Molecular and Metabolic Basis of Clear Cell Carcinoma of the Kidney

Activation of RHO-GTPase gene pattern correlates with adverse clinical outcome and immune microenvironment in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), the most prevalent renal cancer subtype, is frequently associated with poor prognosis. RHO-GTPase signaling genes have been implicated in tumor aggressiveness and unfavorable survival, but their potential in risk stratification and therapeutic guidance for ccRCC patients remains unexplored. Univariate regression identified prognostically relevant RHO-GTPase signaling genes, followed by consensus clustering for ccRCC subtype classification. LASSO regression selected key genes to construct a six-gene risk model. The model was evaluated for prognostic stratification, immune status, immunotherapy response, and chemotherapy sensitivity. Key genes were analyzed at the genomic, single-cell, and protein levels to explore underlying mechanisms. Among 62 prognostically relevant RHO-GTPase signaling genes, six (ARHGAP11B, NUF2, PLK1, CYFIP2, IQGAP2, and VAV3) were identified to form a robust prognostic signature. This model stratified patients into high- and low-risk groups, with high-risk patients demonstrating significantly worse outcomes. The model exhibited excellent predictive accuracy (AUC > 0.7 in training and validation cohorts). High-risk patients were characterized by an immunosuppressive microenvironment and reduced sensitivity to immunotherapy. Drug sensitivity analysis revealed 107 agents correlated with the risk score, underscoring therapeutic relevance. Mechanistically, the six key genes showed distinct expression patterns, cellular distribution, and positive correlation with VHL mutations, highlighting their potential as actionable drug targets. This study established a novel six-gene RHO-GTPase signaling model for predicting prognosis, immune status, and therapeutic responses in ccRCC, which offers potential for improving patient stratification and guiding personalized treatment strategies.

MED15 is upregulated by HIF-2α and promotes proliferation and metastasis in clear cell renal cell carcinoma via activation of SREBP-dependent fatty acid synthesis

Emerging evidence has highlighted that dysregulation of lipid metabolism in clear cell renal cell carcinoma (ccRCC) is associated with tumor development and progression. HIF-2α plays an oncogenic role in ccRCC and is involved in abnormal lipid accumulation. However, the underlying mechanisms between these two phenomena remain unknown. Here, MED15 was demonstrated to be a dominant factor for HIF-2α-dependent lipid accumulation and tumor progression. HIF-2α promoted MED15 transcriptional activation by directly binding the MED15 promoter region, and MED15 overexpression significantly alleviated the lipid deposition inhibition and malignant tumor behavior phenotypes induced by HIF-2α knockdown. MED15 was upregulated in ccRCC and predicted poor prognosis. MED15 promoted lipid deposition and tumor progression in ccRCC. Mechanistic investigations demonstrated that MED15 acts as SREBP coactivator directly interacting with SREBPs to promote SREBP-dependent lipid biosynthesis enzyme expression, and promotes SREBP1 and SREBP2 activation through the PLK1/AKT axis. Overall, we describe a molecular regulatory network that links MED15 to lipid metabolism induced by the SREBP pathway and the classic HIF-2α pathway in ccRCC. Efforts to target MED15 or inhibit MED15 binding to SREBPs as a novel therapeutic strategy for ccRCC may be warranted.

Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and treatment strategies for ccRCC. This study aims to create a pathomics model to predict OS in ccRCC patients. In this study, data from ccRCC patients in the TCGA database were used as a training set, with clinical data serving as a validation set. Pathological features were extracted from H&E-stained slides using PyRadiomics, and a pathomics model was constructed using the non-negative matrix factorization (NMF) algorithm. The model's predictive performance was assessed through Kaplan-Meier (KM) survival curves and Cox regression analysis. Additionally, differential gene expression, gene ontology (GO) enrichment analysis, immune infiltration, and mutational analysis were conducted to investigate the underlying biological mechanisms. A total of 368 pathomics features were extracted from H&E-stained slides of ccRCC patients, and a pathomics model comprising two subtypes (Cluster 1 and Cluster 2) was successfully constructed using the NMF algorithm. KM survival curves and Cox regression analysis revealed that Cluster 2 was associated with worse OS. A total of 76 differential genes were identified between the two subtypes, primarily involving extracellular matrix organization and structure. Immune-related genes, including CTLA4, CD80, and TIGIT, were highly expressed in Cluster 2, while the VHL and PBRM1 genes, along with mutations in the PI3K-Akt, HIF-1, and MAPK signaling pathways, exhibited mutation rates exceeding 40% in both subtypes. The machine learning-based pathomics model effectively predicts the OS of ccRCC patients and differentiates between subtypes. The critical roles of the immune-related gene CTLA4 and the PI3K-Akt, HIF-1, and MAPK signaling pathways offer new insights for further research on the molecular mechanisms, diagnosis, and treatment strategies for ccRCC.

Multi-center validation of an immune-related lncRNA signature for predicting survival and immune status of patients with renal cell carcinoma: an integrating machine learning-derived study

BACKGROUND

Long noncoding RNAs (lncRNAs) have been reported to play an important role in tumor immune modification. Nonetheless, the clinical implication of immune-associated lncRNAs in renal cell carcinoma (RCC) remains to be further explored.

METHODS

76 combinations of machine learning algorithms were integrated to develop and validate a machine learning-derived immune-related lncRNA signature (MDILS) in five independent cohorts (n = 801). We collected 28 published signatures and collated clinical variables for comparison with MDILS to verify its efficacy. Subsequently, molecular mechanisms, immune status, mutation landscape, and pharmacological profile were further investigated in different stratified patients.

RESULTS

Patients with high MDILS displayed worse overall survival than those with low MDILS. The MDILS could independently predict overall survival and convey robust performance across five cohorts. MDILS has a significantly better performance compared with traditional clinical variables and 28 published signatures. Patients with low MDILS exhibited more abundant immune infiltration and higher potency of immunotherapeutic response, while patients with high MDILS might be more sensitive to multiple chemotherapeutic drugs (e.g., sunitinib and axitinib).

CONCLUSION

MDILS is a robust and promising tool to facilitate clinical decision-making and precision treatment of RCC.

hsa_circ_0003596, as a novel oncogene, regulates the malignant behavior of renal cell carcinoma by modulating glycolysis

BACKGROUND

This research was planned to analyze hsa_circ_0003596 (circCOL5A1) and glycolysis-focused mechanisms in renal cell carcinoma (RCC).

METHODS

circCOL5A1, miR-370-5p, and PRKCSH levels were determined in RCC tissues and selected cell lines by RT-qPCR and/or Western blot. RCC cells after corresponding transfection were tested by colony formation assay, EdU assay, Transwell assay, and flow cytometry to analyze cell proliferation, invasion, migration, and apoptosis. Meanwhile, glycolysis in cells was evaluated by measuring glucose consumption, lactic acid, and ATP production, as well as immunoblotting for HK2 and PKM2. In addition, circCOL5A1 knockdown was performed in animal experiments to observe tumor growth and glycolysis. Finally, the ceRNA network between circCOL5A1, miR-370-5p, and PRKCSH was studied by luciferase reporter assay and RIP experiment.

RESULTS

circCOL5A1 and PRKCSH were highly expressed and miR-370-5p was poorly expressed in RCC. circCOL5A1 knockdown depressed RCC proliferation, invasion, migration, and glycolysis, and enhanced apoptosis. circCOL5A1 competitively adsorbed miR-370-5p. Artificial upregulation of miR-370-5p saved the pro-tumor effect of circCOL5A1 on RCC cells, as evidenced by suppression of tumor malignancy and glycolysis. miR-370-5p targeted PRKCSH. PRKCSH overexpression contributed to a reversal of the anti-tumor effect of circCOL5A1 silencing. Silencing circCOL5A1 inhibited RCC tumor growth and glycolysis.

CONCLUSIONS

circCOL5A1 regulates the malignant behavior of RCC by modulating glycolysis.

Prognosis and pain dissection of novel signatures in kidney renal clear cell carcinoma based on fatty acid metabolism-related genes

Renal cell carcinoma (RCC) is a malignant tumor that is characterized by the accumulation of intracellular lipid droplets. The prognostic value of fatty acid metabolism-related genes (FMGs) in RCC remains unclear. Alongside this insight, we collected data from three RCC cohorts, namely, The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts, and identified a total of 309 FMGs that could be associated with RCC prognosis. First, we determined the copy number variation and expression levels of these FMGs, and identified 52 overall survival (OS)-related FMGs of the TCGA-KIRC and the E-MTAB-1980 cohort data. Next, 10 of these genes-FASN, ACOT9, MID1IP1, CYP2C9, ABCD1, CPT2, CRAT, TP53INP2, FAAH2, and PTPRG-were identified as pivotal OS-related FMGs based on least absolute shrinkage and selection operator and Cox regression analyses. The expression of some of these genes was confirmed in patients with RCC by immunohistochemical analyses. Kaplan-Meier analysis showed that the identified FMGs were effective in predicting the prognosis of RCC. Moreover, an optimal nomogram was constructed based on FMG-based risk scores and clinical factors, and its robustness was verified by time-dependent receiver operating characteristic analysis, calibration curve analysis, and decision curve analysis. We have also described the biological processes and the tumor immune microenvironment based on FMG-based risk score classification. Given the close association between fatty acid metabolism and cancer-related pain, our 10-FMG signature may also serve as a potential therapeutic target with dual effects on ccRCC prognosis and cancer pain and, therefore, warrants further investigation.

Molecular subtypes based on cuproptosis regulators and immune infiltration in kidney renal clear cell carcinoma

Copper toxicity involves the destruction of mitochondrial metabolic enzymes, triggering an unusual mechanism of cell death called cuproptosis, which proposes a novel approach using copper toxicity to treat cancer. However, the biological function of cuproptosis has not been fully elucidated in kidney renal clear cell carcinoma (KIRC). Using the expression profile of 13 cuproptosis regulators, we first identified two molecular subtypes related to cuproptosis defined as "hot tumor" and "cold tumor", having different levels of biological function, clinical prognosis, and immune cell infiltration. We obtained three gene clusters using the differentially expressed genes between the two cuproptosis-related subtypes, which were associated with different molecular activities and clinical characteristics. Next, we developed and validated a cuproptosis prognostic model that included two genes (FDX1 and DBT). The calculated risk score could divide patients into high- and low-risk groups. The high-risk group had a poorer prognosis, lower level of immune infiltration, higher frequency of gene alterations, and greater levels of FDX1 methylation and limited DBT methylation. The risk score was also an independent predictive factor for overall survival in KIRC. The established nomogram calculating the risk score achieved a high predictive ability for the prognosis of individual patients (area under the curve: 0.860). We then identified small molecular inhibitors as potential treatments and analyzed the sensitivity to chemotherapy of the signature genes. Tumor immune dysfunction and exclusion (TIDE) showed that the high-risk group had a higher level of TIDE, exclusion and dysfunction that was lower than the low-risk group, while the microsatellite instability of the high-risk group was significantly lower. The results of two independent immunotherapy datasets indicated that cuproptosis regulators could influence the response and efficacy of immunotherapy in KIRC. Our study provides new insights for individualized and comprehensive therapy of KIRC.

Identification of subtypes of clear cell renal cell carcinoma and construction of a prognostic model based on fatty acid metabolism genes

Background: The effects of fatty acid metabolism in many tumors have been widely reported. Due to the diversity of lipid synthesis, uptake, and transformation in clear cell renal cell carcinoma (ccRCC) cells, many studies have shown that ccRCC is associated with fatty acid metabolism. The study aimed was to explore the impact of fatty acid metabolism genes on the prognosis and immunotherapy of ccRCC.

Methods: Two subtypes were distinguished by unsupervised clustering analysis based on the expression of 309 fatty acid metabolism genes. A prognostic model was constructed by lasso algorithm and multivariate COX regression analysis using fatty acid metabolism genes as the signatures. The tumor microenvironment between subtypes and between risk groups was further analyzed. The International Cancer Genome Consortium cohort was used for external validation of the model.

Results: The analysis showed that subtype B had a poorer prognosis and a higher degree of immune infiltration. The high-risk group had a poorer prognosis and higher tumor microenvironment scores. The nomogram could accurately predict patient survival.

Conclusion: Fatty acid metabolism may affect the prognosis and immune infiltration of patients with ccRCC. The analysis was performed to understand the potential role of fatty acid metabolism genes in the immune infiltration and prognosis of patients. These findings have implications for individualized treatment, prognosis, and immunization for patients with ccRCC.

Identification of Pathologic Grading-Related Genes Associated with Kidney Renal Clear Cell Carcinoma

Background. Renal epithelium lesions can cause renal cell carcinoma. This kind of tumor is common among all renal cancers with poor prognosis, of which more than 70% belong to kidney renal clear cell carcinoma. As the pathogenesis of KIRC has not been elucidated, it is necessary to be further explored. Methods. The Genomic Spatial Event database was used to obtain the analysis dataset (GSE126964) based on the GEO database, and The Cancer Genome Atlas was applied for KIRC data collection. edgeR and limma analyses were subsequently conducted to identify differentially expressed genes. Based on the systems biology approach of WGCNA, potential biomarkers and therapeutic targets of this disease were screened after the establishment of a gene coexpression network. GO and KEGG enrichment used cluster Profiler, enrichplot, and ggplot2 in the R software package. Protein-protein interaction network diagrams were plotted for hub gene collection via the STRING platform and Cytoscape software. Hub genes associated with overall survival time of KIRC patients were ultimately identified using the Kaplan-Meier plotter. Results. There were 1863 DEGs identified in total and ten coexpressed gene modules discovered using a WGCNA method. GO and KEGG analysis findings revealed that the most enrichment pathways included Notch binding, cell migration, cell cycle, cell senescence, apoptosis, focal adhesions, and autophagosomes. Twenty-seven hub genes were identified, among which FLT1, HNRNPU, ATP6V0D2, ATP6V1A, and ATP6V1H were positively correlated with OS rates of KIRC patients ( $p<0.05$ ). Conclusions. In conclusion, bioinformatic techniques can be useful tools for predicting the progression of KIRC. DEGs are present in both KIRC and normal kidney tissues, which can be considered the KIRC biomarkers.

Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

Background

Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC.

Methods

A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data.

Results

The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC.

Conclusion

These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

METTL14-mediated N6-methyladenosine modification of Pten mRNA inhibits tumour progression in clear-cell renal cell carcinoma

BACKGROUND

Clear-cell renal-cell carcinoma (ccRCC) is one of the leading causes of tumour-related death worldwide. Methyltransferase-like 14 (METTL14) is reported to regulate m6A modification in cancers. The aim of this study is to investigate the biological function and molecular mechanism of METTL14 in the pathogenesis of ccRCC.

METHODS

Quantitative real-time PCR (qRT-PCR), western blot and immunohistochemical (IHC) assays were used to detect the expression of METTL14 and Pten. METTL14 overexpression or knockdown was used in the in vitro and in vivo studies to investigate the biological functions of METTL14. m6A-RNA immunoprecipitation and RNA immunoprecipitation were used to investigate the m6A modification mediated by METTL14.

RESULTS

METTL14 expression was significantly down-regulated in ccRCC tissues. Functionally, upregulation of METTL14 inhibited ccRCC cells proliferation and migration in vitro. METTL14 overexpression significantly inhibited the activation of the phosphoinositide 3 kinase (PI3K)/AKT signalling pathway. Furthermore, phosphate and tension homology deleted on chromosome ten (Pten) is a target of METTL14. Overexpression of METTL14 increased the m6A enrichment of Pten, and promoted Pten expression. METTL14-enhanced Pten mRNA stability was dependent on YTHDF1.

CONCLUSIONS

METTL14-mediated m6A modification of Pten mRNA inhibited tumour progression, suggesting that METTL14 might be a potential prognostic biomarker and effective therapeutic target for ccRCC.

Complementary roles of surgery and systemic treatment in clear cell renal cell carcinoma

Standard-of-care management of renal cell carcinoma (RCC) indisputably relies on surgery for low-risk localized tumours and systemic treatment for poor-prognosis metastatic disease, but a grey area remains, encompassing high-risk localized tumours and patients with metastatic disease with a good-to-intermediate prognosis. Over the past few years, results of major practice-changing trials for the management of metastatic RCC have completely transformed the therapeutic options for this disease. Treatments targeting vascular endothelial growth factor (VEGF) have been the mainstay of therapy for metastatic RCC in the past decade, but the advent of immune checkpoint inhibitors has revolutionized the therapeutic landscape in the metastatic setting. Results from several pivotal trials have shown a substantial benefit from the combination of VEGF-directed therapy and immune checkpoint inhibition, raising new hopes for the treatment of high-risk localized RCC. The potential of these therapeutics to facilitate the surgical extirpation of the tumour in the neoadjuvant setting or to improve disease-free survival in the adjuvant setting has been investigated. The role of surgery for metastatic RCC has been redefined, with results of large trials bringing into question the paradigm of upfront cytoreductive nephrectomy, inherited from the era of cytokine therapy, when initial extirpation of the primary tumour did show clinical benefits. The potential benefits and risks of deferred surgery for residual primary tumours or metastases after partial response to checkpoint inhibitor treatment are also gaining interest, considering the long-lasting effects of these new drugs, which encourages the complete removal of residual masses.

The role of redox homeostasis biomarkers in clear cell renal cell carcinoma development and progression

The clear cell renal cell carcinoma (ccRCC) is the most frequent and the most aggresive subtype of renal cell carcinoma usually detected at an already advanced stage. It might even be observed as a metabolic disease since complex molecular changes and disturbed redox homeostasis are its hallmark. As certain changes are characteristic for tumorigenesis, while some other for metastatic disease, the identification of metabolic modifications could also point out the stage of tumor progression. Hypoxia inducible factor, as a factor regulating transcription of genes encoding glycolytic enzymes, as well as controlling lipid accumulation, has a particular place in ccRCC development. Additionaly, disturbed redox homeostasis induces the Keap1/Nrf2 pathway which further modulates the synthesis of phase-II detoxifying metabolism enzymes. The upregulation of glutathione transferases, Pi class especially, inhibits kinase-dependent apoptosis that is essential in tumor progression. Furthermore, hydrogen peroxide (H2O2) acts as a signaling molecule conveying redox signals, while superoxide dismutase, as well as glutathione peroxidase are enzymes involved in its production and degradation. Hence, the activity of these enzymes impacts hydrogen peroxide levels and consequentially the ability of ccRCC cells to evade negative effect of reactive oxygen species.

A Novel Radiogenomics Biomarker Based on Hypoxic-Gene Subset: Accurate Survival and Prognostic Prediction of Renal Clear Cell Carcinoma

Purpose

To construct a novel radiogenomics biomarker based on hypoxic-gene subset for the accurate prognostic prediction of clear cell renal cell carcinoma (ccRCC).

Materials and Methods

Initially, we screened for the desired hypoxic-gene subset by analysis using the GSEA database. Through univariate and multivariate cox regression hazard ratio analysis, survival-related hypoxia genes were identified, and a genomics signature was constructed in the TCGA database. Building on this, a hypoxia-gene related radiogenomics biomarker (prediction of hypoxia-genes signature by contrast-enhanced CT radiomics) was constructed in the TCIA-KIRC database by extracting features in the venous phase of contrast-enhanced CT images, selecting features using the mRMR and LASSO algorithms, and building logistic regression models. Finally, we validated the prognostic capability of the new biomarker for patients with ccRCC in an independent validation cohort at Huashan Hospital of Fudan University, Shanghai, China.

Results

The hypoxia-related genomics signature consisting of five genes (IFT57, PABPN1, RNF10, RNF19B and UBE2T) was shown to be significantly associated with survival for patients with ccRCC in the TCGA database, delineated by grouping of the signature expression as either low- or high-risk. In the TCIA database, we constructed a radiogenomics biomarker consisting of 13 radiomics features that were optimal predictors of hypoxia-gene signature expression levels (low- or high-risk) in patients at each institution, that demonstrated AUC values of 0.91 and 0.91 in the training and validation groups, respectively. In the independent validation cohort at Huashan Hospital, our radiogenomics biomarker was significantly associated with prognosis in patients with ccRCC (p=0.0059).

Conclusions

The novel prognostic radiogenomics biomarker that was constructed achieved excellent correlation with prognosis in both the cohort of TCGA/TCIA-KIRC database and the independent validation cohort of Huashan hospital patients with ccRCC. It is anticipated that this work may assist in clinical preferential treatment decisions and promote the process of precision theranostics in the future.

Analysis of Ferroptosis-Related Gene Expression and Prognostic Factors of Renal Clear Cell Carcinoma Based on TCGA Database

Introduction

Renal clear cell carcinoma (ccRCC) is a common tumor of the urinary system, most of which are primary malignant tumors with high metastatic rate and remaining incurable. Ferroptosis is a newly discovered form of iron-dependent programmed cell necrosis in recent years, which is inextricably linked to the occurrence and development of tumors progression. Due to the complexity of the interaction between genes in ccRCC, the research on the pathogenesis of ccRCC is still not remarkably accurate. Therefore, whether ferroptosis-related genes (FRGs) can play a role in predicting prognosis in ccRCC needs to be discussed.

Methods

We entered the Cancer Genome Mapping Project (TCGA) database and downloaded the relevant genes and clinical research data of ccRCC patients. Lasso Cox regression was used to construct a multi-gene prognostic model in the TCGA cohort. R language software was used for drawing pictures related to our study.

Results

Most of the genes involved in ferroptosis (86.2%) existing differences between the tumor and normal tissues in the TCGA public gene database. In terms of univariate Cox regression analysis, 20 differentially expressed genes (DEGs) were associated with prognosis and survival (P<0.05). A prognostic model of 12 FRGs was constructed, and patients were segmented into two different groups depending on how risky they are. Considering overall survival, the high-risk group is dramatically lower than the low-risk group (P<0.001). In multivariate Cox regression analysis, risk scores and stage turned out be an independent prognostic factor (P<0.001). GO and KEGG analysis and ssGSEA analysis of DEGs revealed that these genes were related to immune-related pathways (P<0.05).

Conclusion

This study established and identified the changes in FRGs expression and prognostic factors of ccRCC, which can be helpful for prognosis evaluation and clinical treatment of this disease.

Inhibition of KIF20A by transcription factor IRF6 affects the progression of renal clear cell carcinoma

BACKGROUND

Renal clear cell carcinoma (ccRCC) is one of the most common malignant tumors, whose incidence is increasing year by year. IRF6 plays an important role in the occurrence of tumors, although there is yet no report on its expression in ccRCC.

METHODS

The expression of IRF6 and KIF20A in ccRCC was predicted by GEPIA and HAP databases. In addition, GEPIA database predicted the relationship between IRF6 and KIF20A expressions and the pathological staging, overall survival, and disease-free survival of ccRCC. The possible binding sites of IRF6 and KIF20A promoters were predicted by JASPAR database and verified by luciferase and ChIP assays. The specific effects of IRF6 on ccRCC cell proliferation, invasion and apoptosis were subsequently examined at both cellular level and animal level.

RESULTS

The database predicted down-regulated IRF6 expression in renal carcinoma tissues and its correlation with poor prognosis. IRF6 overexpression inhibited cRCC cell proliferation, invasion and migration. In addition, up-regulated KIF20A expression in renal carcinoma tissues and its association with prognosis were also predicted. Interference with KIF20A inhibited the proliferation, invasion, and migration of ccRCC cells. Finally, we confirmed that KIF20A is a functional target of IRF6 and can partially reverse the effects of IRF6 on the proliferation, invasion and migration of ccRCC cells.

CONCLUSION

Inhibition of KIF20A by transcription factor IRF6 affects cell proliferation, invasion and migration in renal clear cell carcinoma.

A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma

Background

The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration.

Methods

Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature.

Results

Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature.

Conclusions

A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients’ survival.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08111-0.

Bioinformatics analysis and verification of gene targets for renal clear cell carcinoma

BACKGROUND

It is estimated that there are 338,000 new renal-cell carcinoma releases every year in the world. Renal cell carcinoma (RCC) is a heterogeneous tumor, of which more than 70% is clear cell renal cell carcinoma (ccRCC). It is estimated that about 30% of new renal-cell carcinoma patients have metastases at the time of diagnosis. However, the pathogenesis of renal clear cell carcinoma has not been elucidated. Therefore, it is necessary to further study the pathogenesis of ccRCC.

METHODS

Two expression profiling datasets (GSE68417, GSE71963) were downloaded from the GEO database. Differentially expressed genes (DEGs) between ccRCC and normal tissue samples were identified by GEO2R. Functional enrichment analysis was made by the DAVID tool. Protein-protein interaction (PPI) network was constructed. The hub genes were excavated. The clustering analysis of expression level of hub genes was performed by UCSC (University of California Santa Cruz) Xena database. The hub gene on overall survival rate (OS) in patients with ccRCC was performed by Kaplan-Meier Plotter. Finally, we used the ccRCC renal tissue samples to verify the hub genes.

RESULTS

1182 common DEGs between the two datasets were identified. The results of GO and KEGG analysis revealed that variations in were predominantly enriched in intracellular signaling cascade, oxidation reduction, intrinsic to membrane, integral to membrane, nucleoside binding, purine nucleoside binding, pathways in cancer, focal adhesion, cell adhesion molecules. 10 hub genes ITGAX, CD86, LY86, TLR2, TYROBP, FCGR2A, FCGR2B, PTPRC, ITGB2, ITGAM were identified. FCGR2B and TYROBP were negatively correlated with the overall survival rate in patients with ccRCC (P < 0.05). RT-qPCR analysis showed that the relative expression levels of CD86, FCGR2A, FCGR2B, TYROBP, LY86, and TLR2 were significantly higher in ccRCC samples, compared with the adjacent renal tissue groups.

CONCLUSIONS

In summary, bioinformatics technology could be a useful tool to predict the progression of ccRCC. In addition, there are DEGs between ccRCC tumor tissue and normal renal tissue, and these DEGs might be considered as biomarkers for ccRCC.

Targeting glycolysis with 2-deoxy-D-glucose sensitizes primary cell cultures of renal cell carcinoma to tyrosine kinase inhibitors

PURPOSE

To investigate the synergistic effect of glycolysis inhibition on therapy answer to tyrosine kinase inhibitors in renal carcinoma.

METHODS

Primary cell cultures from 33 renal tumors including clear cell RCC (ccRCC), papillary RCC and the rare subtype chromophobe RCC as well as two metastases of ccRCC were obtained and cultivated. The patient-derived cells were verified by immunohistochemistry. CcRCC cells were further examined by exon sequencing of the von Hippel-Lindau gene (VHL) and by RNA-sequencing. Next, cell cultures of all subtypes of RCC were exposed to increasing doses of various tyrosine kinase inhibitors (axitinib, cabozantinib and pazopanib) and the glycolysis inhibitor 2-deoxy-D-glucose, alone or combined. CellTiter-Glo^® Luminescence assay and Crystal Violet staining were used to assess the inhibition of glycolysis and the viability of the cultured primary cells.

RESULTS

The cells expressed characteristic tissue markers and, in case of ccRCC cultures, the VHL status of the tumor they derived from. An upregulation of HK1, PFKP and SLC2A1 was observed, while components of the respiratory chain were downregulated, confirming a metabolic shift towards aerobic glycolysis. The tumors displayed variable individual responses for the therapeutics. All subtypes of RCC were susceptible to cabozantinib treatment indicated by decreased proliferation. Adding 2-deoxy-D-glucose to tyrosine kinase inhibitors decreased ATP production and increased the susceptibility of ccRCC to pazopanib treatment.

CONCLUSION

This study presents a valuable tool to cultivate even uncommon and rare renal cancer subtypes and allows testing of targeted therapies as a personalized approach as well as testing new therapies such as glycolysis inhibition in an in vitro model.

MUC15 inhibits cancer metastasis via PI3K/AKT signaling in renal cell carcinoma

Patients with renal cell carcinoma (RCC) often develop distant metastasis and the specific molecular mechanism remains poorly understood. In our study, we demonstrated that MUC15, a subtype of mucins family, could suppress the progression of RCC by inhibiting PI3K/AKT signaling. Firstly, we observed that MUC15 was notably decreased in RCC compared to normal tissue. Furthermore, we showed that MUC15 could negatively modulate the migration and invasion of RCC in vitro and in vivo. Mechanistically, we found that knocking-down of MUC15 could active the PI3K/AKT signaling by increasing the AKT phosphorylation and subsequently increase the mRNA and protein expression of MMP2 and MMP9. Interruption of the AKT pathway with the specific inhibitor LY294002 could reverse the expression of MMPs. Therefore, our study clarify the novel function of MUC15 in RCC, which may provide a new sight to diagnose and prevent RCC metastasis.

Calpastatin participates in the regulation of cell migration in BAP1-deficient uveal melanoma cells

AIM

To detect how BRCA-associated protein 1 (BAP1) regulates cell migration in uveal melanoma (UM) cells.

METHODS

Wound healing and transwell assays were performed to detect UM cell migration abilities. Protein chip, immunoprecipitations and surface plasmon resonance analyses were applied to identify BAP1 protein partners. Western blot and calpain activity assays were used to test the expression and function of calpastatin (CAST).

RESULTS

CAST protein was confirmed as a new BAP1 protein partner, and loss of BAP1 reduced the expression and function of CAST in UM cells. The overexpression of CAST rescued the cell migration phenotype caused by BAP1 loss.

CONCLUSION

BAP1 interacts with CAST in UM cells, and CAST and its subsequent calpain pathway may mediate BAP1-related cell migration regulation.

The mRNA Expression Signature and Prognostic Analysis of Multiple Fatty Acid Metabolic Enzymes in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is a metabolic disease, and accumulating evidences indicate significant alterations in the cellular metabolism, especial aerobic glycolysis and glutamine metabolism, in RCC. However, fatty acid (FA) metabolism has received less attention, and the mRNA expression pattern and prognostic role of FA metabolic enzymes in clear cell RCC (ccRCC) have not been carefully examined. In the current study, we first investigated the mRNA expression profiles of multiple FA metabolic enzymes, i.e., ACLY, ACC, FASN, SCD, CPT1A, HADHA, HADHB, and ACAT1, in 42 ccRCC and 33 normal kidney tissues using the Oncomine database, validated their mRNA expression profiles using GEPIA resource, then evaluated and validated the prognostic significance of these metabolic enzymes in 530 ccRCC patients using Kaplan-Meier plotter and GEPIA analyses respectively. The Oncomine and GEPIA confirmed higher ACLY, SCD, and lower ACAT1 mRNA expression in ccRCC than normal tissues (P<0.05). And further prognostic analysis displayed that overexpression of the some FA anabolic enzymes (FASN) was correlated to poor overall survival (OS), while overexpression of the FA catabolic enzymes (CPT1A, HADHA, HADHB, and ACAT1) was correlated to favorable OS in ccRCC patients. In conclusion, multiple FA metabolic enzymes, such as FASN, HADHA, and ACAT1, were potential prognostic markers of ccRCC, which implied alterations in FA metabolism might be involved in ccRCC tumorigenesis and progression.

microRNA-505 negatively regulates HMGB1 to suppress cell proliferation in renal cell carcinoma

microRNAs have been recognized to regulate a wide range of biology of renal cell carcinoma (RCC). Although miR-505 has been reported to play as a suppressor in several human tumors, the physiological function of miR-505 in RCC still remain unknown. Therefore, the role of miR-505 and relevant regulatory mechanisms were investigated in RCC in this study. Quantitative real-time polymerase chain reaction was conducted to detect the expression of miR-505 and high mobility group box 1 (HMGB1) in both RCC tissues and cell lines. Immunohistochemical staining was used to assess the correlation between HMGB1 expression and PCNA expression in RCC tissues. Subsequently, the effects of miR-505 on proliferation were determined in vitro using cell counting kit-8 proliferation assays and 5-ethynyl-2'-deoxyuridine incorporation. The molecular mechanism underlying the relevance between miR-505 and HMGB1 was confirmed by luciferase assay. Xenograft tumor formation was used to reflect the proliferative capacity of miR-505 in vivo experiments. Overall, a relatively lower miR-505 and higher HMGB1 expression in RCC specimens and cell lines were found. HMGB1 was verified as a direct target of miR-505 by luciferase assay. In vitro, overexpression of miR-505 negatively regulates HMGB1 to suppress the proliferation in Caki-1; meanwhile, knock-down of miR-505 negatively regulates HMGB1 to promote the proliferation in 769P. In addition, in vivo overexpression of miR-505 could inhibit tumor cell proliferation in RCC by xenograft tumor formation. Therefore, miR-505, as a tumor suppressor, negatively regulated HMGB1 to suppress the proliferation in RCC, and might serve as a novel therapeutic target for RCC clinical treatment.

Prognostic significance of VHL, HIF1A, HIF2A, VEGFA and p53 expression in patients with clear‑cell renal cell carcinoma treated with sunitinib as first‑line treatment

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell cancer, characterized by the highest mortality rate among other RCC subtypes due to the occurrence of metastasis and drug resistance following surgery. The Von Hippel-Lindau tumor suppressor (VHL)-hypoxia-inducible factor 1 subunit α (HIF1A)/hypoxia-inducible factor 2α (HIF2A)-vascular endothelial growth factor A (VEGFA) protein axis is involved in the development and progression of ccRCC, whereas sunitinib, a tyrosine kinase inhibitor, blocks the binding of VEGFA to its receptor. The aim of the present study was to examine the possible association of the gene expression of VHL, HIF1A, HIF2A, VEGFA and tumor protein P53 (P53) in cancer tissue with the outcome of ccRCC patients who were treated with sunitinib as first-line therapy following nephrec-tomy. A total of 36 ccRCC patients were enrolled, 11 of whom were administered sunitinib post-operatively. Tumor and control samples were collected, and mRNA and protein levels were assessed by reverse transcription-quantitative polymerase chain reaction and western blot analysis, respectively. High mRNA and protein expression levels of HIF2A and VEGFA were found to be associated with shorter overall survival (OS) and progression-free survival (PFS) rates, as well as with unfavorable risk factors of cancer recurrence and mortality. Resistance to sunitinib was also observed; the OS and PFS rates were shorter (median OS and PFS: 12 and 6 months, respectively, vs. undetermined). Sunitinib resistance was associated with high HIF2A and VEGFA protein levels (b=0.57 and b=0.69 for OS and PFS, respectively; P<0.001). Taken together, the findings of this study suggest that the protein levels of HIF2A and VEGFA in tumor tissue may serve as independent prognostic factors in ccRCC. ccRCC patients with increased intratumoral HIF2A and VEGFA protein levels, and unaltered VHL protein levels, are not likely to benefit from sunitinib treatment following nephrectomy; however, this hypothesis requires verification by large-scale replication studies.

Renal Cell Carcinoma With Hemangioma-Like Features: Diagnostic Implications and Review of the Literature

Renal cell carcinoma (RCC) with clear cell morphology may show a prominent delicate vascularity. In this article, we report the morphologic and immunohistochemical features of a clear cell papillary RCC mimicking hemangioblastoma and a clear cell RCC mimicking hemangioma. Case 1 showed tubular and papillary growth of clear cells with distinctive areas of capillary proliferation and admixed stromal-like cells resembling a hemangioblastoma. Case 2 consisted of homogeneously delicate microvascular proliferations resembling a capillary hemangioma with scattered inconspicuous clear cells. The clear cells of Case 1 were PAX8(+), CK7(diffuse+), CA9(diffuse+, cup-shaped), and inhibin A(−). The hemangioblastoma-like areas were PAX8(+), CK7(−), CA9(diffuse+), and inhibin A(diffuse+). Case 2 showed PAX8(+), CK7(−), and CA9(diffuse+). They can be diagnostically challenging, and it is important to recognize that a pure hemangioma or hemangioblastoma of the kidneys is very rare, and that RCCs with clear cell morphology rarely exhibit hemangioma-like characteristics.

Mutations in renal cell carcinoma

Renal cell carcinoma (RCC) is a commonly diagnosed and histologically diverse urologic malignancy. Clear cell RCC (ccRCC) is by far the most common, followed by the papillary and chromophobe subtypes. Sarcomatoid differentiation is a morphologic change that can be seen in all subtypes that typically portends a poor prognosis. In the past, treatment options for RCC were limited to cytokine-based therapy with a high-toxicity profile and low response rate. An increased understanding of the molecular basis of RCC has led to substantial improvement in treatment options in the form of targeted therapy and immunotherapy. A significant early discovery in RCC was frequent inactivation of the Von Hippel Lindau gene in ccRCC, which ultimately led to the development of vascular endothelial growth factor and mammalian target of rapamycin inhibitors. Further genomic sequencing of ccRCC tumors has identified other common mutations including BAP-1, PBRM1, SETD2, and PIK3CA. Many recent studies have explored how these mutations can affect prognosis and response to treatment. Likewise, papillary RCC has also been studied at the molecular level, which has shown a high level of mutations in the MET gene; early clinical data suggest the utility of MET targeted therapy. Finally, regarding the rarer sarcomatoid tumors, mutations in TP53 and NF2 may be important to their development. As we continue to learn more about what drives RCC at the molecular level, treatment options for RCC patients are diversifying.