SEARCH · PubMed Health

Results for “ccRCC”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2024

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Humans↗

PubMed2025

Study on the mechanism of BGN in progression and metastasis of ccRCC.

PURPOSE: To investigate the role of Biglycan(BGN) in the progression and metastasis of clear cell renal cell carcinoma(ccRCC). METHODS: Based on multiple public databases, we investigated the expression level of BGN in ccRCC, its clinical significance, and its association with immune cells. Real-time fluorescence quantitative polymerase chain reaction(PCR) was employed to validate BGN expression in tumor and adjacent normal tissues from ten patients. We utilized RNA sequencing results for further analysis, including differential gene analysis, GO-KEGG analysis, and GSEA analysis, to identify the signaling pathways through which BGN exerts its effects. BGN knockdown cells(786-0 and Caki-1) were generated through lentiviral transfection to examine the impact of BGN on ccRCC. Cell proliferation, migration, and invasion were assessed using CCK8, colony formation, wound healing, Transwell migration, and invasion assays, respectively. RESULTS: Our findings from database analysis and PCR revealed a significant upregulation of BGN expression in kidney cancer tissues compared to normal tissues. Further analysis demonstrated a correlation between high BGN expression and ccRCC progression and immune infiltration. In vitro experiments confirmed that BGN silencing effectively inhibited cell proliferation, migration, and invasion of ccRCC. Mechanistically, these effects may be mediated through the MAPK signaling pathway. CONCLUSION: BGN potentially plays a pivotal role in the progression and metastasis of ccRCC, possibly acting through the MAPK signaling pathway. Therefore, BGN holds promise as a potential therapeutic target for ccRCC.

Humans↗

PubMed2026

Machine learning and multi-omics clustering to map cellular rewiring and immune evasion in ccRCC.

Immune checkpoint blockade (ICB) efficacy in clear cell renal cell carcinoma (ccRCC) is limited by tumor microenvironment (TME) heterogeneity. Because traditional bulk-derived models lack spatial resolution, we developed an integrated framework connecting macroscopic survival risks to microscopic TME structures. We applied ten algorithms to establish multi-omics subtypes and evaluated 101 machine-learning combinations across three independent cohorts to generate a Consensus Machine Learning-driven Signature (CMLS). The signature's spatial and cellular origins were decoded using spatial transcriptomics (ST) and a 140,000-cell scRNA-seq atlas. Expression of key genes was experimentally validated via RT-qPCR in 17 paired ccRCC clinical tissues. We identified two molecular subtypes with distinct clinical and epigenetic profiles. SuperPC optimization yielded a 24-gene CMLS serving as an independent prognostic factor. scRNA-seq and ST deconvolution revealed these signals predominantly originate from cancer-associated fibroblasts (CAFs) and malignant epithelial cells, which collaborate to drive spatial immune exclusion. RT-qPCR confirmed significant overexpression of five core CMLS genes in ccRCC versus adjacent normal tissues. Low CMLS scores correlated with enhanced ICB responsiveness, whereas high-CMLS tumors demonstrated specific vulnerability to dasatinib and dabrafenib. The CMLS translates spatial immune-exclusion dynamics into a quantifiable metric, outperforming tumor mutational burden in predicting ICB benefits, providing a robust tool for patient stratification in ccRCC.

Humans↗

PubMed2026

Oxygen-dependent subcellular redistribution of PHD3 links the hypoxic microenvironment to mitochondrial metabolic reprogramming in ccRCC.

Clear cell renal cell carcinoma (ccRCC) is characterized by profound metabolic dysregulation, with both prolyl hydroxylase domain protein 3 (PHD3) and pyruvate carboxylase (PC) independently implicated in disease progression. Although each influences patient outcomes, a direct mechanistic interplay between these two regulators has remained elusive. Here, we uncover a novel regulatory axis involving PHD3 and PC by identifying an unexpected subcellular behavior of PHD3, namely, its dual localization to the cytosol and the mitochondrial matrix. We show that mitochondrial import of PHD3 is associated with its intracellular clustering, a process modulated by PHD3 hydroxylase activity and oxygen levels. Once in the matrix, PHD3 directly hydroxylates PC, suppressing its enzymatic activity. In ccRCC with elevated PHD3 expression, this modification restricts anaplerotic flux into the tricarboxylic acid cycle, leading to impaired proliferation, reduced metastasis, and enhanced apoptosis. Together, our findings provide a new framework for targeting cancer metabolism by establishing a previously unrecognized mechanistic link between PHD3-mediated oxygen sensing within the tumor microenvironment and the regulation of ccRCC mitochondrial metabolism through the subcellular re-localization of PHD3.

Journal Article↗

PubMed2025

Tracking Nongenetic Evolution from Primary to Metastatic ccRCC: TRACERx Renal.

While the key aspects of genetic evolution and their clinical implications in clear cell renal-cell carcinoma (ccRCC) are well-documented, how genetic features co-evolve with the phenotype and tumor microenvironment (TME) remains elusive. Here, through joint genomic-transcriptomic analysis of 243 samples from 79 patients recruited to the TRACERx Renal study, we identify pervasive non-genetic intratumor heterogeneity, with over 40% not attributable to genetic alterations. By integrating tumor transcriptomes and phylogenetic structures, we observe convergent evolution to specific phenotypic traits, including cell proliferation, metabolic reprogramming and overexpression of putative cGAS-STING repressors amid high aneuploidy. We also uncover a co-evolution between the tumor and the T cell repertoire, as well as a longitudinal shift in the TME from an anti-tumor to an immunosuppressive state, linked to the acquisition of recurrently late ccRCC drivers 9p loss and SETD2 mutations. Our study reveals clinically-relevant and hitherto underappreciated non-genetic evolution patterns in ccRCC.

Journal Article↗

PubMed2025

miR-9-5p/HMMR regulates the tumorigenesis and progression of clear cell renal cell carcinoma through EMT and JAK1/STAT1 signaling pathway.

BACKGROUND: The most common malignant type of kidney cancer is clear cell renal cell carcinoma (ccRCC). The expression levels of hyaluronan-mediated motility receptor (HMMR) in many tumor types are significantly elevated. HMMR is closely associated with tumor-related progression, treatment resistance, and poor prognosis, and has yet to be fully investigated in terms of its expression patterns and molecular mechanisms of action in ccRCC. Further research is imperative to elucidate these aspects. METHODS: We used The Cancer Genome Atlas (TCGA) database to preliminarily investigate HMMR expression and function in ccRCC and the data for 19 samples from the NCBI GEO database (GSE207493) for single-cell analysis. We assessed the differential expression level of HMMR between ccRCC cancerous tissues and their matched non-tumor tissues. Subsequently, a series of in vivo and in vitro experiments were designed to elucidate the biological function of HMMR in ccRCC, including Transwell assays, CCK-8 assays, clone formation assays and subcutaneous xenograft experiments in nude mice. Through bioinformatics analysis, we identified potential microRNAs (miRNAs) that may regulate HMMR, as well as the possible signaling pathways involved. Finally, we conducted a series of cellular functional experiments to validate our hypotheses regarding the HMMR axis. RESULTS: HMMR expression was significantly up-regulated in tumor tissues of ccRCC patients, and elevated HMMR expression level showed a strong correlation with ccRCC progression and adverse prognoses of patients. Knocking down HMMR inhibited the proliferative and migratory abilities of ccRCC cells, while its overexpression amplified these oncogenic properties. In nude mice model, reduced HMMR expression inhibited ccRCC tumor proliferation in vivo. Furthermore, overexpression of an upstream transcriptional regulator, miR-9-5p, effectively downregulated HMMR expression and thus impeded ccRCC cells proliferation and migration. HMMR might influence ccRCC growth via the Epithelial-Mesenchymal Transition (EMT) pathway and the Janus Kinase 1/Signal Transducer and Activator of Transcription 1 (JAK1/STAT1) pathway. CONCLUSIONS: HMMR is overexpressed in ccRCC, and there is a significant link between high HMMR expression and tumor progression, as well as poor patient prognosis. Specifically, HMMR could be targeted and inhibited by miR-9-5p and might modulate the tumorigenesis and progression of ccRCC through both EMT and JAK1/STAT1 signaling pathway.

Carcinoma, Renal Cell↗

PubMed2026

KIM-1 in Advanced Papillary and Clear Cell Renal Cell Carcinoma.

Kidney injury molecule 1 (KIM-1) is a promising biomarker in adjuvant clear cell renal cell carcinoma (ccRCC), but its relevance in advanced ccRCC or papillary RCC (pRCC) remains unclear. CALYPSO (NCT02819596) was a prospective, multi-arm trial that evaluated durvalumab alone or in combination with tremelimumab or savolitinib in metastatic ccRCC and pRCC. Circulating KIM-1 levels were measured at baseline and on-treatment. The primary endpoint was to explore if KIM-1 levels were raised in pRCC. Analyses were exploratory and p values were nominal. KIM-1 was measured in 123 patients with ccRCC and 31 patients with pRCC. Higher median concentrations occurred in pRCC compared to ccRCC (7835 vs 5470 pg/ml, p = 0.05). Reductions in KIM-1 levels occurred with systemic therapy in both ccRCC and pRCC (-59.2% and -32% respectively). In pRCC, radiological responders had significantly lower baseline KIM-1 levels (p = 0.025). In ccRCC, high baseline KIM-1 levels were associated with significantly shorter overall survival (OS) (hazard ratio [HR] 1.77; 95% CI, 1.15-2.72; p = 0.01). Also, an increase in KIM-1 during therapy was linked to worse progression-free survival (HR 1.7; 95% CI, 1.13-2.58; p = 0.01) and OS (HR 1.95; 95% CI, 1.23-3.08; p = 0.004) in ccRCC. This exploratory analysis supports the utility of KIM-1 in advanced ccRCC and pRCC.

Aged↗

PubMed2026

Reduced VEPH1 expression is associated with an invasive phenotype and poor prognosis in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) remains a clinically heterogeneous urologic malignancy, and improved biomarkers are needed to refine prognostic stratification. VEPH1 has been implicated in cancer biology, but its role in ccRCC is incompletely defined. This study aimed to investigate the expression, prognostic relevance, and functional effects of VEPH1 in ccRCC. METHODS: VEPH1 transcript expression and prognostic relevance were evaluated using The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset and the University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) and validated in paired ccRCC and adjacent normal renal tissues. The ability of VEPH1 transcript expression to distinguish tumor from normal tissues within the TCGA-KIRC dataset was assessed by receiver operating characteristic analysis. Gain- and loss-of-function experiments were performed in 786-O and 769-P ccRCC cells to determine the effects of VEPH1 on epithelial-mesenchymal transition (EMT)-related markers, migration, and invasion. AKT and ERK phosphorylation was evaluated by western blotting. RESULTS: VEPH1 transcript expression was significantly lower in ccRCC tissues than in normal renal tissues and distinguished tumor from normal samples within the TCGA-KIRC dataset. Low VEPH1 transcript expression was associated with poorer overall survival. Validation in 11 paired clinical specimens confirmed reduced VEPH1 messenger RNA (mRNA) and VEPH1 protein expression in tumor tissues. Functionally, VEPH1 overexpression increased E-cadherin, decreased N-cadherin, and suppressed migration and invasion, whereas partial VEPH1 knockdown produced the opposite changes. In exploratory signaling analyses, VEPH1 overexpression was associated with reduced AKT and ERK phosphorylation without altering total AKT or ERK levels. CONCLUSIONS: Reduced VEPH1 transcript expression was associated with poorer overall survival, whereas experimental VEPH1 depletion was associated with invasive and EMT-related features in ccRCC cells. VEPH1 may represent a candidate prognostic indicator in ccRCC; however, its relationship with AKT and ERK signaling and its clinical relevance require further mechanistic and independent-cohort validation.

Clear cell renal cell carcinoma (ccRCC)↗

PubMed2026

Multi-Omics Integration Identifies a Five-Gene Metabolic Signature With Experimental Validation in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is hallmarked by profound metabolic reprogramming; however, its intricate crosstalk with the tumor immune microenvironment (TIME) and its clinical ramifications remain inadequately elucidated. This study aims to systematically decipher the metabolic-immune interplay in ccRCC through multi-omics integration, with the goal of identifying robust prognostic biomarkers and actionable therapeutic vulnerabilities. AIMS: This study aims to systematically decipher the metabolic-immune interplay in clear cell renal cell carcinoma (ccRCC) through multi‑omics integration, and to identify robust prognostic biomarkers and actionable therapeutic vulnerabilities that can inform precision risk stratification and individualized treatment strategies. METHODS: We integrated bulk transcriptomic, genomic, and clinical data from multiple ccRCC cohorts. Differential expression and functional enrichment analyses were performed to characterize metabolic pathway alterations. Mendelian randomization (MR) was employed to infer causal relationships between metabolic disorders and ccRCC risk. A machine learning-based prognostic framework, incorporating SHAP (SHapley Additive exPlanations) for feature interpretability, was constructed and rigorously validated. TIME heterogeneity was dissected using deconvolution algorithms, while drug sensitivity, tumor mutation burden (TMB), and TIDE scores were utilized to assess therapeutic responses and immune evasion. Candidate gene function was evaluated through in vitro gain- and loss-of-function assays, with expression validated via TCGA, HPA, western blot, and qRT-PCR. RESULTS: Enrichment analysis identified coordinated dysregulation in lipid metabolism, energy homeostasis, and hypoxia response pathways. MR analysis confirmed lipid metabolism disorders as a causal risk factor for ccRCC. Our machine-learning model, centered on five core SHAP-identified features (SUCLA2, ACAT1, PC, SUCLG1, and HMGCS2), demonstrated superior predictive accuracy over conventional clinical staging. Immune profiling unveiled dichotomous TIME states: the low-risk group retained active immune surveillance, whereas the high-risk group was enriched with immunosuppressive subsets. Drug sensitivity screening pinpointed LY2109761 and carmustine as high-risk-specific candidate agents. Furthermore, TMB and TIDE analyses stratified high-risk patients displaying genomic instability and immune evasion phenotypes. Functionally, SUCLA2 knockdown significantly enhanced ccRCC cell proliferation and invasion, while its overexpression suppressed these malignant phenotypes, corroborating its tumor-suppressive role. Expression patterns of the hub genes were consistently validated across multi-level datasets and experimental assays. CONCLUSION: This study establishes a precision oncology framework for ccRCC by functionally linking metabolic biomarkers, immunophenotypes, and stratified therapeutic strategies. Importantly, we identify SUCLA2 as a potential functional tumor suppressor and a promising target for further mechanistic and translational investigation.

Humans↗

PubMed2026

Proteomic Analysis Identifies Potential Biomarkers of ELOC -Mutated Renal Cell Carcinoma.

ELOC -mutated renal cell carcinoma (RCC) is a rare tumor with only ∼40 cases reported to date; it shares a molecular background with clear cell RCC (ccRCC) in terms of hypoxia-inducible factor-alpha (HIF-α) protein accumulation. ELOC -mutated RCC is characterized by prominent leiomyomatous stromal growth and a more indolent clinical course compared with ccRCC. In our previous study, whole-genome sequencing of 102 ccRCC cases identified 5 cases of ELOC -mutated RCC. In the present study, we conducted proteomic and immunohistochemical analyses on up to 13 Japanese ELOC -mutated RCCs, including 8 previously reported cases, to elucidate its distinct molecular mechanisms and identify biomarkers that may be useful in distinguishing ELOC -mutated RCC from ccRCC. Proteomic profiling revealed that molecules, including cytokeratin 7, scinderin (SCIN), and sortilin 1 (SORT1), were significantly overexpressed in ELOC -mutated RCC compared with ccRCC. Notably, SCIN and SORT1 emerged as novel potential diagnostic biomarkers for distinguishing ELOC -mutated RCC from ccRCC. The analysis further suggested that ELOC -mutated RCC relies more on oxidative phosphorylation and less on glycolysis than ccRCC. This metabolic shift may be linked to the relative depletion of NAD+ due to the low expression of NAPRT and QPRT. In addition, we observed geographic variation in the disease frequency among different cohorts, with a higher frequency in Japan. Our findings provide novel insights into the pathogenesis of ELOC -mutated RCC and highlight SCIN and SORT1 as potential supportive biomarkers.

Humans↗

PubMed2026

The fall of the genome protectors triad: PBRM1, SETD2, and BAP1's impact on metabolism and immunity in clear cell renal cell carcinoma.

The loss of chromosome 3p and the inactivation of the tumor suppressor gene von Hippel-Lindau (VHL) were identified in clear cell renal cell carcinomas (ccRCC) over three decades ago. Since then, mutations in genes for the three chromatin modulators, polybromo 1 (PBRM1), SET domain-containing 2 (SETD2), and BRCA1-associated protein-1 (BAP1), have been recognized as common in ccRCC. Although these genomic alterations are central to understanding ccRCC's development, other deregulated cellular processes are also prominent in these tumors. Metabolic reprogramming is a key hallmark of this disease, characterized by various changes linked to the stabilization of hypoxia-inducible factors (HIF), including increased aerobic glycolysis, elevated lipid levels, and glutamine dependence for cell survival. Additionally, HIF-α stabilization plays a crucial role in regulating the immune system, thereby enhancing CD8+ T lymphocyte cytotoxicity. Immune checkpoint inhibitors (ICI) are now used as first-line treatments to target the often highly infiltrated tumor microenvironment of ccRCC. However, the effectiveness of ICI varies and is difficult to predict. Although emerging studies are beginning to provide insight, evidence suggests roles for PBRM1, SETD2, and BAP1 in metabolic regulation and in shaping the tumor immune microenvironment in ccRCC. Here, we review recent advances in this field and examine their impact on the management of ccRCC.

BAP1↗

PubMed2026

Targeting RELA and STAT3 regulates TNFRSF10A-mediated apoptosis in a novel apoptosis-based prognostic model for clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal malignancy and remains a major cause of cancer-related mortality worldwide. Although advances in surgery, targeted therapy, and immunotherapy have improved outcomes for patients, reliable biomarkers for predicting prognosis remain limited. Therefore, robust gene-based prognostic models are urgently needed to improve risk stratification and guide individualized treatment strategies. METHODS: We developed a novel prognostic model integrating apoptosis and immune - related genes (AIRGs) to predict overall survival (OS) in patients with ccRCC. RESULT: Using Gene Set Enrichment Analysis (GSEA) combined with least absolute shrinkage and selection operator (LASSO) Cox regression, we identified 7 key prognostic genes, namely, CCR4, TNFRSF10A, TEK, TGFA, CD14, IFITM1, and SEMA3G, that collectively demonstrated strong predictive performance in TCGA cohort with c-index = 0.711. Functional enrichment analyses revealed that apoptosis, immune regulation, and multiple oncogenic signaling pathways were significantly associated with the risk score, highlighting the critical role of the tumor microenvironment in ccRCC progression. Transcription factor binding analysis based on the JASPAR database suggested that RELA and STAT3 with scores of 0.829 and 0.951, respectively are potential upstream regulators within the prognostic network, particularly influencing TNFRSF10A expression. External validation using the International Cancer Genome Consortium (ICGC) dataset confirmed the robustness of the prognostic model with c-index = 0.612 Furthermore, in vitro experiments demonstrated that RELA and STAT3 regulate TNFRSF10A-mediated apoptotic signaling in ccRCC cells, providing mechanistic support for the bioinformatic findings. CONCLUSION: This study establishes a biologically informed and clinically relevant prognostic framework for ccRCC. Our findings highlight the therapeutic potential of targeting the RELA/STAT3-TNFRSF10A axis and contribute to the advancement of precision medicine in ccRCC.

Humans↗

PubMed2026

Distinct endogenous retroviruses are expressed in mutational subtypes of clear cell renal cell carcinoma and are linked to improved clinical outcomes.

Distinct mutations in chromatin regulators and aberrant expression of transposable elements (TEs), have been associated with clinical benefit to immunotherapy (IO) in specific clear cell renal cell carcinoma (ccRCC) clinical contexts. However, the relationship between mutations in chromatin regulators and TE expression, and their effect on clinical outcomes, are incompletely understood. Here, we identified TEs expressed in distinct mutational subtypes of ccRCC, with endogenous retroviruses (ERVs) comprising the majority of TEs observed. Of these, ERVs 544 and 2014 were upregulated in PBRM1 mutant samples. Patients with high expression of these ERVs and somatic PBRM1 mutations had improved progression-free survival with IO monotherapy, but not targeted therapy, and their upregulation associated with expression of innate immune pathways. Chromatin accessibility increased at ERV 544 and 2014 loci in PBRM1-deficient ccRCC cells, and ERV 544 and 2014 were upregulated upon in vitro PBRM1 knockout in ccRCC cell line clones. Broadly, our study supports a link between PBRM1 mutations, subsequent chromatin accessibility changes, and aberrant but immunoresponsive ERVs in ccRCC.

CP: cancer↗

PubMed2026

Dietary Polyphenol Acteoside-Related Molecular Signatures in Clear Cell Renal Cell Carcinoma: Multi-Omics Profiling and Functional Validation of IMPDH1.

Clear cell renal cell carcinoma (ccRCC) is characterized by substantial metabolic and molecular heterogeneity, but the disease-relevant programs associated with acteoside, a dietary polyphenol, remain poorly understood. We integrated predicted acteoside targets with bulk, single-cell, and spatial transcriptomic data from ccRCC and combined molecular subtyping with cross-cohort machine-learning analysis. Acteoside-related signatures were preferentially enriched in malignant compartments and increased with tumor grade and stage. Consensus clustering identified two molecular subtypes with distinct biological and clinical features. C1 was associated with immune activation, metabolic activity, and more favorable survival, whereas C2 showed greater genomic instability, reduced renal epithelial differentiation, and poorer outcomes. We further benchmarked multiple machine-learning strategies and established a 10-gene prognostic model that retained predictive performance across independent cohorts, with IMPDH1 emerging as the strongest risk-associated feature. Functional experiments confirmed the biological relevance of IMPDH1: its knockdown suppressed ccRCC cell proliferation, DNA synthesis, colony formation, and migration, whereas overexpression produced the opposite effects. Together, these findings indicate that acteoside-related molecular signatures capture clinically relevant heterogeneity in ccRCC and provide a framework for linking dietary-polyphenol-related molecular space with tumor biology. The identification and functional validation of IMPDH1 further highlight its potential importance in ccRCC progression.

IMPDH1↗

PubMed2025

HMGA2 links morphological evolution and microenvironment dynamics to systemic therapy response in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits significant heterogeneity due to morphological changes and tumor microenvironment dynamics, influencing systemic therapy responses. While the role of high-mobility group AT-hook 2 (HMGA2) in tumor progression has been implicated in other cancers, its significance in ccRCC remains unclear. This study investigates the role of HMGA2 in these processes and its clinical impact. METHODS: Spatial transcriptomics (ST) was performed on primary ccRCC samples to investigate expression trajectories associated with HMGA2 expression and morphological evolution. In metastatic ccRCC cohorts treated with systemic therapy, immunohistochemistry and bulk RNA sequencing data were analyzed to evaluate molecular and clinical features in relation to HMGA2. Single-cell RNA sequencing (scRNA-seq) data were used to explore immune cell populations and their interactions. Based on these findings, multiplex immunohistochemistry (mIHC) assessed spatial distribution, cell-cell interactions, and pathological responses of key immune populations. RESULTS: HMGA2 expression was associated with aggressive morphological patterns, such as solid sheets and rhabdoid/sarcomatoid. ST revealed a progressive increase in HMGA2 expression along the morphological trajectory, marked by a shift from clear to eosinophilic cytoplasm, with eccentric nuclei and prominent nucleoli, and loss of vascular architecture. HMGA2-high tumors exhibited aggressive phenotypes driven by cell cycle, epithelial-mesenchymal transition, and inflammatory signaling pathways. Clinically, patients with high HMGA2 had worse progression-free survival but responded better to immune checkpoint inhibitor combination (Combo-ICI) therapy than to tyrosine kinase inhibitor monotherapy. To assess the immune landscape, scRNA-seq data revealed that HMGA2-high tumors were enriched with progenitor exhausted CD8+ T cells (Tpex), along with increased frequencies of conventional dendritic cell type 1 (cDC1) and inflammatory cDC type 2, which were found to interact with Tpex via ICAM-1. mIHC confirmed that Tpex were enriched among Combo-ICI responders in HMGA2-high tumors, with higher densities and closer proximity to ICAM-1+ cDC1. CONCLUSIONS: These findings suggest that dynamic HMGA2 expression contributes to morphological evolution and modulates immune responses through enhanced Tpex-cDCs engagement, serving as a potential marker for systemic therapy response in ccRCC. However, additional experimental studies are required to validate these mechanisms.

Humans↗

PubMed2026

Enhancer-mediated DDIT4 activation by SMYD2-dependent H3K4me1 promotes pazopanib resistance in clear cell renal cell carcinoma.

BACKGROUND: The progression and resistance to targeted therapy, including pazopanib, frequently lead to poor prognosis in clear cell renal cell carcinoma (ccRCC) patients. However, the underlying molecular mechanisms of these processes remain unclear. METHODS: In this study, we first performed RNA-seq to identify genes that were differentially expressed in both SMYD2-knockdown and pazopanib-resistant cells, indicating their potential role in SMYD2-mediated drug resistance. We analyzed TCGA-KIRC data and 150 patient samples to identify the relationship between SMYD2 and DDIT4 expression levels, as well as the prognostic significance of DDIT4. In vitro functional assays and murine models were applied to evaluate the effects of SMYD2 and DDIT4 on tumor growth and on pazopanib resistance. CUT&Tag and chromosome conformation capture (4 C) assays were applied to identify enhancers associated with SMYD2-mediated regulation of DDIT4, while the JASPAR database was utilized to predict transcription factors involved in the enhancer regulation. CRISPR-mediated enhancer deletion and ChIP-qPCR were subsequently performed to validate the regulatory roles of the identified enhancer and the transcription factor SPI1 in DDIT4 expression. RESULTS: Our study revealed that the expression level of DDIT4 is positively correlated with SMYD2. DDIT4 is highly expressed in renal cell carcinoma and is associated with poorer survival outcomes. Further research revealed that SMYD2 regulates H3K4me1 in a DDIT4 distal enhancer (chr10:72830412-72830891), promoting the recruitment of the transcription factor SPI1, thereby activating DDIT4 expression. We found that DDIT4 promotes the proliferation, metastasis, and pazopanib resistance of ccRCC, and DDIT4 knockdown enhances drug sensitivity in both in vitro and in vivo experiments. Furthermore, the SMYD2-DDIT4 axis activates the downstream STAT3 signaling pathway, thereby promoting tumor progression. In addition, DDIT4-related prognostic features showed potential associations with patient survival and predicted drug sensitivity in computational analyses. CONCLUSIONS: Our study identifies a previously unrecognized SMYD2-enhancer-DDIT4 regulatory axis, which promotes tumor progression and pazopanib resistance in ccRCC. These findings may provide potential therapeutic implications to overcome pazopanib resistance and improve treatment outcomes in ccRCC by targeting the SMYD2-enhancer-DDIT4 axis.

Carcinoma, Renal Cell↗

PubMed2025

Long-term oncologic outcomes of metastatic clear-cell renal cell carcinoma after local therapy alone.

PURPOSE: Oligometastatic clear-cell renal cell carcinoma (ccRCC) represents a heterogeneous entity that can, in select cases, be managed with primary tumor resection and complete local treatment at all metastatic sites, rendering a patient metastatic with no evidence of disease (M1 NED). M1 NED patients have improved overall survival, although previous cohorts are relatively small and heterogeneous. We sought to identify the natural history of M1 NED ccRCC to clinical trial findings and to optimize management strategies. MATERIALS AND METHODS: Patients with synchronous metastatic ccRCC treated with local therapy alone and considered radiographically M1 NED at our institution between 1989 and 2023 were retrospectively evaluated. Survival probabilities used a combination of Kaplan-Meier estimator, log-rank test, and multivariable Cox proportional hazards regression. When available, limited genomic data obtained using the MSK-IMPACT targeted panel was correlated with outcomes. RESULTS: 85 patients met inclusion criteria. One-year disease free survival (DFS) was 53% (95% CI: 42 to 63%). Sarcomatoid features predicted shorter DFS (HR 2.62, CI: 1.08, 6.34, P = 0.03). Time from first disease recurrence to second recurrence was longer among patients with initial DFS ≥2 years (median 42 vs. 15 months, log-rank P = 0.005). A total of 18 patients (21%) underwent targeted genomic sequencing; higher fraction of genome altered and CDKN2A copy number loss were associated with shorter DFS. Findings were limited by cohort size. CONCLUSIONS: Most M1 NED ccRCC patients will experience disease recurrence, although certain baseline risk factors appear to predict earlier recurrence. Prognostic biomarkers are needed to predict outcomes and facilitate patient management.

Humans↗

PubMed2026

Urinary multi-omics reveal non-invasive diagnostic biomarkers in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common kidney malignancy. Yet, no rapid, non-invasive biomarkers are available for diagnosis or screening. Urine represents an ideal analyte matrix due to its accessibility, low invasiveness, longitudinal sampling, and the kidney's central role in filtration. Here, we integrated proteomic, lipidomic, and metabolomic analyses of urine from ccRCC patients and controls to identify diagnostic biomarkers. Multi-omics profiling revealed urogenital metabolic dysregulation in ccRCC, including increased lipid metabolism, altered mitochondrial respiration signatures, and elevated urinary lipid content. We identified three urinary protein biomarkers: serum amyloid A1 (SAA1), haptoglobin (HP), and lipocalin 15 (LCN15). Using a parallel reaction monitoring mass spectrometry workflow, we developed a rapid and sensitive assay and combined these markers into a diagnostic UrineScore. The UrineScore achieved 0.96 in an area under the receiver operating characteristic curve analysis in the discovery cohort, and 0.95 in an independent validation cohort. Together, these results support the feasibility of multi-omics-guided urinary biomarker discovery and represent a step toward accessible diagnostic platforms for ccRCC.

Humans↗