Search Results (465)

Clear cell renal cell carcinoma (ccRCC) is a highly immune-evasive malignancy that exhibits limited and often transient responses to immune checkpoint inhibitors (ICIs) and remains a major challenge for emerging cellular immunotherapies, including chimeric antigen receptor (CAR)-T cells. A defining feature of ccRCC, largely driven by von Hippel–Lindau (VHL) deficiency, is persistent activation of the transforming growth factor-β1 (TGF-β1) and hypoxia-inducible factor (HIF) signaling network. Acting as a central immunometabolic regulatory axis, TGF-β1/HIF promotes angiogenesis, metabolic reprogramming, epigenetic dysregulation, and immune escape through coordinated induction of immunosuppressive mediators, including PD-L1, VEGF, and CTLA-4, resulting in impaired T-cell infiltration, functional exhaustion, and resistance to immunotherapy. Preclinical studies have demonstrated that pharmacologic-dose Seleno-L-methionine (SLM) and its active metabolite, methylseleninic acid (MSA), suppress TGF-β1 and both HIF-1α and HIF-2α, leading to downregulation of multiple downstream immunosuppressive pathways at pharmacologically achievable, non-toxic concentrations. In addition to enhancing the antitumor activity of chemotherapy and VEGF-targeted agents, accumulating evidence suggests that SLM exerts broad immunologic, metabolic, and epigenetic effects that may overcome key mechanisms of therapeutic resistance. This review synthesizes current mechanistic and translational evidence supporting the repurposing of SLM as a first-in-class pleiotropic immunomodulatory agent. Using ccRCC as a model of TGF-β1/HIF-driven immune resistance, we discuss how simultaneous targeting of this central regulatory axis may restore immune surveillance, improve T-cell fitness and trafficking, enhance responses to ICIs and CAR-T cell therapy, and provide a mechanistically rational strategy for the treatment of advanced solid tumors. Full article

Background: Cytochrome P450 2J2 (CYP2J2) has been implicated in tumor biology, but its expression pattern and clinical significance in prostate and renal cancers remain poorly characterized. Methods: Commercially available tissue microarrays containing 208 renal and 121 prostate tissue specimens were used for immunohistochemical (IHC) characterization of CYP2J2 protein expression. We performed transcriptomic analysis and examined correlations with clinicopathological features and survival using the OncoDB 2.0 platform. Results: CYP2J2 immunoreactivity was mainly cytoplasmic, with minimal protein expression in both cancers. We identified positive staining in 7/100 (7.0%) prostate adenocarcinomas and 2/192 (1.0%) clear cell renal cell carcinoma (ccRCC) specimens, with negative expression in corresponding normal tissues. We detected no significant associations between protein expression and clinicopathological features in either cohort (all p > 0.05). In contrast, transcriptomic analysis revealed elevated CYP2J2 mRNA expression in both malignancies, with a slight increase in prostate adenocarcinoma (log₂ fold change = 1.10) and marked overexpression in ccRCC (log₂ fold change = 5.24) compared with normal tissues. We observed significant associations between CYP2J2 mRNA expression and pathological T stage in prostate adenocarcinoma (p = 0.0019) and pathological M stage in ccRCC (p = 0.0079). Moreover, higher CYP2J2 mRNA expression was associated with longer overall survival in ccRCC (HR = 0.64, 95% CI: 0.47–0.86; log-rank p = 0.0029) but not in prostate adenocarcinoma; however, these findings remain exploratory and do not establish independent prognostic value. Conclusions: Despite elevated transcript expression, CYP2J2 protein expression was infrequent in prostate adenocarcinoma and ccRCC, suggesting limited clinicopathological relevance and warranting further investigation using functional techniques. Full article

Clear cell renal cell carcinoma (ccRCC) is the most common and aggressive type of renal cell carcinoma (RCC), representing approximately 80% of cases globally. Despite improved diagnosis and therapy, treatment of aggressive or metastatic ccRCC remains challenging due to acquisition of primary or secondary resistance. Among the dysregulated signaling mechanisms identified in ccRCC, the mechanistic target of rapamycin (mTOR) and the nuclear factor kappa light-chain enhancer of activated B cells (NF-κB) pathways play central roles in regulating various biological functions such as metabolism, inflammation, tumor growth, and survival. However, the molecular crosstalk between mTOR and NF-κB signaling in ccRCC progression and therapeutic resistance remains poorly understood. Therefore, in our current study, we aimed to investigate the interplay between mTOR and NF-κB signaling in ccRCC. We analyzed tumor tissue samples from human ccRCC patients. For validation of mTOR and NF-κB signaling, we used two human ccRCC cell lines, A498 and 786-O. Using pharmacological inhibitors of mTOR and IKK/NF-κB signaling, Torin-1 and MLN120B, respectively, we assessed the functional relationship between these two pathways employing immunoblotting, EdU-based immunocytochemistry, and functional assays. Our findings reveal that both mTOR and NF-κB pathways are aberrantly activated in human ccRCC tissues. Phosphorylation of IκBα, S6, and 4E-BP1 was increased compared with matched adjacent control tissue. In A498 and 786-O cells, pharmacological inhibition of mTOR or IKK/NF-κB altered key readouts of the reciprocal pathway, including AKT, S6, 4E-BP1, IκBα and p65 phosphorylation. Both inhibitors reduced cell number and EdU incorporation, with stronger anti-proliferative effects observed after Torin-1 treatment. Pharmacological inhibition of either pathway altered key readouts of the other pathway, supporting a reciprocal functional association between mTOR- and NF-κB-associated signaling in the ccRCC models analyzed. Our findings support a functional association between mTOR- and NF-κB-associated signaling in the ccRCC models and provide a rationale for further mechanistic studies evaluating combined pathway modulation. Full article

Background/Objectives: Accurate prognostic stratification after nephrectomy for clear cell renal carcinoma (ccRCC) remains challenging. Traditional models often lack the intuitive clinical application or the ability to handle non-linear interactions between variables. We aimed to develop and internally validate a decision tree-based model to predict cancer-specific survival in patients with ccRCC following nephrectomy. Methods: We analyzed 79,526 patients with ccRCC who underwent nephrectomy from the SEER database (2012–2018). Patients were randomized into development (2/3) and validation (1/3) cohorts. A conditional inference tree was constructed to predict cancer-specific survival. Multiple imputation by chained equations was used to handle missing data. Discriminatory ability was assessed using the C-index. Net clinical benefit was evaluated with decision curve analysis. The model was evaluated using CHARMS and PROBAST. Results: A decision tree with 15 risk groups is presented, further classified into high-, intermediate-, and low-risk categories according to observed median survival. The final predictors were tumor localization, tumor grade, TNM stage, age, and sarcomatoid differentiation. The model demonstrated excellent discriminatory performance, with a C-index of 0.846 (95% CI: 0.834–0.847). PROBAST assessment showed low risk of bias and low concern regarding applicability. Conclusions: The use of decision trees provides an interpretable alternative to conventional regression-based models. Three main risk categories and 15 subgroups are proposed based on tumor localization, tumor grade, TNM stage, age, and sarcomatoid differentiation. Our model demonstrates good applicability and a low risk of bias according to PROBAST guidelines; however, external validation in independent cohorts is required prior to clinical implementation. Full article

Background: Sunitinib remains an important VEGFR-targeted therapy for advanced clear cell renal cell carcinoma (ccRCC), but acquired resistance frequently limits its clinical benefit. The molecular mechanisms underlying sunitinib resistance remain insufficiently understood. Methods: Sunitinib-resistant ccRCC models were generated by serial in vivo selection using Caki-1 and 786-O xenografts. Transcriptomic profiling, integration with GSE76068, and siRNA-based screening were performed to identify candidate resistance drivers. DERL3 expression and function were validated using qRT-PCR, Western blot, immunohistochemistry, gain- and loss-of-function assays, xenograft models, and mechanistic analyses of endoplasmic reticulum stress, ROS, and apoptosis. Results: Serial in vivo selection established stable sunitinib-resistant Caki-1-SR and 786-O-SR cells with markedly increased IC50 values. Integrated transcriptomic analysis identified six consistently upregulated genes in resistant models and GSE76068, among which DERL3 knockdown most strongly restored sunitinib sensitivity. DERL3 was upregulated in resistant ccRCC cells and clinical resistant specimens. High intratumoral DERL3 expression was associated with poor response to neoadjuvant sunitinib and shorter progression-free and overall survival. Functionally, DERL3 overexpression increased sunitinib resistance in vitro and in vivo, whereas DERL3 silencing restored drug sensitivity. Mechanistically, DERL3 depletion activated pro-apoptotic endoplasmic reticulum stress, increased ROS accumulation, and enhanced caspase-dependent apoptosis. Suppression of endoplasmic reticulum stress reduced ROS generation and apoptosis induced by DERL3 knockdown. In resistant xenografts, DERL3-targeted inhibition enhanced the antitumor efficacy of sunitinib. Conclusions: DERL3 is a clinically relevant driver of acquired sunitinib resistance in ccRCC. Targeting DERL3 may restore sunitinib sensitivity by reactivating pro-apoptotic endoplasmic reticulum stress and ROS-dependent apoptosis. Full article

Background/Objectives: Evaluation of renal tumour masses relies on conventional imaging, which cannot reliably characterise the histopathological type, and no validated blood-based diagnostic marker is available for renal cell carcinoma. The cfDNA integrity index, the ratio of long to short circulating cell-free DNA (cfDNA) fragments, may reflect the necrotic origin of tumour-derived DNA and is a candidate qualitative marker of malignancy. This exploratory, single-centre case–control study assessed the preoperative plasma cfDNA integrity index in patients with clear cell renal cell carcinoma (ccRCC). Methods: Plasma concentrations of 90 bp and 222 bp cfDNA fragments were measured by quantitative real-time PCR (qPCR) in 46 patients with histopathologically confirmed ccRCC (before surgery) and 17 healthy volunteers; the two groups were a convenience sample, were not matched, and differed in age and body-mass index. The cfDNA integrity index was defined as the ratio of the 222 bp to the 90 bp fragment concentration. Results: The cfDNA integrity index was higher in patients with ccRCC than in controls (median 0.28 vs. 0.15; p < 0.001, Mann–Whitney test) and rose progressively across healthy, non-metastatic (M0) and metastatic (M1) groups (p < 0.001, Kruskal–Wallis test; M0 vs. M1 p = 0.004). In unadjusted ROC analysis, both the integrity index (AUC 0.83, 95% CI 0.72–0.94) and its long 222 bp fragment component (AUC 0.93) discriminated patients with ccRCC from healthy volunteers, and the index separated metastatic from non-metastatic disease with an AUC of 0.79 (95% CI 0.64–0.88). The index was higher in high-grade (Fuhrman G3 + G4) tumours (p = 0.04) and in tumours with lymphovascular invasion (p < 0.001), and correlated with primary-tumour diameter. Conclusions: In this exploratory cohort, the preoperative plasma cfDNA integrity index was higher in patients with ccRCC than in healthy volunteers and was associated with several adverse pathological features; these findings require confirmation in larger, matched studies that include benign renal masses before any diagnostic role can be claimed. Full article

Background: Clear cell renal cell carcinoma (ccRCC) is characterized by marked molecular heterogeneity, aggressive clinical behavior, and prominent angiogenesis, highlighting the need to better understand the functional regulators underlying tumor progression and vascular remodeling. OTOF has previously been reported as a prognostically relevant gene in ccRCC; however, its biological function and potential involvement in tumor angiogenesis remain unclear. Methods: In the present study, we investigated the biological and pro-angiogenic roles of OTOF and explored the signaling pathways potentially involved. Results: Analysis of the TCGA-KIRC cohort confirmed that elevated OTOF expression was associated with unfavorable clinical outcomes. Functional experiments demonstrated that OTOF knockdown suppressed ccRCC cell proliferation, migration, and invasion and inhibited xenograft tumor growth. OTOF depletion also reduced intratumoral vascularization and impaired the ability of ccRCC cell-conditioned medium to promote HUVEC tube formation. Mechanistically, OTOF knockdown decreased VEGFA levels and was accompanied by reduced AKT phosphorylation and suppression of downstream HIF/VEGFA signaling. Pharmacological modulation of AKT signaling and VEGFA add-back experiments further supported the functional involvement of the AKT/HIF/VEGFA pathway in OTOF-associated angiogenesis. Conclusions: These findings extend previous observations regarding the prognostic relevance of OTOF by providing functional and mechanistic evidence that OTOF contributes to ccRCC progression and angiogenesis, at least in part, through AKT-dependent HIF/VEGFA signaling. Full article

Here, we report the identification of a previously unrecognized population of tumor-induced podoplanin-positive (PDPN⁺) cells in clear-cell renal cell carcinoma (ccRCC) that exhibit features of under-differentiated lymphatic endothelial cells (LECs). These PDPN⁺ cells lack a complete repertoire of canonical LEC markers, including VE-cadherin, LYVE1, and VEGFR3, and fail to form functional lymphatic vessels, indicating a dysplastic phenotype. We termed these cells dysLECs and found that these cells are induced by BMP10 produced specifically by tumor cells. In turn, dysLECs secrete CXCL13, which promotes tumor cell proliferation and metastasis. Ligand-receptor analyses revealed a highly tumor-specific reciprocal signaling circuit: kidney tubule cells deficient in the von Hippel-Lindau (VHL) tumor suppressor gene uniquely express BMP10, a TGF-β family cytokine, whereas its receptor ALK1 is restricted to dysLECs; conversely, dysLECs produce CXCL13, while VHL mutant kidney tubule cells uniquely express its receptor, CXCR5. Pharmacological inhibition of ALK1 reduced CXCL13 production and suppressed the hyperplastic phenotype of VHL mutant tumor cells in vivo, whereas BMP10 neutralization inhibited tumor growth and metastasis in an orthotopic ccRCC xenograft model. Collectively, these findings identify a dysplastic population of PDPN⁺ lymphatic-like endothelial cells and define a tumor-specific BMP10-CXCL13 signaling axis that drives ccRCC progression, uncovering a previously unrecognized therapeutic vulnerability in this disease. Full article

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) is frequently vascular and immune-infiltrated, yet durable responses to immune checkpoint blockade remain limited. This suggests that immune resistance may reflect tumor microenvironmental organization and mechanotransduction state rather than immune infiltration alone. We aimed to determine whether matrix reorganization and branch-specific integrin mechanosensing define immune-regulatory states in ccRCC, with particular attention to adenosine-associated immune resistance. Methods: We performed an integrative computational analysis of TCGA-KIRC bulk RNA-sequencing, clinical, survival, immune feature, and reverse-phase protein array data. Matrix- and mechanobiology-related programs were quantified using ssGSEA, compact z-score-based signatures, and principal component-based sensitivity analyses. Immune-regulatory programs, CAF and ECM scores, FAK/SRC activation features, and MINER-inferred transcriptional regulons were integrated using stage association, correlation, partial correlation, variance partitioning, survival, and transcriptional state analyses. Results: Matrix-centered transcriptional programs were the dominant stage-associated mechanobiology signal in ccRCC, including ECM deposition, collagen organization, matrix remodeling, fluid shear stress, and YAP/TAZ activity. A compact ECM-associated core (ECM_Stiffness_Core; a ten-gene signature whose highest-loading members include FN1, COL1A1, COL6A1, and LOX) captured a matrix reorganization program, indicating remodeling of ECM composition and architecture rather than uniform increases in tumor stiffness, pressure, or bulk mechanical load. Matrix remodeling was associated with CAF abundance, TGFβ signaling, CD276/B7-H3, CSF1-related myeloid biology, ENTPD1/CD39, and PRDM1, whereas associations with cytotoxic immune cells were weaker. Integrin mechanosensing separated into opposing branches: ITGA5/ILK/SRC-associated features aligned with higher-risk biology and adenosine-linked immune regulation, whereas PTK2/FAK–RHOA–ROCK components showed lower-risk directions. RPPA analyses supported SRC–FAK imbalance as an adverse signaling pattern. MINER analyses further separated matrix-associated immune-suppressive regulons from canonical integrin/focal adhesion states. Conclusions: Matrix reorganization and integrin branch imbalance appear to shift ccRCC toward distinct immune-regulatory states. We propose a conceptual model that matrix architecture may act as a directional suppressive amplifier, whereas the relative balance between ITGA5/ILK/SRC-associated signaling and canonical PTK2/FAK–RHOA–ROCK mechanosensing functions as an integrin branch rheostat. This framework identifies matrix remodeling, CD276/B7-H3, CSF1-related myeloid biology, adenosine signaling, and SRC–FAK imbalance as candidate biological axes for future investigation, including their potential relevance to combination strategies beyond PD-1/PD-L1 blockade. Future experimental, spatial, and treatment response studies may further clarify the mechanistic basis of these associations and evaluate their potential therapeutic relevance. Full article

Clear cell renal cell carcinoma (ccRCC), hepatocellular carcinoma (HCC), lung adenocarcinoma (LUAD), and pancreatic ductal adenocarcinoma (PDAC) are highly lethal cancers that share molecular mechanisms underlying tumor progression, yet common biomarkers across these cancers remain largely unexplored. Microarray datasets for the four cancers were analyzed to identify differentially expressed genes (DEGs) using adjusted $p<0.05$ and $\left|{\log }_2\mathrm{FC}\right|>1$ as significance thresholds. Disease-associated gene targets were collected from CTD, DISEASES, and GeneCards databases. Shared genes were identified across cancers, and functional enrichment analysis revealed their involvement in key cancer-related pathways, particularly the cell cycle. Protein–protein interaction networks identified ten candidate hub biomarkers (HGF, CDK1, CCNB1, RRM2, KIF14, DCN, SERPINE1, CCNA2, DLGAP5, and MAD2L1) consistently dysregulated across all four cancers. Survival analysis supported their potential as therapeutic targets, correlating with poor prognosis. These findings highlight candidate pan-cancer biomarkers for improved diagnosis and therapy. Full article

Background/Objectives: Prostate cancer is the second most frequent cancer among men and the 5th leading cause of cancer death among men worldwide. Identification of urine-derived biomarkers, such as exosomal miRNAs, in liquid biopsies for prostate cancer could be very beneficial for screening and active surveillance. Methods: Urine was collected from 42 patients with biopsy-proven evidence of prostate cancer and exosomes were extracted. Transcriptomic analysis was performed on the urine-derived exosomal miRNA and compared to the urine-derived exosomal miRNA profiles from 10 normal control donors and 15 von Hippel-Lindau (VHL) syndrome patients with clear cell renal cell carcinoma (ccRCC). Results: Urine-derived exosomal miRNA profiles of prostate patients were significantly different from normal control individuals. Significantly increased expression of miR-122-5p and decreased expression of miR-125-5p and miR-16-5p were observed in the urine-derived exosomes from prostate cancer patients. Significant upregulation of miR-30a-5p and downregulation of miR-320-5p, miR-320b, and miR-320c were observed in the urine-derived exosomes from both prostate cancer patients and VHL patients with ccRCC, indicating these miRNAs could be non-specific markers of urological cancer. Increased expression of miR-10a-5p and miR-30e-5p or miR-532-5p and miR-206 correlated with the presence of either extracapsular or perineural invasion, respectively. Conclusions: This study highlights the potential for urine-derived exosomal miRNA profiles to identify the presence of prostate cancer and predict clinical features, additionally showing that miRNA signals could be non-specific markers of urologic cancer types. Further validation studies are necessary to demonstrate the utility of urine-derived exosomal miRNA profiles as biomarkers for diagnosis or prognosis in prostate cancer. Full article

Background/Objectives: Clear cell renal cell carcinoma (ccRCC), the predominant malignant subtype of kidney cancer, is the leading cause of death among renal cell carcinoma patients. Although a subset of ccRCC patients benefit from select immune checkpoint inhibitors (ICIs), prognosis remains poor. While PD-1 and PD-L1 have been extensively studied, the prevalence and distribution of other immune checkpoints (ICs) and their relationship with epithelial-to-mesenchymal transition (EMT) remain poorly characterised. Here, we investigated the interplay between twenty ICs and EMT markers and assessed their combined prognostic relevance in ccRCC patients. Methods: Transcriptomic profiling and integrated bioinformatic analyses were performed, including differential expression, correlation analyses, survival analyses, forest plot analyses, ROC curve evaluation, and OncoPrint visualisation, complemented by analysis of single-cell RNA sequencing data, immunohistochemistry, and multiplex secretory IC (LegendPlex) assays. Results: Transcriptomic profiling of over 500 ccRCC tumours versus normal kidney tissue revealed dysregulation of ICs, particularly LAG3 and NT5E. Notably, expression of ICs, including LAG3 and NT5E, was associated with poor overall survival in 415 ccRCC patients. ICs that synergised with the EMT phenotype provided improved prognostic discrimination compared to individual ICs. Correlation analyses, single-cell RNA sequencing, and immunohistochemistry demonstrated an association between EMT-associated tumours and expression of LAG3 and NT5E. ROC analysis indicated modest prognostic performance of LAG3 and NT5E. Conclusions: Collectively, this study identifies an EMT–IC axis in ccRCC and demonstrates its relevance to tumour biology and patient outcomes, highlighting LAG3 and NT5E as potential prognostic markers and therapeutic targets that warrant further investigation. Full article

Background: Hypertension is a common comorbidity and risk factor for clear cell renal cell carcinoma (ccRCC), yet the molecular mechanisms linking these two diseases remain unclear. This study aimed to investigate hypertension-related molecular signatures in ccRCC using integrated multi-transcriptomic analyses. Method: Hypertension-related differentially expressed genes (DEHRGs) in ccRCC were identified by integrating transcriptomic data from the TCGA-KIRC cohort with the GeneCards database. Functional enrichment, WGCNA, machine learning, GSVA, survival analysis, and Mendelian randomization were performed to identify and characterize hub genes. Spatial and single-cell transcriptomic analyses were used to investigate tumor heterogeneity and predict candidate therapeutic compounds, which were subsequently evaluated in vitro. Results: Four hypertension-related hub genes—SCNN1G, CASR, KCNJ1, and WNK4—were identified and were mainly involved in ion transport, electrolyte homeostasis, and blood pressure regulation. Diagnostic models based on these genes showed good discriminatory performance between tumor and normal tissues, and the nomogram showed good calibration and potential clinical benefit. Higher hypertension-related transcriptional activity was associated with significantly poorer overall survival, while MR analysis suggested a genetic association with ccRCC risk. Spatial transcriptomics revealed pronounced spatial heterogeneity of SCNN1G, CASR, KCNJ1, and WNK4, with these hub genes predominantly enriched in stromal and immune regions. Single-cell-based drug screening identified candidate compounds predicted to have antitumor activity, among which epicatechin gallate (ECG) and pseudoginsenoside-F11 showed favorable tumor selectivity. Conclusions: This study systematically characterized hypertension-related molecular signatures in ccRCC and identified SCNN1G, CASR, KCNJ1, and WNK4 as key hub genes. These genes may contribute to the molecular association between hypertension and ccRCC. They also represent promising candidate biomarkers and therapeutic targets. Integrated spatial and single-cell analyses further identified pseudoginsenoside-F11 and ECG as potential therapeutic compounds and supporting a potential molecular association between hypertension and ccRCC. Full article

Background and Objectives: Clear cell renal cell carcinoma (ccRCC) demonstrates substantial molecular and clinical heterogeneity, limiting the prognostic accuracy of conventional staging system and complicating treatment selection. CT-based radiomics and radiogenomics have emerged as promising non-invasive approaches for predicting molecular biomarkers. This review aimed to evaluate the current evidence regarding CT-based radiogenomics for the prediction of molecular markers in ccRCC, with emphasis on methodological approaches, predictive performance, and clinical applicability. Materials and Methods: A comprehensive literature search of PubMed/MEDLINE, Scopus, and Cochrane Library databases was performed for original studies published between January 2012 and December 2025. Eligible studies included patients with histopathologically confirmed ccRCC, performed CT-based radiomics feature extraction, and investigated molecular or genetic biomarkers using machine learning (ML) methods. Data regarding CT acquisition phase, segmentation strategy, radiomics features, ML algorithms, investigated biomarkers, and model performance metrics were extracted. Results and Discussion: Twenty-five retrospective studies were included. CT-based radiomics demonstrated promising performance in predicting gene mutations, including Von Hippel–Lindau (VHL), Polybromo 1 (PBRM1), BRCA1-associated protein 1 (BAP1), SET domain containing 2 (SETD2), and Lysine demethylase 5C (KDM5C), with reported area under the curve (AUC) values reaching 0.987. Radiogenomic models also showed utility in assessing hypoxia-related pathways, lipid metabolism signatures, programmed cell death profiles, immune-related markers, and tumor microenvironment characteristics, including programmed death-ligand 1 (PD-L1), Cluster of Differentiation 68 (CD68+) tumor-associated macrophages (TAMs), Cytotoxic T-Lymphocyte–Associated Protein 4 (CTLA-4), Forkhead Box P3 (FOXP3), and Ki-67 proliferation index. Predictive performance varied across biomarkers, with AUCs generally ranging from 0.68 to 0.91. Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), Adaptive Boosting (AdaBoost), and Gradient Boosting algorithms were most commonly applied. Conclusions: CT-based radiogenomics represents a promising non-invasive tool for molecular characterization and risk stratification in ccRCC. Standardized multicenter prospective studies, methodological homogeneity, and external validation are required before routine clinical implementation. Full article

Solid tumors frequently experience hypoxia during tumor progression, resulting in profound metabolic alterations. This phenomenon is particularly pronounced in clear-cell renal cell carcinoma (ccRCC) because of loss of the von Hippel–Lindau (VHL) tumor suppressor gene and constitutive activation of hypoxia-inducible factor (HIF) signaling. ccRCC is the most common subtype of kidney cancer, and durable therapeutic responses remain limited despite advances in immune checkpoint inhibition. Owing to its strong pseudohypoxic phenotype and extensive metabolic rewiring, ccRCC is widely regarded as a metabolic disease. These alterations generate a unique immune landscape characterized by abundant immune-cell infiltration together with profound T-cell dysfunction and exhaustion. This paradoxical “immune-hot yet immunosuppressed” phenotype is largely driven by hypoxia-associated immunometabolic reprogramming within tumor cells and the tumor microenvironment (TME). Several metabolic pathways are critically involved in this process, including lactate acidosis, arginine (Arg) depletion, tryptophan (Trp) depletion, kynurenine (Kyn)-mediated T-cell exhaustion, and adenosine-driven immune suppression. This review summarizes the current understanding of hypoxia-driven immunometabolic interactions in ccRCC and discusses how targeting these pathways may improve future therapeutic strategies against this aggressive malignancy. Full article