External Validation of a Five-Tiered CT Algorithm for the Diagnosis of Clear Cell Renal Cell Carcinoma: A Retrospective Five-Reader Study

BACKGROUND. In 2022, a five-tiered CT algorithm was proposed for predicting whether a small (cT1a) solid renal mass represents clear cell renal cell carcinoma (ccRCC). OBJECTIVE. The purpose of this external validation study was to evaluate the proposed CT algorithm for diagnosis of ccRCC among small solid renal masses. METHODS. This retrospective study included 93 patients (median age, 62 years; 42 women, 51 men) with 97 small solid renal masses that were seen on corticomedullary phase contrast-enhanced CT performed between January 2012 and July 2022 and subsequently underwent surgical resection. Five readers (three attending radiologists, two clinical fellows) independently evaluated masses for the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score; these scores were used to derive the CT score by use of the previously proposed CT algorithm. The CT score's sensitivity, specificity, and PPV for ccRCC were calculated at threshold of 4 or greater, and the NPV for ccRCC was calculated at a threshold of 3 or greater (consistent with thresholds in studies of the MRI-based clear cell likelihood score and the CT algorithm's initial study). The CT score's sensitivity and specificity for papillary RCC were calculated at a threshold of 2 or less. Interreader agreement was assessed using the Gwet agreement coefficient (AC1). RESULTS. Overall, 61 of 97 masses (63%) were malignant and 43 of 97 (44%) were ccRCC. Across readers, CT score had sensitivity ranging from 47% to 95% (pooled sensitivity, 74% [95% CI, 68-80%]), specificity ranging from 19% to 83% (pooled specificity, 59% [95% CI, 52-67%]), PPV ranging from 48% to 76% (pooled PPV, 59% [95% CI, 49-71%]), and NPV ranging from 83% to 100% (pooled NPV, 90% [95% CI, 84-95%]), for ccRCC. A CT score of 2 or less had sensitivity ranging from 44% to 100% and specificity ranging from 77% to 98% for papillary RCC (representing nine of 97 masses). Interreader agreement was substantial for attenuation score (AC1 = 0.70), poor for heterogeneity score (AC1 = 0.17), fair for five-tiered CT score (AC1 = 0.32), and fair for dichotomous CT score at a threshold of 4 or greater (AC1 = 0.24 [95% CI, 0.14-0.33]). CONCLUSION. The five-tiered CT algorithm for evaluation of small solid renal masses was tested in an external sample and showed high NPV for ccRCC. CLINICAL IMPACT. The CT algorithm may be used for risk stratification and patient selection for active surveillance by identifying patients unlikely to have ccRCC.

LncRNA PVT1 promotes strong stemness and endothelial progenitor cell characteristics in renal carcinoma stem cells

Renal cancer stem cells (RCSCs) derived from clear cell renal cell carcinoma (ccRCC) tissues with higher microvessel density (MVD) have strong stemness and endothelial progenitor cells-like (EPCs-like) characteristics. A high level of lncRNA PVT1 expression is essential for simultaneously retaining strong RCSC stemness and EPCs-like characteristics. PVT1 binds with TAZ protein and prevents its phosphorylation, which promotes RCSC stemness. Moreover, RCSCs support endothelial differentiation and angiogenesis, which are mediated via the PVT1/miR-15b/KDR axis. This report provides insight into the determinants of RCSC impact on stemness and highlights the critical role of RCSC in angiogenesis. The presented findings suggest that targeting RCSC through PVT1 expression may be a new treatment strategy for ccRCC.

Integrating bioinformatic analysis and detailed experiments reveal an EMT-related biomarker for clear cell renal cell carcinoma

BACKGROUND

Epithelial-mesenchymal transition (EMT) is associated with early recurrence and a poor prognosis in clear cell renal cell carcinoma (ccRCC). Studies have shown that EMT-related genes play an important regulatory role in tumor invasion, metastasis, and drug resistance, but the biological functions of EMT-related genes in ccRCC have not been specifically described.

METHODS

The mRNA and clinicopathological data of 532 ccRCC and 72 normal samples were downloaded from The Cancer Genome Atlas as a training set. The gene expression matrix and survival data of 91 and 101 ccRCC samples were obtained from the International Cancer Genome Consortium and the ArrayExpress databases as validation sets, respectively. Univariate Cox analysis was used to identify and cluster prognostic genes, and multivariate Cox was performed to construct a prognostic signature. Moreover, CIBERSORT and CellMiner were used to assess immune cell infiltration and prognostic gene-drug sensitivity of the signature, respectively. Most importantly, we performed detailed experiments to verify the oncogenic function of a significant gene, OLFML2B, in vitro and in vivo.

RESULTS

We constructed a prognostic signature including seven genes and divided patients into high-risk and low-risk groups. The prognosis of the high-risk group was significantly worse than that of the low-risk group through Kaplan-Meier survival analysis. Interestingly, significant differences were observed in clinical characteristics and immune cell infiltration between the two groups. In addition, a significant correlation was found between the expression of prognostic genes and the sensitivity of tumor cells to chemotherapeutics. Most importantly, OLFML2B was proved to contribute to the proliferation and metastasis of ccRCC through detailed functional experiments in vitro and in vivo, and its prognostic efficacy for ccRCC patients was affirmed.

CONCLUSION

We identified the prognostic signature of seven genes based on EMT-related genes as prognostic biomarkers for ccRCC. Besides, OLFML2B was validated as a potential diagnostic and therapeutic target for ccRCC by our detailed experiments.

Protein Arginine Methyltransferases Refine the Classification of Clear Cell Renal Cell Carcinoma with Distinct Prognosis and Tumor Microenvironment Characteristics

Background: Clear cell renal cell carcinoma (ccRCC) is an aggressive urological cancer that originates from the proximal tubular epithelium. As one of the most common post-translational modification, protein arginine methylation plays a pivotal role in various cancer-associated biological functions, especially in cancer immunity. Therefore, constructing a protein arginine methylation-related prognostic signature would be beneficial in guiding better personalized clinical management for patients with ccRCC. Methods: Based on the multi-omics profiling of the expression levels of eight protein arginine methyltransferases (PRMTs) in 763 ccRCC samples (from TCGA, CPTAC, EMBL, and ICGC databases), we established a scoring system with machine-learning algorithms to quantify the modification patterns on clinical and immunological characterizations of individual ccRCC patient, which was termed as PRMTScore. Moreover, we utilized two external clinical cohorts receiving immunotherapy (n=302) to validate the reliability of the PRMTScore system. Multiplex immunohistochemistry (mIHC) was performed to characterize the cellular composition of 30 paired ccRCC samples. The proteomic profiling of 232 ccRCC samples obtained from Fudan University Shanghai Cancer Center (FUSCC) was analyzed to validate the protein expression of PRMT5 in ccRCC. Finally, CCK-8, transwell, and wound healing assays were conducted to elucidate the role of PRMT5 in ccRCC in vitro. Results: A total of 763 ccRCC patients with available multi-omics profiling were stratified into two clusters (PRMTCluster A and B) with distinctive prognosis, genomic alterations, tumor microenvironment (TME) characteristics, and fundamental biological mechanisms. Subsequently, protein arginine methylation-related prognostic signature (PRMTScore) was constructed and consisted of SLC16A12, HRH2, F2RL3, and SAA1. The PRMTScore showed remarkable differences in outcomes, immune and stromal fractions, expressions of immune checkpoints, the abundance of immune cells, and immunotherapy response in ccRCC patients. Additionally, preliminary insights unveiled the tumor-suppressive role of PRMT5 in ccRCC, and the signal of PRMT5low significantly predicted aggressive prognosis and the high abundance of PD1+ CD8+ cells in ccRCC. Conclusion: We constructed a PRMTScore system, which showed the potent ability to assess the prognosis, TME characteristics, and immunotherapy response for patients with ccRCC. Moreover, this is the first study to propose that PRMT5 acts as a cancer suppressor in ccRCC.

Immune-related risk prognostic model for clear cell renal cell carcinoma: Implications for immunotherapy

Clear cell renal cell carcinoma (ccRCC) is associated with complex immune interactions. We conducted a comprehensive analysis of immune-related differentially expressed genes in patients with ccRCC using data from The Cancer Genome Atlas and ImmPort databases. The immune-related differentially expressed genes underwent functional and pathway enrichment analysis, followed by COX regression combined with LASSO regression to construct an immune-related risk prognostic model. The model comprised 4 IRGs: CLDN4, SEMA3G, CAT, and UCN. Patients were stratified into high-risk and low-risk groups based on the median risk score, and the overall survival rate of the high-risk group was significantly lower than that of the low-risk group, confirming the reliability of the model from various perspectives. Further comparison of immune infiltration, tumor mutation load, and immunophenoscore (IPS) comparison between the 2 groups indicates that the high-risk group could potentially demonstrate a heightened sensitivity towards immunotherapy checkpoints PD-1, CTLA-4, IL-6, and LAG3 in ccRCC patients. The proposed model not only applies to ccRCC but also shows potential in developing into a prognostic model for renal cancer, thus introducing a novel approach for personalized immunotherapy in ccRCC.

Decreased Expression of GLYATL1 Predicts Poor Prognosis in Patients with Clear Cell Renal Cell Carcinoma

Background

GLYATL1 is a member of the glycine-N-acyltransferase family, which catalyses acyl group transfer. The role of GLYATL1 in cancer is largely unknown; therefore, the potential value of GLYATL1 in clear cell renal cell carcinoma (ccRCC) was explored.

Methods

The ccRCC gene expression profiles and clinical data were obtained from the University of California Santa Cruz Xena platform. Differential expression and survival analysis were performed using R software. Samples from the TIMER public database and real-world were used for validation. The potential molecular mechanism of GLYATL1 in ccRCC was explored using gene set enrichment analysis (GSEA).

Results

GLYATL1 was downregulated, indicating a poor prognosis in ccRCC. Low expression of GLYATL1 was significantly associated with advanced stage and higher histological grade ccRCC. The differential expression of GLYATL1 was validated at the protein level using clinical samples and tissue microarray. The results of GSEA showed that multiple crucial signalling pathways including fatty acid metabolism, adipogenesis, oxidative phosphorylation and epithelial-mesenchymal transition were enriched.

Conclusion

This study demonstrated that GLYATL1 downregulation has an unfavourable impact on the survival of patients with ccRCC. The resulting data indicated that GLYATL1 could be a potential new target for ccRCC therapy, which may be helpful for the personalized treatment of such individuals.

Identification and validation of SERPINE1 as a prognostic and immunological biomarker in pan-cancer and in ccRCC

Background: SERPINE1, a serine protease inhibitor involved in the regulation of the plasminogen activation system, was recently identified as a cancer-related gene. However, its clinical significance and potential mechanisms in pan-cancer remain obscure. Methods: In pan-cancer multi-omics data from public datasets, including The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and online web tools were used to analyze the expression of SERPINE1 in different cancers and its correlation with prognosis, genetic alteration, DNA promoter methylation, biological processes, immunoregulator expression levels, immune cell infiltration into tumor, tumor mutation burden (TMB), microsatellite instability (MSI), immunotherapy response and drug sensitivity. Further, two single-cell databases, Tumor Immune Single-cell Hub 2 (TISCH2) and CancerSEA, were used to explore the expression and potential roles of SERPINE1 at a single-cell level. The aberrant expression of SERPINE1 was further verified in clear cell renal cell carcinoma (ccRCC) through qRT-PCR of clinical patient samples, validation in independent cohorts using The Gene Expression Omnibus (GEO) database, and proteomic validation using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Results: The expression of SERPINE1 was dysregulated in cancers and enriched in endothelial cells and fibroblasts. Copy number amplification and low DNA promoter methylation could be partly responsible for high SERPINE1 expression. High SERPINE1 expression was associated with poor prognosis in 21 cancers. The results of gene set enrichment analysis (GSEA) indicated SERPINE1 involvement in the immune response and tumor malignancy. SERPINE1 expression was also associated with the expression of several immunoregulators and immune cell infiltration and could play an immunosuppression role. Besides, SERPINE1 was found to be related with TMB, MSI, immunotherapy response and sensitivity to several drugs in cancers. Finally, the high expression of SERPINE1 in ccRCC was verified using qRT-PCR performed on patient samples, six independent GEO cohorts, and proteomic data from the CPTAC database. Conclusion: The findings of the present study revealed that SERPINE1 exhibits aberrant expression in various types of cancers and is associated with cancer immunity and tumor malignancy, providing novel insights for individualized cancer treatment.

Multi-phase-combined CECT radiomics models for Fuhrman grade prediction of clear cell renal cell carcinoma

Objective

This study aimed to evaluate the effectiveness of multi-phase-combined contrast-enhanced CT (CECT) radiomics methods for noninvasive Fuhrman grade prediction of clear cell renal cell carcinoma (ccRCC).

Methods

A total of 187 patients with four-phase CECT images were retrospectively enrolled and then were categorized into training cohort (n=126) and testing cohort (n=61). All patients were confirmed as ccRCC by histopathological reports. A total of 110 3D classical radiomics features were extracted from each phase of CECT for individual ccRCC lesion, and contrast-enhanced variation features were also calculated as derived radiomics features. These features were concatenated together, and redundant features were removed by Pearson correlation analysis. The discriminative features were selected by minimum redundancy maximum relevance method (mRMR) and then input into a C-support vector classifier to build multi-phase-combined CECT radiomics models. The prediction performance was evaluated by the area under the curve (AUC) of receiver operating characteristic (ROC).

Results

The multi-phase-combined CECT radiomics model showed the best prediction performance (AUC=0.777) than the single-phase CECT radiomics model (AUC=0.711) in the testing cohort (p value=0.039).

Conclusion

The multi-phase-combined CECT radiomics model is a potential effective way to noninvasively predict Fuhrman grade of ccRCC. The concatenation of first-order features and texture features extracted from corticomedullary phase and nephrographic phase are discriminative feature representations.

Prognostic and tumor microenvironmental feature of clear cell renal cell carcinoma revealed by m6A and lactylation modification-related genes

Background

Both lactylation and m6A modification have important implications for the development of clear cell renal cell carcinoma (ccRCC), and we aimed to use crosstalk genes of both to reveal the prognostic and immunological features of ccRCC.

Methods

Our first step was to look for lactylation-related genes that differed between normal and tumor tissues, and then by correlation analysis, we found the genes associated with M6A. Following that, ccRCC subtypes will be identified and risk models will be constructed to compare the prognosis and tumor microenvironment among different subgroups. A nomogram was constructed to predict the prognosis of ccRCC, and in vitro, experiments were conducted to validate the expression and function of key genes.

Results

We screened 100 crosstalk genes and identified 2 ccRCC subtypes. A total of 11 prognostic genes were screened for building a risk model. we observed higher immune scores, elevated tumor mutational burden, and microsatellite instability scores in the high-risk group. Therefore, individuals classified as high-risk would derive greater benefits from immunotherapy. The nomogram's ability to predict overall survival with a 1-year AUC of 0.863 demonstrates its significant practical utility. In addition, HIBCH was identified as a potential therapeutic target and its expression and function were verified by in vitro experiments.

Conclusion

In addition to developing a precise prognostic nomogram for patients with ccRCC, our study also discovered the potential of HIBCH as a biomarker for the disease.

Characterization of papillary and clear cell renal cell carcinoma through imaging mass cytometry reveals distinct immunologic profiles

Objective

To characterize and further compare the immune cell populations of the tumor microenvironment (TME) in both clear cell and papillary renal cell carcinoma (RCC) using heavy metal-labeled antibodies in a multiplexed imaging approach (imaging mass cytometry).

Materials and methods

Formalin-fixed paraffin-embedded (FFPE) baseline tumor tissues from metastatic patients with clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) were retrospectively requisitioned from an institutional biorepository. Pretreated FFPE samples from 33 RCC patients (10 ccRCC, 23 pRCC) were accessioned and stained for imaging mass cytometry (IMC) analysis. Clinical characteristics were curated from an institutional RCC database. FFPE samples were prepared and stained with heavy metal-conjugated antibodies for IMC. An 11-marker panel of tumor stromal and immune markers was used to assess and quantify cellular relationships in TME compartments. To validate our time-of-flight (CyTOF) analysis, we cross-validated findings with The Cancer Genome Atlas Program (TCGA) analysis and utilized the CIBERSORTx tool to examine the abundance of main immune cell types in pRCC and ccRCC patients.

Results

Patients with ccRCC had a longer median overall survival than did those with pRCC (67.7 vs 26.8 mo, respectively). Significant differences were identified in the proportion of CD4+ T cells between disease subtypes (ccRCC 14.1%, pRCC 7.0%, p<0.01). Further, the pRCC cohort had significantly more PanCK+ tumor cells than did the ccRCC cohort (24.3% vs 9.5%, respectively, p<0.01). There were no significant differences in macrophage composition (CD68+) between cohorts. Our results demonstrated a significant correlation between the CyTOF and TCGA analyses, specifically validating that ccRCC patients exhibit higher levels of CD4+ T cells (ccRCC 17.60%, pRCC 15.7%, p<0.01) and CD8+ T cells (ccRCC 17.83%, pRCC 11.15%, p<0.01). The limitation of our CyTOF analysis was the large proportion of cells that were deemed non-characterizable.

Conclusions

Our findings emphasize the need to investigate the TME in distinct RCC histological subtypes. We observed a more immune infiltrative phenotype in the TME of the ccRCC cohort than in the pRCC cohort, where a tumor-rich phenotype was noted. As practical predictive biomarkers remain elusive across all subtypes of RCC, further studies are warranted to analyze the biomarker potential of such TME classifications.

Recent Advances in Renal Tumors with TSC/mTOR Pathway Abnormalities in Patients with Tuberous Sclerosis Complex and in the Sporadic Setting

A spectrum of renal tumors associated with frequent TSC/mTOR (tuberous sclerosis complex/mechanistic target of rapamycin) pathway gene alterations (in both the germline and sporadic settings) have recently been described. These include renal cell carcinoma with fibromyomatous stroma (RCC FMS), eosinophilic solid and cystic renal cell carcinoma (ESC RCC), eosinophilic vacuolated tumor (EVT), and low-grade oncocytic tumor (LOT). Most of these entities have characteristic morphologic and immunohistochemical features that enable their recognition without the need for molecular studies. In this report, we summarize recent advances and discuss their evolving complexity.

Prognostic significance and mechanisms of CXCL genes in clear cell renal cell carcinoma

This study aimed to investigate the clinical significance, biological functions, and underlying mechanisms of CXCL genes in clear cell renal cell carcinoma (ccRcc) based on patient datasets and pan-cancer analysis. The interaction between CXCL genes in ccRcc and immune components, particularly in relation to neutrophil recruitment and polarization mechanisms, was also evaluated. Furthermore, a risk score was developed using a signature for neutrophil polarization. The role of CXCL2 was assessed through in vitro experiments. Results showed that five CXCL genes (CXCL 2, 5, 9, 10, and 11) were upregulated in renal cancer tissue, while seven genes (CXCL 1, 2, 3, 5, 8, 13, and 14) significantly impacted patient survival. Moreover, CXCL 1, 5, and 13 affected progression-free survival. Besides, differences in mRNA expression and immune components affected renal cancer outcomes. Furthermore, three pairs of CXCL gene-immune cell interactions (CXCL13-CD8+ T cells, CXCL9/10-M1 cells, CXCL1/2/3/8-neutrophils) were identified through single-cell and pan-cancer analysis. A TAN risk score with prognostic value for KIRC patients was constructed using 11 genes and a TAN signature. Neutrophil polarization significantly impacted survival. Notably, CXCL2 was involved in neutrophil recruitment and polarization, thus promoting ccRcc progression. In conclusion, seven prognostic CXCL genes (CXCL 1/2/3/5/8/13/14) for ccRcc patients and three pairs of CXCL gene-immune cell interactions were identified. Furthermore, results showed that CXCL 2 promotes ccRcc progression through neutrophil recruitment and polarization.

A novel oxidative stress-related genes signature associated with clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Background

Oxidative stress plays a significant role in the tumorigenesis and progression of tumors. We aimed to develop a prognostic signature using oxidative stress-related genes (ORGs) to predict clinical outcome and provide light on the immunotherapy responses of clear cell renal cell carcinoma (ccRCC).

Methods

The information of ccRCC patients were collected from the TCGA and the E-MTAB-1980 datasets. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) were conducted to screen out overall survival (OS)-related genes. Then, an ORGs risk signature was built by multivariate Cox regression analyses. The performance of the risk signature was evaluated with Kaplan-Meier (K-M) survival. The ssGSEA and CIBERSORT algorithms were performed to evaluate immune infiltration status. Finally, immunotherapy responses was analyzed based on expression of several immune checkpoints.

Results

A prognostic 9-gene signature with ABCB1, AGER, E2F1, FOXM1, HADH, ISG15, KCNMA1, PLG, and TEK. The patients in the high risk group had apparently poor survival (TCGA: p < 0.001; E-MTAB-1980: p < 0.001). The AUC of the signature was 0.81 at 1 year, 0.76 at 3 years, and 0.78 at 5 years in the TCGA, respectively, and was 0.8 at 1 year, 0.82 at 3 years, and 0.83 at 5 years in the E-MTAB-1980, respectively. Independent prognostic analysis proved the stable clinical prognostic value of the signature (TCGA cohort: HR = 1.188, 95% CI =1.142-1.236, p < 0.001; E-MTAB-1980 cohort: HR =1.877, 95% CI= 1.377-2.588, p < 0.001). Clinical features correlation analysis proved that patients in the high risk group were more likely to have a larger range of clinical tumor progression. The ssGSEA and CIBERSORT analysis indicated that immune infiltration status were significantly different between two risk groups. Finally, we found that patients in the high risk group tended to respond more actively to immunotherapy.

Conclusion

We developed a robust prognostic signature based on ORGs, which may contribute to predict survival and guide personalize immunotherapy of individuals with ccRCC.

Six-transmembrane epithelial antigen of prostate 3 (STEAP3) is a potential prognostic biomarker in clear cell renal cell carcinoma that correlates with M2 macrophage infiltration and epithelial-mesenchymal

BACKGROUND

The six-transmembrane epithelial antigen of the prostate 3 (STEAP3) is a metalloreductase, which is essential for iron uptake. Existing literature has shown that STEAP3 may perform an important role in the onset and progression of tumors. Nonetheless, a complete pan-cancer investigation of the prognostic significance and immune properties of STEAP3 is currently unavailable.

AIMS

As part of our investigation into the possible functions of STEAP3 in malignancies, we conducted a comprehensive analysis to examine the prognostic value and immune features of STEAP3 in human pan-cancer.

METHODS AND RESULTS

R and Cytoscape programs were applied to analyze and visualize the data. The expression of STEAP3 in both cell lines and tissues was measured utilizing a variety of approaches. Using the shRNA knockdown technique, we tested the viability of the A498 and 786-O cell lines and validated their functions. Both CCK-8 and transwell assays were conducted to estimate cell proliferation and invasion. The expression of STEAP3 was substantially elevated and was shown to be linked to prognosis in the majority of malignancies, notably in clear cell renal cell carcinoma (ccRCC). In addition, the expression of STEAP3 was shown to have a strong correlation with immune infiltrates, which in turn triggered the recruitment and polarization of M2 macrophages in ccRCC. The protein STEAP3 shows promise as a predictor of responses to immune-checkpoint blockade (ICB) therapy. Positive links between STEAP3 and the epithelial-mesenchymal transition (EMT), the p53 pathway, and the immune-associated pathways were also found in the enrichment analysis. Our results illustrated that the STEAP3 expression level was substantially elevated in ccRCC tissues and suggested that it could stimulate EMT in ccRCC by downregulating CDH1.

CONCLUSION

In a diverse range of cancers, STEAP3 might serve as a biomarker for determining the prognosis as well as a predictor of immunotherapy responsiveness. STEAP3 is a novel biological marker for determining prognosis, and it also performs a remarkable function in the promotion of tumor growth in ccRCC by enhancing invasion and EMT, as well as by triggering the recruitment and polarization of M2 macrophages.

Clear Cell Renal Cell Carcinoma with Hemangioblastoma-Like Features: A Case Report

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) constitutes the most frequently encountered sporadic class of kidney cancer in adults. Recently, a rare form of clear cell kidney cancer known as ccRCC with hemangioblastoma-like features was proposed, with unique immunological characteristics and a good prognosis. The tumor expressed alpha-inhibin and carbonic anhydrase Ⅸ (CA9) as examined by immunohistochemistry.

METHODS

Herein, we report a clinical instance of ccRCC with hemangioblastoma-like features. A 49-year-old woman presenting with a chief complaint of hematuria underwent a comprehensive and meticulous assessment. Imaging findings indicated the presence of a mass in the right kidney. Subsequently, she underwent a partial nephrectomy.

RESULTS

Histopathological analysis of the resected specimen confirmed the presence of ccRCC with hemangioblastoma-like features. The patient was discharged from the hospital six days post-surgery and could resume her daily activities. During a one-year follow-up after surgery, no signs of recurrence were detected.

CONCLUSIONS

This case demonstrates the importance of including ccRCC with hemangioblastoma-like features in the differential diagnosis of renal masses in patients with hematuria, and suggests partial nephrectomy as an effective treatment modality for this rare subtype of renal cell carcinoma. However, because of the small number of reported cases and insufficient follow-up time, further investigation is necessary to determine the optimal therapeutic approach and to identify the molecular and genetic characteristics of this tumor.

Development and validation of a prognostic model incorporating tumor thrombus grading for nonmetastatic clear cell renal cell carcinoma with tumor thrombus: A multicohort study

There is significant variability with respect to the prognosis of nonmetastatic clear cell renal cell carcinoma (ccRCC) patients with venous tumor thrombus (VTT). By applying multiregion whole-exome sequencing on normal-tumor-thrombus-metastasis quadruples from 33 ccRCC patients, we showed that metastases were mainly seeded by VTT (81.8%) rather than primary tumors (PTs). A total of 706 nonmetastatic ccRCC patients with VTT from three independent cohorts were included in this study. C-index analysis revealed that pathological grading of VTT outperformed other indicators in risk assessment (OS: 0.663 versus 0.501-0.610, 0.667 versus 0.544-0.651, and 0.719 versus 0.511-0.700 for Training, China-Validation, and Poland-Validation cohorts, respectively). We constructed a risk predicting model, TT-GPS score, based on four independent variables: VTT height, VTT grading, perinephric fat invasion, and sarcomatoid differentiation in PT. The TT-GPS score displayed better discriminatory ability (OS, c-index: 0.706-0.840, AUC: 0.788-0.874; DFS, c-index: 0.691-0.717, AUC: 0.771-0.789) than previously reported models in risk assessment. In conclusion, we identified for the first-time pathological grading of VTT as an unheeded prognostic factor. By incorporating VTT grading, the TT-GPS score is a promising prognostic tool in predicting the survival of nonmetastatic ccRCC patients with VTT.

[Retracted] MicroRNA‑599 targets high‑mobility group AT‑hook 2 to inhibit cell proliferation and invasion in clear cell renal carcinoma

Following the publication of the above paper, it was drawn to the Editors' attention by a concerned reader that cell migration and invasion assay data shown in Fig. 5C were strikingly similar to data appearing in different form in other articles by different authors, which have been retracted. Owing to the fact that the contentious data in the above article were already under consideration for publication, or had already been published, elsewhere when it was submitted to Molecular Medicine Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive any reply. The Editor apologizes to the readership for any inconvenience caused. [Molecular Medicine Reports 17: 7451‑7459, 2018; DOI: 10.3892/mmr.2018.8755].

Discovery of Gastric Metastases From Primary Renal Cell Carcinoma Through MRI: A Case Report

Gastric metastases from primary renal cell carcinoma (RCC) are rare and poorly documented in the existing literature. This case report presents the clinical course of a 65-year-old male with multi-metastatic clear cell RCC (ccRCC) who was incidentally found to have stomach metastases during follow-up magnetic resonance imaging (MRI). Gastric metastases from ccRCC are typically associated with other metastatic sites. They often emerge at an advanced stage of the disease, indicating a poor prognosis. It is therefore important to consider gastric metastases as a potential site of involvement in RCC patients. MRI revealed three gastric mucosal lesions exhibiting hypervascularity, a characteristic feature of ccRCC. Histological analysis confirmed the presence of malignant cells compatible with RCC.

Evaluation of therapeutic mechanism of Hedyotis diffusa Willd (HDW)‒Scutellaria barbata (SB) in clear cell renal cell carcinoma via single-cell RNA sequencing and network pharmacology

OBJECTIVE

The present study aimed to investigate the therapeutic mechanism of Hedyotis diffusa Willd (HDW) and Scutellaria barbata (SB) in ccRCC using a combination of single-cell RNA sequencing (scRNA-seq) and network pharmacology.

METHODS

The active ingredients and potential molecular targets of HDW-SB were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. Gene expression data (GSE53757) were obtained from the Gene Expression Omnibus database. The hub genes of HDW-SB against ccRCC were identified via the protein-protein interaction network, and further analyzed by molecular complex detection. The roles of these genes in the diagnosis and immune infiltration of ccRCC were analyzed. The clinical significance of hub genes was verified using scRNA-seq data (GSE121638) and molecular docking.

RESULTS

Following the PPI network analysis, 29 hub genes of HDW-SB against ccRCC were identified. All hub genes, except for CENPE, had significantly different expressions in tumor tissue and a more accurate diagnosis of ccRCC. Fifteen cell clusters were defined based on the scRNA-seq dataset, and the clusters were annotated as six cell types using marker genes. TYMS and KIAA0101 from hub genes were highly expressed in NK cells. Three active compounds, quercetin, luteolin, and baicalein, were found to target TYMS and KIAA0101 from the compound-target interaction network.

CONCLUSION

29 hub genes of HDW-SB against ccRCC were identified and showed good performance in terms of diagnosis and prognosis. Moreover, among these hub genes docking with the main ingredients of HDW-SB, TYMS and KIAA0101 exerted anti-ccRCC effects through NK cells.

Preoperative Inflammation-Associated Blood Cell Markers in Patients with Non-Metastatic Clear Cell Renal Cell Carcinoma: A Retrospective Study

Purpose

This study aimed to investigate the association between preoperative inflammation-associated blood cell markers and the prognosis of patients with non-metastatic clear cell renal cell carcinoma (ccRCC) who underwent nephrectomy.

Patients and Methods

We retrospectively analyzed data from our single-center cohort of patients who underwent radical or partial nephrectomy for non-metastatic ccRCC. The optimal cutoff values for red blood cell distribution width (RDW), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR) were determined using X-tile software. We evaluated recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS) using the Kaplann-Meier method. Cox proportional-hazards regression models were utilized to assess predictors of RFS, CSS, and OS. The predictive accuracy was evaluated using Harrell's Concordance Index (C-index).

Results

A total of 444 patients who underwent nephrectomy were included in the study. The optimal cutoff values for RDW, PLR, NLR, and LMR were determined as 13.1, 157.3, 3.4, and 2.7, respectively. On univariate Cox regression analysis, NLR, PLR, and LMR were significant predictors for RFS, CSS, and OS. After adjusting for important prognostic factors, only NLR remained a significant prognostic marker for both CSS and OS. When NLR was added to the stage, size, grade, and necrosis (SSIGN) model, the C-index increased from 0.777 to 0.826 for CSS and from 0.703 to 0.734 for OS. Similarly, when NLR was added to the University of California, Los Angeles, Integrated Staging System (UISS), the C-index increased from 0.796 to 0.811 for CSS and from 0.735 to 0.745 for OS.

Conclusion

NLR is a reliable prognostic biomarker for patients with non-metastatic ccRCC. The prognostic capabilities of UISS and SSIGN models could be improved by adding NLR to UISS and SSIGN models.

Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis

Introduction: Clear cell renal cell carcinoma (ccRCC) is associated with unfavorable clinical outcomes. To identify viable therapeutic targets, a comprehensive understanding of intratumoral heterogeneity is crucial. In this study, we conducted bioinformatic analysis to scrutinize single-cell RNA sequencing data of ccRCC tumor and para-tumor samples, aiming to elucidate the intratumoral heterogeneity in the ccRCC tumor microenvironment (TME). Methods: A total of 51,780 single cells from seven ccRCC tumors and five para-tumor samples were identified and grouped into 11 cell lineages using bioinformatic analysis. These lineages included tumor cells, myeloid cells, T-cells, fibroblasts, and endothelial cells, indicating a high degree of heterogeneity in the TME. Copy number variation (CNV) analysis was performed to compare CNV frequencies between tumor and normal cells. The myeloid cell population was further re-clustered into three major subgroups: monocytes, macrophages, and dendritic cells. Differential expression analysis, gene ontology, and gene set enrichment analysis were employed to assess inter-cluster and intra-cluster functional heterogeneity within the ccRCC TME. Results: Our findings revealed that immune cells in the TME predominantly adopted an inflammatory suppression state, promoting tumor cell growth and immune evasion. Additionally, tumor cells exhibited higher CNV frequencies compared to normal cells. The myeloid cell subgroups demonstrated distinct functional properties, with monocytes, macrophages, and dendritic cells displaying diverse roles in the TME. Certain immune cells exhibited pro-tumor and immunosuppressive effects, while others demonstrated antitumor and immunostimulatory properties. Conclusion: This study contributes to the understanding of intratumoral heterogeneity in the ccRCC TME and provides potential therapeutic targets for ccRCC treatment. The findings emphasize the importance of considering the diverse functional roles of immune cells in the TME for effective therapeutic interventions.

NCOA7 Regulates Growth and Metastasis of Clear Cell Renal Cell Carcinoma via MAPK/ERK Signaling Pathway

NCOA7 is a nuclear receptor coactivator that is downregulated in a variety of cancers. However, the expression and prognostic significance of NCOA7 in clear cell renal cell carcinoma (ccRCC) remain unknown. The expression of NCOA7 in ccRCC tissues was analyzed using bioinformatics analysis, Western blotting, and immunohistochemistry. Kaplan-Meier analysis, the receiver operating characteristic (ROC) curve, and clinicopathological correlation analysis were used to assess the predictive power of NCOA7. Overexpression function tests were conducted in cells and mouse models to clarify the function and mechanism of NCOA7 in inhibiting the progression of ccRCC. NCOA7 expression was downregulated in all three subtypes of renal cell carcinoma, and only had significant prognostic value for patients with ccRCC. NCOA7 overexpression inhibited the proliferation, invasion, and metastasis of ccRCC cells in vivo and in vitro. Mechanistically, NCOA7 inhibited the MAPK/ERK pathway to regulate epithelial-mesenchymal transformation (EMT) and apoptosis, thereby inhibiting the progression of ccRCC. NCOA7 inhibits tumor growth and metastasis of ccRCC through the MAPK/ERK pathway, thus indicating its potential as a prognostic marker and therapeutic target for ccRCC.

High C1QTNF1 expression mediated by potential ncRNAs is associated with poor prognosis and tumor immunity in kidney renal clear cell carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) originates from proximal tubular cells and is the most common subtype of renal cell carcinoma. KIRC is characterized by changes in lipid metabolism, and obesity is a risk factor for it. C1q And TNF Related 1 (C1QTNF1), a novel adipokine and member of the C1q and TNF-related protein (CTRP) family, has been shown to affect the progression of various cancers. However, the role of C1QTNF1 in KIRC has not been studied. Methods: The Wilcoxon rank sum test was used to analyze the expression of C1QTNF1 in KIRC tissues and normal tissues. The relationship between clinicopathological features and C1QTNF1 levels was also examined by logistic regression and the Wilcoxon rank sum test. In addition, the effect of C1QTNF1 on the prognosis of KIRC patients was analyzed by Kaplan-Meier (KM). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the potential signaling pathways and biological functions of differential genes. A nomogram was constructed to predict the prognosis of KIRC patients. Spearman correlation analysis was performed to determine the association between C1QTNF1 expression and immune cell infiltration and immune checkpoint genes. The upstream miRNAs and lncRNAs of C1QTNF1 were predicted by the ENCORI online tool. Finally, we examined the proliferation, invasion, and migration abilities of KIRC cells after C1QTNF1 knockdown. Results: The expression of C1QTNF1 in KIRC tissues was significantly higher than in normal renal tissues. Patients with higher C1QTNF1 expression had a poor prognosis, a finding supported by Kaplan-Meier survival analysis. C1QTNF1 expression was significantly correlated with TNM and pathologic stages, age, and gender (p < 0.05). The C1QTNF1 expression level was significantly correlated with immune cell infiltration and immune checkpoint genes in KIRC. Additionally, high C1QTNF1 expression was associated with poor prognosis in stage I and II, T1 and T2, T3 and T4, N0, and M0 patients (HR > 1, p < 0.05). The calibration diagram shows that the C1QTNF1 model has effective predictive performance for the survival of KIRC patients. Knockdown of C1QTNF1 inhibited KIRC cell proliferation, cell migration, and cell invasion. In addition, CYTOR and AC040970.1/hsa-miR-27b-3p axis were identified as the most likely upstream ncRNA-related pathways of C1QTNF1 in KIRC. Conclusion: In conclusion, our study suggests that high expression of C1QTNF1 is associated with KIRC progression and immune infiltration. The increased expression of C1QTNF1 suggests a poor prognosis in KIRC patients.

Prognostic value of neutrophil extracellular trap signature in clear cell renal cell carcinoma

Introduction

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of urological carcinoma. Although targeted therapy and immunotherapy are usually employed, they often result in primary and acquired resistance. There is currently a lack of dependable biomarkers that can accurately anticipate the prognosis of ccRCC. Recent research has indicated the critical role of neutrophil extracellular traps (NETs) in the development, metastasis, and immune evasion of cancer. The aim of this study was to explore the value of NETs in the development and prognosis of ccRCC.

Methods

Clinical features and genetic expression information of ccRCC patients were acquired from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and E-MTAB-1980 database. NETs-related gene set were obtained from previous studies. A NETs-related gene signature was constructed based on TCGA data and validated using ICGC and E-MTAB-1980 databases. Furthermore, the immune microenvironment and responsiveness to anticancer medications in ccRCC patients with varying levels of NETs risks were investigated.

Results

A total of 31 NET-related genes were differently expressed between normal kidney and ccRCC tissues. 17 out of 31 were significantly associated with overall survival. After LASSO Cox regression analysis, nine NETs-related genes were enrolled to construct the NETs prognosis signature, and all the ccRCC patients from TCGA were divided into low and high risk group. This signature demonstrated excellent performance in predicting the overall survival of TCGA patients as well as the validation ICGC and E-MTAB-1980 patients. Additionally, the NETs signature was significantly correlated with immune infiltration and drug sensitivity.

Conclusions

The NETs signature established by the current study has prognostic significance in ccRCC, and may serve as a useful biomarker for patient stratification and treatment decisions. Further validation and clinical studies are required to fully translate these findings into clinical practice.

A reactive oxygen species-related signature to predict prognosis and aid immunotherapy in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a malignant disease containing tumor-infiltrating lymphocytes. Reactive oxygen species (ROS) are present in the tumor microenvironment and are strongly associated with cancer development. Nevertheless, the role of ROS-related genes in ccRCC remains unclear.

Methods

We describe the expression patterns of ROS-related genes in ccRCC from The Cancer Genome Atlas and their alterations in genetics and transcription. An ROS-related gene signature was constructed and verified in three datasets and immunohistochemical staining (IHC) analysis. The immune characteristics of the two risk groups divided by the signature were clarified. The sensitivity to immunotherapy and targeted therapy was investigated.

Results

Our signature was constructed on the basis of glutamate-cysteine ligase modifier subunit (GCLM), interaction protein for cytohesin exchange factors 1 (ICEF1), methionine sulfoxide reductase A (MsrA), and strawberry notch homolog 2 (SBNO2) genes. More importantly, protein expression levels of GCLM, MsrA, and SBNO2 were detected by IHC in our own ccRCC samples. The high-risk group of patients with ccRCC suffered lower overall survival rates. As an independent predictor of prognosis, our signature exhibited a strong association with clinicopathological features. An accurate nomogram for improving the clinical applicability of our signature was constructed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the signature was closely related to immune response, immune activation, and immune pathways. The comprehensive results revealed that the high-risk group was associated with high infiltration of regulatory T cells and CD8+ T cells and more benefited from targeted therapy. In addition, immunotherapy had better therapeutic effects in the high-risk group.

Conclusion

Our signature paved the way for assessing prognosis and developing more effective strategies of immunotherapy and targeted therapy in ccRCC.

Prediction of Distant Metastases in Patients with Kidney Cancer Based on Gene Expression and Methylation Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common and aggressive histological type of cancer in this location. Distant metastases are present in approximately 30% of patients at the time of first examination. Therefore, the ability to predict the occurrence of metastases in patients at early stages of the disease is an urgent task aimed at personalized treatment. Samples of tumor and paired histologically normal kidney tissue from patients with metastatic and non-metastatic ccRCC were studied. Gene expression was analyzed using real-time PCR. The level of gene methylation was evaluated using bisulfite conversion followed by quantitative methylation-specific PCR. Two groups of genes were analyzed in this study. The first group includes genes whose expression is significantly reduced during metastasis: CA9, NDUFA4L2, EGLN3, and BHLHE41 (p < 0.001, ROC analysis). The second group includes microRNA genes: MIR125B-1, MIR137, MIR375, MIR193A, and MIR34B/C, whose increased methylation levels are associated with the development of distant metastases (p = 0.002 to <0.001, ROC analysis). Based on the data obtained, a combined panel of genes was formed to identify patients whose tumors have a high metastatic potential. The panel can estimate the probability of metastasis with an accuracy of up to 92%.

Inter- and intra-tumor heterogeneity of genetic and immune profiles in inherited renal cell carcinoma

Patients with von Hippel-Lindau disease (vHL) are at risk of developing spatially and temporally multiple clear cell renal cell carcinomas (ccRCCs), which offers a valuable opportunity to analyze inter- and intra-tumor heterogeneity of genetic and immune profiles within the same patient. Here, we perform whole-exome and RNA sequencing, digital gene expression, and immunohistochemical analyses for 81 samples from 51 ccRCCs of 10 patients with vHL. Inherited ccRCCs are clonally independent and have less genomic alterations than sporadic ccRCCs. Hierarchical clustering of transcriptome profiles shows two clusters with distinct immune signatures: immune hot and cold clusters. Interestingly, not only samples from the same tumors but also different tumors from the same patients tend to show a similar immune signature, whereas samples from different patients frequently exhibit different signatures. Our findings reveal the genetic and immune landscape of inherited ccRCCs, demonstrating the relevance of host factors in shaping anti-tumor immunity.

LINC01480 as a Prognostic Biomarker Associated With Proliferation, Migration, and Invasion of Clear Cell Renal Cell Carcinoma

BACKGROUND/AIM

The present study aimed to identify key long noncoding RNAs (lncRNAs) involved in survival and metastasis of clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

A systemic screening for genes with differential expression in ccRCC was performed using publicly available databases. Cox regression analysis was used to identify lncRNAs associated with survival. A competing endogenous RNAs (ceRNA) regulation network of metastasis-related lncRNAs was constructed and hub lncRNAs were identified. Functional and pathway enrichment analyses were performed to investigate the role of lncRNA in ccRCC. Cell Counting Kit-8 and Transwell assays were used to determine the levels of cell proliferation, migration, and invasion.

RESULTS

A total of 732 lncRNAs were found to be differentially expressed between ccRCC tumors and healthy samples. Among them, 139 lncRNAs were differentially expressed between metastasis and non-metastasis ccRCC samples and 75 lncRNAs were associated with overall survival and curated metastasis-related genes. Notably, LINC01480 was identified as the hub lncRNA involved in regulation of ccRCC metastasis. Clinically, LINC01480 may act as an independent factor for poor overall survival of ccRCC patients (log-rank p<0.05). Reverse transcription-quantitative PCR analysis validated that LINC01480 was significantly up-regulated in ccRCC compared to paired normal samples (n=20). Moreover, LINC01480 silencing inhibited the proliferation, migration, and invasion of ccRCC cells in vitro. Gene set enrichment analysis showed that high LINC01480 expression may promote ccRCC metastasis through enhancing immunodeficiency and amino acid metabolism.

CONCLUSION

LINC01480 may act as a novel biomarker for overall prognosis in ccRCC and exhibit potential as a therapeutic target for the treatment of metastatic ccRCC.

An integrative multi-omics analysis based on disulfidptosis-related prognostic signature and distinct subtypes of clear cell renal cell carcinoma

Background

The association between clear cell renal cell carcinoma (ccRCC) and disulfidoptosis remains to be thoroughly investigated.

Methods

We conducted multiple bioinformatics analyses, including prognostic analysis and cluster analysis, using R software. Additionally, we utilized Quantitative Real-time PCR to measure RNA levels of specific genes. The proliferation of ccRCC was assessed through CCK8 and colony formation assays, while the invasion and migration of ccRCC cells were evaluated using the transwell assay.

Results

In this study, utilizing data from multiple ccRCC cohorts, we identified molecules that contribute to disulfidoptosis. We conducted a comprehensive investigation into the prognostic and immunological roles of these molecules. Among the disulfidoptosis-related metabolism genes (DMGs), LRPPRC, OXSM, GYS1, and SLC7A11 exhibited significant correlations with ccRCC patient prognosis. Based on our signature, patients in different groups displayed varying levels of immune infiltration and different mutation profiles. Furthermore, we classified patients into two clusters and identified multiple functional pathways that play important roles in the occurrence and development of ccRCC. Given its critical role in disulfidoptosis, we conducted further analysis on SLC7A11. Our results demonstrated that ccRCC cells with high expression of SLC7A11 exhibited a malignant phenotype.

Conclusions

These findings enhanced our understanding of the underlying function of DMGs in ccRCC.

Exploring the Characteristics of Circulating Tumor DNA in Pt1a Clear Cell Renal Cell Carcinoma: A Pilot Study

Circulating tumor DNA (ctDNA) is a promising biomarker for clear cell renal cell carcinoma (ccRCC); however, its characteristics in small renal masses of ccRCC remain unclear. In this pilot study, we explored the characteristics of ctDNA in pT1a ccRCC. Plasma samples were collected preoperatively from 53 patients with pT1a ccRCC. The ctDNA of pT1a ccRCC was profiled using next-generation sequencing and compared with that of higher-stage ccRCC. The association of ctDNA in pT1a ccRCC with clinicopathological features was investigated. The positive relationship of mutations between ctDNA and matched tissues was evaluated. In pT1a ccRCC, the ctDNA detection rate, cell-free DNA concentration, and median variant allele frequency were 20.8%, 5.8 ng/mL, and 0.38%, respectively, which were significantly lower than those in metastatic ccRCC. The ctDNA gene proportions in pT1a samples differed from those in metastatic ccRCC samples. The relationships between ctDNA and tumor size, tumor grade, and patient age were not elucidated. The positive concordance between ctDNA and matched tissues was poor for pT1a ccRCC. Strategies are needed to increase sensitivity while eliminating noise caused by clonal hematopoiesis to increase the clinical utility of ctDNA analysis in small renal masses of ccRCC.

Establishing a prognostic model based on five starvation-related long non-coding RNAs for clear cell renal cell carcinoma

BACKGROUND

Starvation-induced tumor microenvironment significantly alters genetic profiles including long non-coding RNAs (lncRNAs), further regulating the malignant biological characteristics (invasion and migration) of clear cell renal cell carcinoma (ccRCC).

METHODS

Transcriptome RNA-sequencing data of 539 ccRCC tumors and 72 normal tissues were acquired from the TCGA and paired clinical samples of 50 ccRCC patients. In vitro experiments, such as qPCR, migration and invasion assays were applied to reveal the clinical relevance of LINC-PINT, AC108449.2 and AC007637.1.

RESULTS

170 lncRNAs were verified as starvation-related lncRNAs (SR-LncRs), of which 25 lncRNAs were associated with overall survival in ccRCC patients. Furthermore, a starvation-related risk score model (SRSM) was built based on the expression levels of LINC-PINT, AC108449.2, AC009120.2, AC008702.2 and AC007637.1. ccRCC patients with high level of LINC-PINT expression were divided into high-risk group and led to higher mortality, but AC108449.2 and AC007637.1 were contrary. Analogously, LINC-PINT was highly expressed in ccRCC cell lines and tumor tissues, especially in patients with advanced stage, T-stage and M-stage, while AC108449.2 and AC007637.1 showed the opposite results. In addition, the increased levels of AC108449.2 and AC007637.1 were significantly correlated with grade. Silencing LINC-PINT reduced the invasion and migration characteristics of ccRCC cells. SiR-AC108449.2 and siR-AC007637.1 enhanced the ability of invasion and migration in ccRCC cells.

CONCLUSIONS

In this study, we find the clinical significance of LINC-PINT, AC108449.2 and AC007637.1 in predicting the prognosis of ccRCC patients and verify their correlation with various clinical parameters. These findings provide an advisable risk score model for ccRCC clinical decision-making.

Recent Advances in the Management of Clear Cell Renal Cell Carcinoma: Novel Biomarkers and Targeted Therapies

Renal cell carcinoma (RCC) belongs to a heterogenous cancer group arising from renal tubular epithelial cells. Among RCC subtypes, clear cell renal cell carcinoma (ccRCC) is the most common variant, characterized by high aggressiveness, invasiveness and metastatic potential, features that lead to poor prognosis and high mortality rate. In addition, diagnosis of kidney cancer is incidental in the majority of cases, and this results in a late diagnosis, when the stage of the disease is advanced and the tumor has already metastasized. Furthermore, ccRCC treatment is complicated by its strong resistance to chemo- and radiotherapy. Therefore, there is active ongoing research focused on identifying novel biomarkers which could be useful for assessing a better prognosis, as well as new molecules which could be used for targeted therapy. In this light, several novel targeted therapies have been shown to be effective in prolonging the overall survival of ccRCC patients. Thus, the aim of this review is to analyze the actual state-of-the-art on ccRCC diagnosis, prognosis and therapeutic options, while also reporting the recent advances in novel biomarker discoveries, which could be exploited for a better prognosis or for targeted therapy.

A Weakly Supervised Deep Learning Model and Human-Machine Fusion for Accurate Grading of Renal Cell Carcinoma from Histopathology Slides

(1) Background: The Fuhrman grading (FG) system is widely used in the management of clear cell renal cell carcinoma (ccRCC). However, it is affected by observer variability and irreproducibility in clinical practice. We aimed to use a deep learning multi-class model called SSL-CLAM to assist in diagnosing the FG status of ccRCC patients using digitized whole slide images (WSIs). (2) Methods: We recruited 504 eligible ccRCC patients from The Cancer Genome Atlas (TCGA) cohort and obtained 708 hematoxylin and eosin-stained WSIs for the development and internal validation of the SSL-CLAM model. Additionally, we obtained 445 WSIs from 188 ccRCC eligible patients in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) cohort as an independent external validation set. A human-machine fusion approach was used to validate the added value of the SSL-CLAM model for pathologists. (3) Results: The SSL-CLAM model successfully diagnosed the five FG statuses (Grade-0, 1, 2, 3, and 4) of ccRCC, and achieved AUCs of 0.917 and 0.887 on the internal and external validation sets, respectively, outperforming a junior pathologist. For the normal/tumor classification (Grade-0, Grade-1/2/3/4) task, the SSL-CLAM model yielded AUCs close to 1 on both the internal and external validation sets. The SSL-CLAM model achieved a better performance for the two-tiered FG (Grade-0, Grade-1/2, and Grade-3/4) task, with AUCs of 0.936 and 0.915 on the internal and external validation sets, respectively. The human-machine diagnostic performance was superior to that of the SSL-CLAM model, showing promising prospects. In addition, the high-attention regions of the SSL-CLAM model showed that with an increasing FG status, the cell nuclei in the tumor region become larger, with irregular contours and increased cellular pleomorphism. (4) Conclusions: Our findings support the feasibility of using deep learning and human-machine fusion methods for FG classification on WSIs from ccRCC patients, which may assist pathologists in making diagnostic decisions.

Case report: A rare case of tumor-to-tumor metastasis: metastatic lobular breast carcinoma to clear cell renal cell carcinoma

Tumor-to-tumor metastasis is a rare phenomenon. Although renal cell carcinoma is the most common recipient tumor, metastatic lobular breast carcinoma to clear cell renal cell carcinoma is even rarer, with only one case reported to date. We present a 66-year-old female patient with an invasive lobular carcinoma history who was admitted to the hospital with a right renal mass. The patient received partial nephrectomy. The final established diagnosis is lobular breast carcinoma metastasizing to clear cell renal cell carcinoma (ccRCC). Thus, although rare, the simultaneous or consecutive find of a renal mass in follow-up should be carefully evaluated, especially in high-risk patients, including women with an advanced breast cancer history, as in this scenario.

Biological Biomarkers of Response and Resistance to Immune Checkpoint Inhibitors in Renal Cell Carcinoma

Renal cell carcinoma (RCC) represents around 2% of cancer-related deaths worldwide per year. RCC is an immunogenic malignancy, and treatment of metastatic RCC (mRCC) has greatly improved since the advent of the new immunotherapy agents, including immune checkpoint inhibitors (ICIs). However, it should be stressed that a large proportion of patients does not respond to these therapies. There is thus an urgent need to identify predictive biomarkers of efficacy or resistance associated with ICIs or ICI/Tyrosine kinase inhibitor (TKI) combinations; this is a major challenge to achieve precision medicine for mRCC in routine practice. To identify potential biomarkers, it is necessary to improve our knowledge on the biology of immune checkpoints. A lot of efforts have been made over the last decade in the field of immuno-oncology. We summarize here the main data obtained in this field when considering mRCC. As for clinical biomarkers, clinician and scientific experts of the domain are facing difficulties in identifying such molecular entities, probably due to the complexity of immuno-oncology and the constant adaptation of tumor cells to their changing environment.

Predicting prognosis, immunotherapy and distinguishing cold and hot tumors in clear cell renal cell carcinoma based on anoikis-related lncRNAs

Background

Clear cell renal cell carcinoma (ccRCC) is the most frequently occurring malignant tumor within the kidney cancer subtype. It has low sensitivity to traditional radiotherapy and chemotherapy, the optimal treatment for localized ccRCC has been surgical resection, but even with complete resection the tumor will be eventually developed into metastatic disease in up to 40% of localized ccRCC. For this reason, it is crucial to find early diagnostic and treatment markers for ccRCC.

Methods

We obtained anoikis-related genes (ANRGs) integrated from Genecards and Harmonizome dataset. The anoikis-related risk model was constructed based on 12 anoikis-related lncRNAs (ARlncRNAs) and verified by principal component analysis (PCA), Receiver operating characteristic (ROC) curves, and T-distributed stochastic neighbor embedding (t-SNE), and the role of the risk score in ccRCC immune cell infiltration, immune checkpoint expression levels, and drug sensitivity was evaluated by various algorithms. Additionally, we divided patients based on ARlncRNAs into cold and hot tumor clusters using the ConsensusClusterPlus (CC) package.

Results

The AUC of risk score was the highest among various factors, including age, gender, and stage, indicating that the model we built to predict survival was more accurate than the other clinical features. There was greater sensitivity to targeted drugs like Axitinib, Pazopanib, and Sunitinib in the high-risk group, as well as immunotherapy drugs. This shows that the risk-scoring model can accurately identify candidates for ccRCC immunotherapy and targeted therapy. Furthermore, our results suggest that cluster 1 is equivalent to hot tumors with enhanced sensitivity to immunotherapy drugs.

Conclusion

Collectively, we developed a risk score model based on 12 prognostic lncRNAs, expected to become a new tool for evaluating the prognosis of patients with ccRCC, providing different immunotherapy strategies by screening for hot and cold tumors.

LINC00493-encoded microprotein SMIM26 exerts anti-metastatic activity in renal cell carcinoma

Human microproteins encoded by long non-coding RNAs (lncRNA) have been increasingly discovered, however, complete functional characterization of these emerging proteins is scattered. Here, we show that LINC00493-encoded SMIM26, an understudied microprotein localized in mitochondria, is tendentiously downregulated in clear cell renal cell carcinoma (ccRCC) and correlated with poor overall survival. LINC00493 is recognized by RNA-binding protein PABPC4 and transferred to ribosomes for translation of a 95-amino-acid protein SMIM26. SMIM26, but not LINC00493, suppresses ccRCC growth and metastatic lung colonization by interacting with acylglycerol kinase (AGK) and glutathione transport regulator SLC25A11 via its N-terminus. This interaction increases the mitochondrial localization of AGK and subsequently inhibits AGK-mediated AKT phosphorylation. Moreover, the formation of the SMIM26-AGK-SCL25A11 complex maintains mitochondrial glutathione import and respiratory efficiency, which is abrogated by AGK overexpression or SLC25A11 knockdown. This study functionally characterizes the LINC00493-encoded microprotein SMIM26 and establishes its anti-metastatic role in ccRCC, and therefore illuminates the importance of hidden proteins in human cancers.

[Corrigendum] High expression of the secreted protein dickkopf homolog 4: Roles in invasion and metastasis of renal cell carcinoma and its association with Von Hippel-Lindau gene

Subsequently to the publication of the above paper, an interested reader drew to the authors' attention that the β-actin bands data shown to portray the control experiments in the western blots in Fig. 3C and 4F were apparently identical. The authors have re‑examined their data, and realize that the control bands in Fig. 3C had inadvertently been selected incorrectly. The revised version of Fig. 3, containing the correct β-actin bands in Fig. 3C, is shown below. Note that this error did not affect the major conclusions reported in the paper. All the authors agree with the publication of this corrigendum, and thank the Editor of International Journal of Molecular Medicine for allowing them the opportunity to publish this. The authors regret this mistake went unnoticed during the compilation of the figure in question, and apologize to the readership for any confusion that this may have caused. [International Journal of Molecular Medicine 33: 1319‑1326, 2014; DOI: 10.3892/ijmm.2014.1673].

Knocking down NSUN5 inhibits the development of clear cell renal cell carcinoma by inhibiting the p53 pathway

Clear cell renal cell carcinoma (ccRCC) is the most common solid renal tumor. NSUN5, a gene encoding cytosine-5 RNA methyltransferase, has rarely been reported associated with cancer. A bioinformatics analysis revealed that NSUN5 was overexpressed in ccRCC. Gene Ontology and gene set variation analyses showed that NSUN5 was associated with tumor immunity in ccRCC. The effect of immunosuppressive treatment was superior in the low-risk group compared to the high-risk group, and higher stromal score in the high-risk group relative to the low-risk group. A drug sensitivity analysis revealed that the high-risk group was more sensitive to 5-fluorouracil, mitomycin C, methotrexate, and 17-AAG, whereas the low-risk group was more sensitive to crizotinib, sorafenib, foretinib, and ivozanib. NSUN5 knockout decreased ccRCC cell proliferation. The migration speed and number of invasive cells further decreased. The percentage of apoptotic cells increased. In NSUN5-knockout cells, the levels of BAX, caspase-8, caspase-9, and p53 increased significantly, whereas those of Bcl2, CCND1, CCND3, and MMP9 decreased significantly. NSUN5 is highly expressed in ccRCC and inhibits cancer cell invasion, proliferation, and migration while promoting apoptosis by activating the p53 signaling pathway. This study provides insights into the mechanisms of action of NSUN5 in urological tumors and may contribute to improving ccRCC treatment options.

Corrigendum: Comprehensive transcriptomic analysis of critical RNA regulation associated with metabolism and prognosis in clear cell renal carcinoma

[This corrects the article DOI: 10.3389/fcell.2021.709490.].

Integrated Bioinformatics Analysis for the Identification of Key lncRNAs, mRNAs, and Potential Drugs in Clear Cell Renal Cell Carcinomas

Purpose

The overall survival of clear cell renal cell carcinoma (ccRCC) is poor. Markers for early detection and progression could improve disease outcomes. This study aims to reveal the potential pathogenesis of ccRCC by integrative bioinformatics analysis and to further develop new therapeutic strategies.

Patients and Methods

RNA-seq data of 530 ccRCC cases in TCGA were downloaded, and a comprehensive analysis was carried out using bioinformatics tools. Another 14 tissue samples were included to verify the expression of selected lncRNAs by qRT-PCR. DGIdb database was used to screen out potential drugs, and molecular docking was used to explore the interaction and mechanism between candidate drugs and targets.

Results

A total of 58 differentially expressed lncRNAs (DElncRNAs) and 660 differentially expressed mRNAs (DEmRNAs) were identified in ccRCC. LINC02038, FAM242C, LINC01762, and PVT1 were identified as the optimal diagnostic lncRNAs, of which PVT1 was significantly correlated with the survival rate of ccRCC. GO analysis of cell components showed that DEmRNAs co-expressed with 4 DElncRNAs were mainly distributed in the extracellular area and the plasma membrane, involved in the transport of metal ions, the transport of proteins across membranes, and the binding of immunoglobulins. Immune infiltration analysis showed that MDSC was the most correlated immune cells with PVT1 and key mRNA SIGLEC8. Validation analysis showed that GABRD, SIGLEC8 and CDKN2A were significantly overexpressed, while ESRRB, ELF5 and UMOD were significantly down-regulated, which was consistent with the expression in our analysis. Furthermore, 84 potential drugs were screened by 6 key mRNAs, of which ABEMACICLIB and RIBOCICLIB were selected for molecular docking with CDKN2A, with stable binding affinity.

Conclusion

In summary, 4 key lncRNAs and key mRNAs of ccRCC were identified by integrative bioinformatics analysis. Potential drugs were screened for the treatment of ccRCC, providing a new perspective for disease diagnosis and treatment.

A Novel Defined PANoptosis-Related miRNA Signature for Predicting the Prognosis and Immune Characteristics in Clear Cell Renal Cell Carcinoma: A miRNA Signature for the Prognosis of ccRCC

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers, and PANoptosis is a distinct, inflammatory-programmed cell death regulated by the PANoptosome. The essential regulators of cancer occurrence and progression are microRNAs (miRNAs). However, the potential function of PANoptosis-related microRNAs (PRMs) in ccRCC remains obscure. This study retrieved ccRCC samples from The Cancer Genome Atlas database and three Gene Expression Omnibus datasets. PRMs were recognized based on previous reports in the scientific literature. Regression analyses were used to identify the prognosis PRMs and construct a PANoptosis-related miRNA prognostic signature based on the risk score. We discovered that high-risk patients had poorer survival prognoses and were significantly linked to high-grade and advanced-stage tumors, using a variety of R software packages and web analysis tools. Furthermore, we demonstrated that the low-risk group had significant changes in their metabolic pathways. In contrast, the high-risk group was characterized by high immune cell infiltration, immune checkpoint expression, and low half-maximum inhibition concentration (IC50) values of chemotherapeutic agents. This suggests that high-risk patients may benefit more from immunotherapy and chemotherapy. In conclusion, we constructed a PANoptosis-related microRNA signature and revealed its potential significance in clinicopathological features and tumor immunity, thereby providing new precise treatment strategies.

mTOR Regulation of N-Myc Downstream Regulated 1 (NDRG1) Phosphorylation in Clear Cell Renal Cell Carcinoma

The mechanistic target of rapamycin (mTOR) kinase is a component of two signaling complexes that are known as mTOR complex 1 (mTORC1) and mTORC2. We sought to identify mTOR-phosphorylated proteins that are differently expressed in clinically resected clear cell renal cell carcinoma (ccRCC) relative to pair-matched normal renal tissue. Using a proteomic array, we found N-Myc Downstream Regulated 1 (NDRG1) showed the greatest increase (3.3-fold) in phosphorylation (on Thr346) in ccRCC. This was associated with an increase in total NDRG1. RICTOR is a required subunit in mTORC2, and its knockdown decreased total and phospho-NDRG1 (Thr346) but not NDRG1 mRNA. The dual mTORC1/2 inhibitor, Torin 2, significantly reduced (by ~100%) phospho-NDRG1 (Thr346). Rapamycin is a selective mTORC1 inhibitor that had no effect on the levels of total NDRG1 or phospho-NDRG1 (Thr346). The reduction in phospho-NDRG1 (Thr346) due to the inhibition of mTORC2 corresponded with a decrease in the percentage of live cells, which was correlated with an increase in apoptosis. Rapamycin had no effect on ccRCC cell viability. Collectively, these data show that mTORC2 mediates the phosphorylation of NDRG1 (Thr346) in ccRCC. We hypothesize that RICTOR and mTORC2-mediated phosphorylation of NDRG1 (Thr346) promotes the viability of ccRCC cells.

Identification of AKI signatures and classification patterns in ccRCC based on machine learning

Background

Acute kidney injury can be mitigated if detected early. There are limited biomarkers for predicting acute kidney injury (AKI). In this study, we used public databases with machine learning algorithms to identify novel biomarkers to predict AKI. In addition, the interaction between AKI and clear cell renal cell carcinoma (ccRCC) remain elusive.

Methods

Four public AKI datasets (GSE126805, GSE139061, GSE30718, and GSE90861) treated as discovery datasets and one (GSE43974) treated as a validation dataset were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between AKI and normal kidney tissues were identified using the R package limma. Four machine learning algorithms were used to identify the novel AKI biomarkers. The correlations between the seven biomarkers and immune cells or their components were calculated using the R package ggcor. Furthermore, two distinct ccRCC subtypes with different prognoses and immune characteristics were identified and verified using seven novel biomarkers.

Results

Seven robust AKI signatures were identified using the four machine learning methods. The immune infiltration analysis revealed that the numbers of activated CD4 T cells, CD56^dim natural killer cells, eosinophils, mast cells, memory B cells, natural killer T cells, neutrophils, T follicular helper cells, and type 1 T helper cells were significantly higher in the AKI cluster. The nomogram for prediction of AKI risk demonstrated satisfactory discrimination with an Area Under the Curve (AUC) of 0.919 in the training set and 0.945 in the testing set. In addition, the calibration plot demonstrated few errors between the predicted and actual values. In a separate analysis, the immune components and cellular differences between the two ccRCC subtypes based on their AKI signatures were compared. Patients in the CS1 had better overall survival, progression-free survival, drug sensitivity, and survival probability.

Conclusion

Our study identified seven distinct AKI-related biomarkers based on four machine learning methods and proposed a nomogram for stratified AKI risk prediction. We also confirmed that AKI signatures were valuable for predicting ccRCC prognosis. The current work not only sheds light on the early prediction of AKI, but also provides new insights into the correlation between AKI and ccRCC.

[Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma]

OBJECTIVE

To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).

METHODS

We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.

RESULTS

In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05).

CONCLUSION

ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

Netrin Family Genes as Prognostic Markers and Therapeutic Targets for Clear Cell Renal Cell Carcinoma: Netrin-4 Acts through the Wnt/β-Catenin Signaling Pathway

Clear cell renal cell carcinoma (ccRCC, or KIRC) is the most common type of kidney cancer, originating within the renal cortex. The current outcomes for early diagnosis and late treatment of ccRCC are unsatisfactory. Therefore, it is important to explore tumor biomarkers and therapeutic opportunities for ccRCC. In this study, we used bioinformatics methods to systematically evaluate the expression and prognostic value of Netrin family genes in ccRCC. Through our analysis, three potential biomarkers for ccRCC were identified, namely NTNG1, NTNG2, and NTN4. Moreover, we performed in vitro and in vivo experiments to explore the possible biological roles of NTN4 and found that NTN4 could regulate ccRCC development through Wnt/β-catenin signaling. We elucidate the molecular mechanism by which NTN4 modulates β-catenin expression and nuclear translocation to inhibit ccRCC progression, providing a new theoretical basis for developing therapeutic targets for ccRCC. Thus, we suggest that Netrin-related studies may offer new directions for the diagnosis, treatment, and prognosis of ccRCC patients.

Excavation of diagnostic biomarkers and construction of prognostic model for clear cell renal cell carcinoma based on urine proteomics

Purpose

Clear cell renal cell carcinoma (ccRCC) is the most common pathology type in kidney cancer. However, the prognosis of advanced ccRCC is unsatisfactory. Thus, early diagnosis becomes one of the most important research priorities of ccRCC. However, currently available studies about ccRCC lack urine-related further studies. In this study, we applied proteomics to search urinary biomarkers to assist early diagnosis of ccRCC. In addition, we constructed a prognostic model to assist judge patients' prognosis.

Materials and methods

Urine which was used to perform 4D label-free quantitative proteomics was collected from 12 ccRCC patients and 11 non-tumor patients with no urinary system diseases. The urine of 12 patients with ccRCC confirmed by pathological examination after surgery was collected before operatoin. Bioinformatics analysis was used to describe the urinary proteomics landscape of these patients with ccRCC. The top ten proteins with the highest expression content were selected as the basis for subsequent validation. Urine from 46 ccRCC patients and 45 control patients were collected to use for verification by enzyme linked immunosorbent assay (ELISA). In order to assess the prognostic value of urine proteomics, a prognostic model was constructed by COX regression analysis on the intersection of RNA-sequencing data in The Cancer Genome Atlas (TCGA) database and our urine proteomic data.

Results

133 proteins differentially expressed in the urinary samples were found and 85 proteins (Fold Change, FC>1.5) were identified up-regulated while 48 down-regulated (FC<0.5). Top 10 proteins including S100A14, PKHD1L1, FABP4, ITIH2, C3, C8G, C2, ATF6, ANGPTL6, F13B were performed ELISA to verify. The results showed that PKHD1L1, ANGPTL6, FABP4 and C3 were statistically significant (P<0.05). We performed multivariate logistic regression analysis and plotted a nomogram. Receiver operating characteristic (ROC) curve indicted that the diagnostic efficiency of combined indicators is satisfactory (Aare under curve, AUC=0.835). Furthermore, the prognostic value of the urine proteomics was explored through the intersection between urine proteomics and TCGA RNA-seq data. Thus, COX regression analysis showed that VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 were statistically significant (P<0.05).

Conclusion

Our study indicated that the application of urine proteomics to explore diagnostic biomarkers and to construct prognostic models of renal clear cell carcinoma is of certain clinical value. PKHD1L1, ANGPTL6, FABP4 and C3 can assist to diagnose ccRCC. The prognostic model constituted of VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 can significantly predict the prognosis of ccRCC patients, but this still needs more clinical trials to verify.

Neurological applications of belzutifan in von Hippel-Lindau disease

Von Hippel-Lindau (VHL) disease is a tumor predisposition syndrome caused by mutations in the VHL gene that presents with visceral neoplasms and growths, including clear cell renal cell carcinoma, and central nervous system manifestations, such as hemangioblastomas of the brain and spine. The pathophysiology involves dysregulation of oxygen sensing caused by the inability to degrade HIFα, leading to the overactivation of hypoxic pathways. Hemangioblastomas are the most common tumors in patients with VHL and cause significant morbidity. Until recently, there were no systemic therapies available for patients that could effectively reduce the size of these lesions. Belzutifan, the first approved HIF-2α inhibitor, has demonstrated benefit in VHL-associated tumors, with a 30% response rate in hemangioblastomas and ~30%-50% reduction in their sizes over the course of treatment. Anemia is the most prominent adverse effect, affecting 76%-90% of participants and sometimes requiring dose reduction or transfusion. Other significant adverse events include hypoxia and fatigue. Overall, belzutifan is well tolerated; however, long-term data on dosing regimens, safety, and fertility are not yet available. Belzutifan holds promise for the treatment of neurological manifestations of VHL and its utility may influence the clinical management paradigms for this patient population.

ADAM metallopeptidase with thrombospondin type 1 motif 16 is a potential marker for prognosis in clear cell renal cell carcinoma

The mortality rate of clear cell renal cell carcinoma (ccRCC) remains high. Immunohistochemical staining, Western blotting and real-time quantitative polymerase chain reaction were employed to evaluate ADAM (a disintegrin and metalloproteinase) metallopeptidase with thrombospondin type 1 motif 16 (ADAMTS16) levels in ccRCC tissues and paired normal tissues, and all tissues were obtained from clinical samples of 46 cases of ccRCC patients. Moreover, we analyzed the role ADAMTS16 in the progression of ccRCC using Cell Counting Kit-8 assay and flow cytometry. ADAMTS16 levels in ccRCC tissues were markedly low, relative to normal tissues, and ADAMTS16 level closely correlated with tumor stage, lymph node metastasis as well as pathological grade. Patients with elevated ADAMTS16 expressions have a more favorable survival outcome, relative to patients with low expression of ADAMTS16. In vitro study showed ADAMTS16 expression markedly decreased in ccRCC cells and acted as a tumor suppressor compared with the normal cells. The expression of ADAMTS16 is down-regulated in ccRCC tissues, relative to normal tissues, and it may inhibit the malignancies of ccRCC. Such inhibitory effect may be ascribed to the involvement of AKT/mammalian target of rapamycin signaling. Hence, the present study of ADAMTS16 will provide new insight into the underlying biological mechanisms of ccRCC.

In Vitro and In Silico Analysis of Epithelial-Mesenchymal Transition and Cancer Stemness as Prognostic Markers of Clear Cell Renal Cell Carcinoma

The process of epithelial-mesenchymal transition (EMT) involves the phenotypic transformation of cells from epithelial to mesenchymal status. The cells exhibiting EMT contain features of cancer stem cells (CSC), and the dual processes are responsible for progressive cancers. Activation of hypoxia-inducible factors (HIF) is fundamental to the pathogenesis of clear cell renal cell carcinoma (ccRCC), and their role in promoting EMT and CSCs is crucial for ccRCC tumour cell survival, disease progression, and metastatic spread. In this study, we explored the status of HIF genes and their downstream targets, EMT and CSC markers, by immunohistochemistry on in-house accrued ccRCC biopsies and adjacent non-tumorous tissues from patients undergoing partial or radical nephrectomy. In combination, we comprehensively analysed the expression of HIF genes and its downstream EMT and CSC-associated targets relevant to ccRCC by using publicly available datasets, the cancer genome atlas (TCGA) and the clinical proteome tumour analysis consortium (CPTAC). The aim was to search for novel biological prognostic markers that can stratify high-risk patients likely to experience metastatic disease. Using the above two approaches, we report the development of novel gene signatures that may help to identify patients at a high risk of developing metastatic and progressive disease.