from 500 patients across 30 centers; and (3) a future comparative analysis of ART-guided versus standard clinical decisions. The AI model is designed to evolve continuously through ongoing data integration. Results and Limitations: Experts underscored the importance of integrating multimodal data—including circulating biomarkers and immune profiling—while expressing concerns about the reliance on short-term endpoints. Key barriers identified included data harmonization, external validation, and regulatory uncertainty regarding adaptive algorithms. The absence of a clear approval pathway for non-static clinical decision support systems also poses a challenge. Despite limited initial funding, the ART platform has generated strong institutional engagement and may serve as a scalable model for clinician-oriented AI tools. Conclusions: The ART project represents an innovative approach to AI-driven personalization of kidney cancer treatment. Expert feedback from IKCSEU25 highlighted the scientific robustness of the initiative, while also emphasizing the need for broader validation, regulatory clarity, and the use of clinically meaningful endpoints to support real-world implementation. Patient Summary: Experts reviewed a new AI-based tool being developed in Spain to help doctors choose the best treatments for kidney cancer. The tool shows promise but needs further testing and must meet regulatory standards before it can be used in routine clinical care. Full article

Objectives: Cancer, characterized by its profound complexity and heterogeneity, arises from a multitude of molecular disruptions. The pursuit of identifying distinct cancer subtypes is driven by the need to stratify patients into clinically coherent subgroups, each exhibiting unique prognostic outcomes. The integration of multi-omics datasets enhances the precision of subtyping and advances precision medicine. Methods: Considering the high-dimensional nature inherent to various multi-omics data types, we introduce an innovative deep learning framework, DAE-MKL, which integrates denoising autoencoders with multi-kernel learning for identifying cancer subtypes. Leveraging the capabilities of DAE, we extract non-linearly transformed features that retain pertinent information while mitigating noise and redundancy. These refined data representations are then funneled into the MKL framework, thereby enhancing the accuracy of subtype identification. We applied the DAE-MKL framework to both simulated studies and empirical datasets derived from two distinct cancer types, low-grade glioma (LGG, $n$ = 86) and kidney renal clear cell carcinoma (KIRC, $n$ = 285), thereby validating its utility and feasibility. Results: In simulations, DAE-MKL achieved superior performance with NMI gains up to 0.78 compared to other state-of-the-art methods. For real datasets, DAE-MKL identified three LGG subtypes and three KIRC subtypes, showing significant survival differences (KIRC log-rank $p$ = 3.33 × 10⁻⁸, LGG log-rank $p$ = 3.99 × 10⁻⁸). Additionally, we explored potential cancer-related biomarkers. Conclusions: The DAE-MKL effectively identifies molecular subtypes, reduces data dimensionality, and improves prognostic stratification in multi-omics cancer datasets, providing an effective tool for precision oncology. Full article

Background: The purpose of this study was to investigate the value of machine learning models for preoperative non-invasive prediction of International Society of Urological Pathology (ISUP) grading in clear cell renal cell carcinoma (ccRCC) based on CT urography (CTU)-related peritumoral area (PAT) radiomics features. Methods: We retrospectively analysed 328 ccRCC patients from our institution, along with an external validation cohort of 175 patients from The Cancer Genome Atlas. A total of 1218 radiomics features were extracted from contrast-enhanced CT images, with LASSO regression used to select the most predictive features. We employed four machine learning models, namely, Logistic Regression (LR), Multilayer Perceptron (MLP), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), for training and evaluation using Receiver Operating Characteristic (ROC) analysis. The model performance was assessed in training, internal validation, and external validation sets. Results: The XGBoost model demonstrated consistently superior discriminative ability across all datasets, achieving AUCs of 0.95 (95% CI: 0.92–0.98) in the training set, 0.93 (95% CI: 0.89–0.96) in the internal validation set, and 0.92 (95% CI: 0.87–0.95) in the external validation set. The model significantly outperformed LR, MLP, and SVM (p < 0.001) and demonstrated prognostic value (Log-rank p = 0.018). Transcriptomic analysis of model-stratified groups revealed distinct biological signatures, with high-grade predictions showing significant enrichment in metabolic pathways (DPEP3/THRSP) and immune-related processes (lymphocyte-mediated immunity, MHC complex activity). These findings suggest that peritumoral imaging characteristics provide valuable biological insights into tumor aggressiveness. Conclusions: The machine learning models based on PAT radiomics features of CTU demonstrated significant value in the non-invasive preoperative prediction of ISUP grading for ccRCC, and the XGBoost modeling had the best predictive ability. This non-invasive approach may enhance preoperative risk stratification and guide clinical decision-making, reducing reliance on invasive biopsy procedures. Full article

Introduction and Objectives: Local recurrence (LR) in patients treated with surgery for renal cell carcinoma (RCC) remains a significant clinical challenge that requires thorough investigation. Our study aimed to identify the relative risk factors and explore the optimal clinical management of LR. Materials and Methods: We conducted a non-randomized, observational, retrospective multicentric registry involving multiple Italian urological centers. We included patients treated with surgery (either nephron-sparing or radical nephrectomy) who later developed LR, defined as recurrence in the ipsilateral kidney or renal fossa. Patients with hereditary syndromes or metastatic disease at the time of LR diagnosis were excluded. Results: We reported 135 cases of LR with the following characteristics: most primary lesions were monofocal (85.7%), with a median size of 42 mm (23–53), the median R.E.N.A.L. score was 7 (6–8), and the median Padua score was 7 (6–9). Patients were treated with robot-assisted techniques in 59% of cases, laparoscopic surgery in 32.4%, and open surgery in 8.6%. Nephron-sparing surgery was performed in 75.2% of cases. Ischemia occurred in 61% of the cases, with a median ischemia time of 21 min (15.5–24). Intraoperative complications occurred in 3.8% of cases, while postoperative complications were reported in 13.8%, all of which were grade ≤3 according to the Clavien–Dindo classification. The primary tumors were pT1a in 43.5% of cases, pT1b in 26.3%, pT2 in 14.7% and pT3 in 15.5%. Histologically, 84% of cases were clear cell, 11.3% papillary type 1 or 2, and 3.7% chromophobe. Sarcomatoid/rhabdoid variants were present in 10.5% of cases. The median rate of LR was 1.3% (range 0.2–3.6), while the median time to LR was 18 months (12–39). LR occurred in the ipsilateral kidney in 70.5% of cases and in the ipsilateral renal fossa in 29.5%. The median rate of PSM in LR cases at initial surgery was 2.4% (range 0–4.3), while the median rate of negative surgical margin (NSM) in LR cases at initial surgery was 0.1 (0–0.3). Following LR diagnosis, most patients (49.2%) underwent surgery, 29.1% received cryoablation or radiotherapy, 17.1% received systemic treatment alone, and 4.6% followed a watchful waiting/active surveillance approach. At a median follow-up of 62 months, the highest oncological control in terms of 5-year cancer-specific survival and overall survival rates was achieved in surgically treated patients. The PSM, the histological variant, and their combination were found to be independent variables correlated with the occurrence of LR, with relative risks of 3.62, 2.71, and 8.12, respectively. Conclusions: LR after nephron-sparing or radical nephrectomy represents a significant clinical dilemma. Known risk factors are not always sufficient to predict recurrence, emphasizing the necessity of consistent radiological follow-up per guideline recommendations. Early detection of recurrence and a multidisciplinary approach involving expert centers are crucial for optimizing patient outcomes. Full article

Background/Objectives: Despite recent therapeutic advances, the clinical management of renal cell carcinoma (RCC) remains suboptimal. Current treatments are hindered by limited efficacy, the emergence of acquired drug resistance, suboptimal tolerability, and a lack of tumor-specific targeting. While development of novel agents remains an important avenue, it is often constrained by high costs, long development time, and low success rates. As an alternative approach, drug combinations of approved agents offer a promising strategy. Methods: Using our proprietary drug combination methodology, we identified multidrug combinations in RCC cells representing the clear cell (786O) and sarcomatoid chromophobe (UOK276) histological subtypes of RCC. Results: From an initial panel of 10 drugs, either approved or undergoing clinical trial, the optimized drug combinations (ODCs) contained crizotinib, telaglenastat, U-104, and vismodegib at clinical and subtherapeutic doses. The ODCs were non-toxic in advanced hepatic, renal, and cardiac cellular models. Importantly, their anti-tumor activity, already notable in normoxic (21% O₂) conditions (approx. 50%) was markedly enhanced in tumor-relevant hypoxia (1.5% O₂), reaching up to 77% in 2D and 62% in 3D spheroid 786O models. Moreover, chronic exposure of 786O and UOK276 cells led to durable responses, suggesting a prolonged effect in responders. Conclusions: Our findings demonstrate the potential of optimized, non-toxic drug combinations as a highly selective and effective strategy for accelerating the development of precision RCC treatment. Full article

Objectives: MicroRNAs of the miR-200 family are recognized as key inhibitors of epithelial-to-mesenchymal transition (EMT). However, there is limited data on the potential regulation of miR-200 family expression by long non-coding RNAs (lncRNAs) in RCC. Methods: We conducted a comprehensive literature and database search to identify lncRNAs that had been already functionally validated as regulators of any member of the miR-200 family. We analyzed the expression levels of the miR-200 family and the identified lncRNAs by qPCR. The study included 42 samples of carcinoma and non-carcinoma tissue from 25 RCC patients. In addition, we used RNA sequencing data from The Cancer Genome Atlas (TCGA), encompassing 511 kidney RCC (KIRC) samples, to further analyze the expression of miRNAs and lncRNAs. Results: We identified 127 lncRNAs with confirmed regulatory functions, 31 of which were validated in our samples. The majority of lncRNAs, along with all members of the miR-200 family, showed consistent downregulation in carcinoma tissues compared to non-carcinoma tissues. We observed a significant correlation between the expression of at least one member of the miR-200 family and 17 lncRNAs. In particular, three lncRNAs (MALAT1, OIP5-AS1, and LINC00467) showed a correlation with the expression of all members of the miR-200 family. Our results were at least partially confirmed in KIRC samples from the TCGA dataset. Conclusions: Our results suggest that the expression of the miR-200 family in RCC might be at least partially influenced by lncRNAs. Based on our cohort of samples, MALAT1, OIP5-AS1, and LINC00467 appear to be potentially important contributors to RCC development. Full article

Renal cell carcinoma (RCC) has a well-established propensity to form grossly visible tumour thrombi; however a comprehensive understanding of the underlying mechanisms is still lacking. The epithelial–mesenchymal transition (EMT) has been implicated in the progression of many carcinomas, including RCC; however, its exact role in the formation of venous tumour thrombi remains unclear. This study aims to explore the involvement of the EMT in venous invasion in RCC. In 14 patients with WHO/ISUP grade 2/3 clear cell RCC with venous invasion, the expression of main EMT markers (the miR-200 family, miR-205, SNAI1/2, TWIST1, ZEB2, and CDH1) was analyzed by qPCR in the selected tumour regions—the tumour centre (TC), the tumour periphery (TP), the venous tumour thrombus (VTT)—and compared to the corresponding non-neoplastic kidney tissue (N). Expression of E-cadherin, N-cadherin, and ZEB2 was analyzed immunohistochemically. The miR-200 family was downregulated in all areas examined compared to the corresponding N. When comparing the VTT with the TC, upregulation of miR-200c and miR-429 was observed. CDH1 was downregulated when the TP was compared with N, while SNAI2 was downregulated in all tumour regions. There was a strong correlation between the expression of all members of the miR-200 family. Our results demonstrate the presence of distinct molecular signatures between the selected ccRCC regions. The upregulation of two miRNAs in the VTT compared to the TC and their correlation with CDH1 expression could indicate a reversal of the EMT towards a more epithelial cell state in the VTT. Full article

Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of kidney cancer and is often diagnosed at advanced stages. PIEZO1, a mechanosensitive ion channel, has been implicated in cancer progression, but its prognostic relevance in ccRCC remains unclear. This study aimed to evaluate the expression pattern of PIEZO1 in ccRCC and its association with clinicopathological characteristics and patient survival. Immunohistochemical analysis was performed on formalin-fixed, paraffin-embedded tumor tissues from 111 patients with ccRCC, along with 23 matched peritumoral non-cancerous tissues. Protein expression was quantified using the H-score system. Associations with tumor grade, staging, and overall survival (OS) were analyzed. mRNA expression data were retrieved from The Cancer Genome Atlas (TCGA) to validate the protein-level findings. Functional enrichment and pathway analyses were conducted to explore the biological context of PIEZO1-related gene expression. PIEZO1 showed predominantly cytoplasmic localization, with significantly lower expression in tumor tissues compared to adjacent non-malignant tissue (p < 0.0001). High PIEZO1 expression was correlated with higher tumor grade (p = 0.0147) and shorter OS (p = 0.0047). These findings were confirmed at the mRNA level in the TCGA cohort. Multivariate Cox regression analysis identified PIEZO1 as an independent prognostic factor for OS. In conclusion, PIEZO1 may serve as a clinically relevant biomarker in ccRCC. Its overexpression is associated with more aggressive tumor characteristics and poor prognosis, underscoring the need for further investigation into its functional role and potential as a therapeutic target. Full article

Background/Objectives: Kidney transplantation is associated with an increased risk of renal cell carcinoma (RCC). This study aimed to evaluate the outcomes of de novo RCC in kidney transplant recipients (KTRs). Methods: We retrospectively identified 50 de novo RCC cases among 4012 KTRs transplanted from 2005 to 2024. Data on patient characteristics and outcomes were collected. Propensity score matching (PSM) compared 34 localized RCC cases in KTRs with 34 non-transplant RCC cases. The statistical analyses used Kaplan–Meier estimates, the log-rank test, and the Cox regression. Results: The RCC incidence was 0.64 per 1000 person-years, with a standardized incidence ratio of 4.40 (95% CI: 3.33–5.80). In the KTR cohort, clear cell RCC was present in 42%, and papillary RCC was present in 42%. RCC developed predominantly in native kidneys (92%). UICC stage I was present in 74%. The treatment for the non-metastatic RCC was nephrectomy in the majority of cases (91%). For the metastatic RCC, 71% received a tyrosine kinase inhibitor (TKI). In the KTR cohort, the 3- and 5-year overall survival (OS) rates were 85% and 72%, respectively, with a median OS of 199 months; the synchronous metastasized (M1) patients had a median OS of 14 months. Rejection, age, advanced UICC stage, higher pT stage, clinical positive lymph nodes, M1, and higher grade were significantly associated with poor OS. The 5-year OS (96% vs. 84%, p = 0.72) and MFS (92% vs. 93%, p = 0.61) were comparable in the PSM cohort between the KTRs and the non-KTRs in the localized RCC. Conclusions: KTRs have a higher risk of RCC and present at a localized stage with comparable OS rates to non-transplant RCC patients. Adverse tumor characteristics, including synchronous metastases, significantly affect the prognosis, highlighting the need for surveillance and individualized treatment, particularly for metastatic RCC. Full article