Clinicopathologic Significance of VHL Gene Alteration in Clear-Cell Renal Cell Carcinoma: An Updated Meta-Analysis and Review

Association of the combined parameters including the frequency of primary cilia, PD-L1, Smoothened protein, membranous β-catenin and cytoplasmic β-catenin expression with the outcome of patients with clear cell renal cell carcinoma

AIMS

The objective of this study was to investigate the association and combined prognostic significance of the PD-L1, Smoothened protein and β-catenin expressions in patients with clear cell renal cell carcinoma (ccRCC).

METHODS

The PD-L1, Smoothened protein and β-catenin expression were evaluated in 104 ccRCC patients. All studied tumor samples were acquired from nephrectomy specimens of primary tumors and not from biopsies or metastases. An indirect immunohistochemistry using polyclonal rabbit anti-Smoothened antibody, monoclonal mouse anti-human β-catenin-1 antibody, immunohistochemical assay PD-L1 28-8 pharmDx using monoclonal rabbit anti-PD-L1 antibody and anti-VHL (C- terminal) rabbit antibody was used. Immunohistochemistry was scored semiquantitavely.

RESULTS

Median overall survival (OS) was significantly better in patients with lower PD-L1 expression (≤5%), Smoothened protein (SMO) expression (<5%) or cytoplasmic β-catenin expression (≤75%) than in patients with higher expressions of these biomarkers (P<0.001, P=0.047, and P<0.001, respectively). Membranous β-catenin showed an opposite effect with its lower expression (≤75%) being associated with longer OS (P=0.020). There was significant association between PD-1 and PD-L1 expression (P=0.007) and significant association of tumor grade (WHO 2016) with membranous β-catenin (P<0.001), cytoplasmic β-catenin (P=0.005), pVHL (P=0.042), PD-L1 (P=0.049) and PD-1 (P=0.028) expression.

CONCLUSION

The present study provides the first data on the potential association and combined prognostic significance of frequency of primary cilia, PD-L1, Smoothened protein and β-catenin expression with the outcome in clear cell renal cell carcinoma.

Potential Role of VHL, PTEN, and BAP1 Mutations in Renal Tumors

The genetic profiling of renal tumors has revealed genomic regions commonly affected by structural changes and a general genetic heterogeneity. The VHL, PTEN, and BAP1 genes are often mutated in renal tumors. The frequency and clinical relevance of these mutations in renal tumors are still being researched. In our study, we investigated VHL, PTEN, and BAP1 genes and the sequencing of 24 samples of patients with renal tumors, revealing that VHL was mutated at a noticeable frequency (25%). Six of the investigated samples showed mutations, and one genetic polymorphism (rs779805) was detected in both heterozygote and homozygote forms. PTEN gene mutation was observed in only one sample, and one specimen showed genetic polymorphism. In the case of the BAP1 gene, all of the samples were wild types. Interestingly, VHL mutation was detected in two female patients diagnosed with AML and in one with oncocytoma. We assume that VHL or PTEN mutations may contribute to the development of human renal cancer. However, the overall mutation rate was low in all specimens investigated, and the development and prognosis of the disease were not exclusively associated with these types of genetic alterations.

Dynamic contrast-enhanced ultrasound characteristics of renal tumors: VueBox™ quantitative analysis

BACKGROUND

VueBoxtrademark has been used for contrast analysis in DCE-US-based quantitative research.

OBJECTIVE

Aim of this study was to use the enhancement-mode and VueBoxtrademark parameters to further evaluate the differential diagnostic value of DCE-US for renal tumors.

METHODS

24 patients with renal tumors, including 7 benign and 17 malignant, were retrospectively analyzed.The DCE-US enhancement-mode and VueBoxtrademark parameters correlated with the histological analyses of tumors were obtained and analyzed.

RESULTS

The benign and malignant renal tumors showed significant differences in enhancement degree (P = 0.017) and presence of a pseudocapsule (P = 0.009) and in the VueBoxtrademark parameters FT (P = 0.045) and RT (P = 0.039). Receiver operating characteristic analysis for differential diagnosis of benign and malignant renal tumors showed that AUC for a combination of enhancement degree and presence of a pseudocapsule was greater (AUC = 0.815) than the values for either parameter of enhancement mode alone. Similarly, the AUC for a combination of RT and FT was greater (AUC = 0.798) than the values for RT or FT alone. A comprehensive index obtaining by combining the enhancement-mode and VueBoxtrademark parameters showed the largest AUC (AUC = 0.916) with relatively high accuracy (87.50%), sensitivity (76.50%), and specificity (85.70%).

CONCLUSIONS

DCE-US with enhancement mode and quantitative analysis can facilitate preoperative differential diagnosis of benign and malignant renal tumors.

Semantic Computed Tomography Features for Predicting BRCA1-associated Protein 1 and/or Tumor Protein p53 Gene Mutation Status in Clear Cell Renal Cell Carcinoma

PURPOSE

The purpose of this study was to explore the semantic computed tomography (CT) features associated with BRCA1-associated protein 1 (BAP1) and/or tumor protein p53 (TP53) mutation in clear cell renal cell carcinoma (ccRCC).

METHODS AND MATERIALS

Clinical characteristics and gene mutation information of 336 ccRCC patients were retrieved from The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma database (TCGA-KIRC). Kaplan-Meier analysis was performed to examine prognosis by gene mutation. The CT imaging data and gene mutation information of 156 ccRCC patients treated between January 2019 and January 2021 (the training cohort) were retrospectively analyzed. The CT imaging information and gene mutation data of 123 patients with ccRCC were downloaded from The Cancer Imaging Archive and The Cancer Genome Atlas database (the external validation cohort). Univariate Chi-square test and multivariate binary logistic regression analysis were performed to determine predictors of gene mutation; a nomogram was developed using these predictors. Receiver operating characteristic curve analysis and the Hosmer-Lemeshow test were performed to evaluate the performance of the nomogram.

RESULTS

Kaplan-Meier analysis showed that BAP1 and/or TP53 mutation was significantly correlated with worse survival outcome. Multivariate binary logistic regression analysis indicated ill-defined margin (P = .001), spiculated margin (P = .018), renal vein invasion (P = .002), and renal pelvis invasion (P = .001) were independent predictors of BAP1 and/or TP53 mutation. A nomogram containing these 4 semantic CT features was constructed; the area under the receiver operating characteristic curves was 0.872 (95% CI, 0.809-0.920). The Hosmer-Lemeshow test showed acceptable goodness-of-fit for the nomogram (X² = 1.194, P = .742). The nomogram was validated in the validation cohort; it showed good accuracy (area under the receiving operating characteristic curve = 0.819, 95% CI, 0.740-0.883) and was well calibrated (X² = 3.934, P = .559).

CONCLUSIONS

Semantic CT features are a potential and promising method for predicting BAP1 and/or TP53 mutation status in ccRCC patients.

Renal Cell Carcinoma as a Metabolic Disease: An Update on Main Pathways, Potential Biomarkers, and Therapeutic Targets

Clear cell renal cell carcinoma (ccRCC) is the most frequent histological kidney cancer subtype. Over the last decade, significant progress has been made in identifying the genetic and metabolic alterations driving ccRCC development. In particular, an integrated approach using transcriptomics, metabolomics, and lipidomics has led to a better understanding of ccRCC as a metabolic disease. The metabolic profiling of this cancer could help define and predict its behavior in terms of aggressiveness, prognosis, and therapeutic responsiveness, and would be an innovative strategy for choosing the optimal therapy for a specific patient. This review article describes the current state-of-the-art in research on ccRCC metabolic pathways and potential therapeutic applications. In addition, the clinical implication of pharmacometabolomic intervention is analyzed, which represents a new field for novel stage-related and patient-tailored strategies according to the specific susceptibility to new classes of drugs.

The Clinical and Molecular Features in the VHL Renal Cancers; Close or Distant Relatives with Sporadic Clear Cell Renal Cell Carcinoma?

Von Hippel-Lindau (VHL) disease is an autosomal dominant inherited cancer syndrome caused by germline mutations in the VHL tumor suppressor gene, characterized by the susceptibility to a wide array of benign and malign neoplasms, including clear-cell renal cell carcinoma. Moreover, VHL somatic inactivation is a crucial molecular event also in sporadic ccRCCs tumorigenesis. While systemic biomarkers in the VHL syndrome do not currently play a role in clinical practice, a new promising class of predictive biomarkers, microRNAs, has been increasingly studied. Lots of pan-genomic studies have deeply investigated the possible biological role of microRNAs in the development and progression of sporadic ccRCC; however, few studies have investigated the miRNA profile in VHL patients. Our review summarize all the new insights related to clinical and molecular features in VHL renal cancers, with a particular focus on the overlap with sporadic ccRCC.

An MRI-based radiomics model to predict clear cell renal cell carcinoma growth rate classes in patients with von Hippel-Lindau syndrome

PURPOSE

Upfront knowledge of tumor growth rates of clear cell renal cell carcinoma in von Hippel-Lindau syndrome (VHL) patients can allow for a more personalized approach to either surveillance imaging frequency or surgical planning. In this study, we implement a machine learning algorithm utilizing radiomic features of renal tumors identified on baseline magnetic resonance imaging (MRI) in VHL patients to predict the volumetric growth rate category of these tumors.

MATERIALS AND METHODS

A total of 73 VHL patients with 173 pathologically confirmed Clear Cell Renal Cell Carcinoma (ccRCCs) underwent MRI at least at two different time points between 2015 and 2021. Each tumor was manually segmented in excretory phase contrast T1 weighed MRI and co-registered on pre-contrast, corticomedullary and nephrographic phases. Radiomic features and volumetric data from each tumor were extracted using the PyRadiomics library in Python (4544 total features). Tumor doubling time (DT) was calculated and patients were divided into two groups: DT <  = 1 year and DT > 1 year. Random forest classifier (RFC) was used to predict the DT category. To measure prediction performance, the cohort was randomly divided into 100 training and test sets (80% and 20%). Model performance was evaluated using area under curve of receiver operating characteristic curve (AUC-ROC), as well as accuracy, F1, precision and recall, reported as percentages with 95% confidence intervals (CIs).

RESULTS

The average age of patients was 47.2 ± 10.3 years. Mean interval between MRIs for each patient was 1.3 years. Tumors included in this study were categorized into 155 Grade 2; 16 Grade 3; and 2 Grade 4. Mean accuracy of RFC model was 79.0% [67.4-90.6] and mean AUC-ROC of 0.795 [0.608-0.988]. The accuracy for predicting DT classes was not different among the MRI sequences (P-value = 0.56).

CONCLUSION

Here we demonstrate the utility of machine learning in accurately predicting the renal tumor growth rate category of VHL patients based on radiomic features extracted from different T1-weighted pre- and post-contrast MRI sequences.

Metastatic Clear Cell Renal Cell Carcinoma Involving the Thyroid Gland: A Clinicopathologic Study of 17 Patients

Background. Metastatic clear cell renal cell carcinoma (RCC) is one of the most common secondary thyroid malignancies. Diagnosis can be challenging, particularly if presenting many years after initial diagnosis. We reviewed clinicopathologic features and immunoprofile of metastatic clear cell RCC in thyroid. Design. We identified 17 patients from 2003-2021. Clinical data were obtained from medical records, and slides were retrieved and reviewed. Results. Seventeen patients (12 male and 5 female) included 12 thyroidectomies, 3 core biopsies, 1 excisional biopsy, and 1 fine-needle aspiration. The average patient age was 68.7 years (range, 45-88 years). Sixteen patients had history of clear cell RCC, and in 1 patient, the clear cell RCC was discovered after the thyroid metastasis was found. Thyroid gland metastases were on average diagnosed 90.7 months after the diagnosis of the renal primary (range, 24-240 months). Patients presented with a new palpable mass (n = 11) or dyspnea/stridor (n = 1). Five tumors were incidentally found via surveillance imaging. In 2 patients, metastases occurred within follicular thyroid neoplasms. All metastases showed conspicuous sinusoidal vasculature between the tumor nests and areas of myxoid degeneration. A prominent thick fibromuscular pseudocapsule was evident in 10 resections. Immunohistochemistry (n = 5) showed that the metastases were positive for PAX8, CA9, and CD10, while negative for keratin 7, thyroglobulin, and TTF1. Conclusions. Metastatic clear cell RCC involving the thyroid gland is infrequent and typically occurs remotely after the initial diagnosis. Cytologic and histologic features may show significant overlap with primary thyroid lesions. Immunohistochemistry can help reliably distinguish metastases from primary thyroid neoplasms.

Novel Prognosis and Therapeutic Response Model of Immune-Related lncRNA Pairs in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal carcinoma. It is particularly important to accurately judge the prognosis of patients. Since most tumor prediction models depend on the specific expression level of related genes, a better model therefore needs to be constructed. To provide an immune-related lncRNA (irlncRNAs) tumor prognosis model that is independent of the specific gene expression levels, we first downloaded and sorted out the data on ccRCC in the TCGA database and screened irlncRNAs using co-expression analysis and then obtained the differently expressed irlncRNA (DEirlncRNA) pairs by means of univariate analysis. In addition, we modified LASSO penalized regression. Subsequently, the ROC curve was drawn, and we compared the area under the curve, calculated the Akaike information standard value of the 5-year receiver operating characteristic curve, and determined the cut-off point to establish the best model to distinguish the high- or low-disease-risk group of ccRCC. Subsequently, we reassessed the model from the perspectives of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutics efficacy, and immunosuppressed biomarkers. A total of 17 DEirlncRNAs pairs (AL031710.1|AC104984.5, AC020907.4|AC127-24.4,AC091185.1|AC005104.1, AL513218.1|AC079015.1, AC104564.3|HOXB-AS3, AC003070.1|LINC01355, SEMA6A-AS1|CR936218.1, AL513327.1|AS005785.1, AC084876.1|AC009704.2, IGFL2-AS1|PRDM16-DT, AC011462.4|MMP25-AS1, AL662844.3I|TGB2-AS1, ARHGAP27P1|AC116914.2, AC093788.1|AC007098.1, MCF2L-AS1|AC093001.1, SMIM25|AC008870.2, and AC027796.4|LINC00893) were identified, all of which were included in the Cox regression model. Using the cut-off point, we can better distinguish patients according to different factors, such as survival status, invasive clinic-pathological features, tumor immune infiltration, whether they are sensitive to chemotherapy or not, and expression of immunosuppressive biomarkers. We constructed the irlncRNA model by means of pairing, which can better eliminate the dependence on the expression level of the target genes. In other words, the signature established by pairing irlncRNA regardless of expression levels showed promising clinical prediction value.

VHL and DNA damage repair pathway alterations as potential clinical biomarkers for first-line TKIs in metastatic clear cell renal cell carcinomas

Purpose

Vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFR-TKIs) are being used for the first-line treatment of metastatic clear cell renal cell carcinoma (mccRCC). Here, we set out to explore associations between genomic statuses, gene expression clusters and clinical outcomes of mccRCCs upon the application of VEGFR-TKIs.

Methods

A retrospective study of 56 patients with mccRCC who received first-line VEGFR-TKIs and who underwent genomic profiling and whole transcriptome sequencing was conducted. Survival analysis was carried out using log-rank tests and Cox regression analyses, and Kaplan–Meier curves were plotted. Clustering was performed using the K-means method.

Results

Among the 56 patients tested, 17 harbored DNA Damage and Repair (DDR) pathway alterations and 35 VHL mutations. The median progression-free survival (PFS) rates for the DDR and VHL alteration groups were 18 and 18 months, respectively, compared with 14 and 10 months for the nonmutant groups. DDR mutations, VHL mutations and co-mutations were identified as prognostic biomarkers of a longer PFS (p = 0.017, 0.04, 0.014). K-means clustering of expressed transcripts revealed three clusters of 40 patients: C_1, C_2 and C_3. The C_1 cluster exhibited the best PFS and objective response rate (ORR) to TKI therapy, with the highest proportion of DDR and VHL mutations. Further analysis of the tumor immune environment revealed that the C_1 cluster was enriched in activated CD8 T cells and effector CD4 T cells, whereas the C_2 cluster was enriched in eosinophils, mast cells and DC cells and, thus, in immunosuppressive cells.

Conclusions

We found that patients with mccRCC harboring DDR and VHL alterations were more likely to benefit from first-line VEGF-TKI systemic therapy than patients with wild-type disease. In addition, we found that a three-cluster prognostic model based on gene expression can predict PFS and ORR, which was well-matched with activated TIL infiltration.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13402-022-00691-8.

Evaluation of a seven gene mutational profile as a prognostic factor in a population-based study of clear cell renal cell carcinoma

In this study, we investigate the influence of the seven genes (VHL, PBRM1, SETD2, BAP1, KDM5C, MTOR and TP53) most frequently mutated in clear cell renal cell cancer (ccRCC) on cancer-specific survival (CSS) in the prospective Netherlands Cohort Study on diet and cancer. DNA isolated from routinely archived formalin-fixed paraffin-embedded tumour blocks from 252 incident ccRCC cases was available for targeted next generation sequencing. Based on the sequencing quality and the completeness of information on clinical characteristics and follow-up, we could use 110 cases for survival analysis. The association with CSS for each mutated gene in these cases was tested using multivariable Cox proportional hazards models to estimate hazards ratios (HR) and confidence intervals (CIs), and we observed mutations in one or more of the seven genes in 64 out of 110 cases (58%). In the multivariable-adjusted analyses, mutations in VHL and PBRM1 were associated with better CSS (HRs (95% CI) 0.34 (0.13‒0.89) and 0.17 (0.04–0.66), respectively), although these results were not statistically significant after multiple testing correction. No association was observed for the other five genes, which may be attributable to limited power.

Comprehensive bioinformatics analyses of APOBECs family and identification of APOBEC3D as the unfavorable prognostic biomarker in clear cell renal cell carcinoma

Purpose: At present, how early screening for ccRCC is still a thorny issue for urologists. Probing the mechanisms underlying the development of ccRCC and finding relevant prognostic biomarkers remains crucial. Therefore, we systematically analyzed the APOBEC family in this study and identified APOBEC3D as a prognostic biomarker. Methods: In this study, based on the TCGA database, we systematically assessed the expression and prognosis of the APOBEC family and analyzed potential bioinformatic pathways. We then constructed nomograms to predict the prognosis of ccRCC patients better. Afterward, we further focused on APOBEC3D in our data on ccRCC specimens. The APOBEC3D should be extensively studied in ccRCC in the future. Results: The results showed that the APOBEC family showed the most significant changes in expression in ccRCC. The pathway enrichment analysis showed that APOBEC3 family members mainly regulated cytidine and cytosine-related processes. Subsequently, the Cox regression was used to construct prognostic signature, and validated in ICGC and GEO databases. Next, a nomogram was created integrating clinical parameters showing good predictive performance. Finally, we screened for APOBEC3D and found in our clinical sample that patients with high expression of APOBEC3D had a worse prognosis. Conclusion: Based on these results, APOBEC family members play important roles in the development of ccRCC, and APOBEC3D could serve as the biomarker for predicting patient prognosis.

Characteristics of contrast-enhanced ultrasound for diagnosis of solid clear cell renal cell carcinomas ≤4 cm: A meta-analysis

Now solid renal tumors ≤4 cm is the most common, especially the subtype of clear cell renal cell carcinoma (ccRCC) of malignant kidney tumors in clinical. However, there is not specific characteristics of contrast‐enhanced ultrasound (CEUS) be recommended by the EFSUMB Guidelines in distinguish the essence of the kidney tumor with different sizes. Therefore, this meta‐analysis aimed to assess the ability of CEUS to diagnose solid ccRCC (sccRCC) ≤4 cm. We comprehensively searched the Cochrane Library, Embase, PubMed, and Web of Science databases from their inception to 28 July 2020, for studies reporting the CEUS features of sccRCC lesions ≤4 cm. Additional articles were identified through the Chinese National Knowledge Infrastructure database. Studies were selected independently by two investigators and the relevant data were extracted. Discrepancies were resolved via discussion with the senior author. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies‐2 tool, and the sensitivity and specificity of each study were determined and plotted as a receiver operating characteristic curve. Ten studies were included in this meta‐analysis. Hyperenhancement showed medium sensitivity (67%–89%) and specificity (42%–75%) for diagnosing sccRCC ≤4 cm, fast‐in contrast agent and heterogeneous enhancement showed high diagnostic abilities (area under curve (AUC) 0.74–0.84), but the presence of a pseudocapsule and fast‐out contrast agent had poor diagnostic ability (AUC <0.70). The combination of hyperenhancement and iso‐enhancement showed high sensitivity (98%) for diagnosing sccRCC ≤4 cm. Hyperenhancement, fast‐in contrast agent, and heterogeneous enhancement may be specific features that could help to identify sccRCC ≤4 cm, while the presence of a pseudocapsule and fast‐out of contrast agent may have low diagnostic values. The combination of multiple indexes may improve the diagnostic value of CEUS for sccRCC ≤4 cm.

Comprehensive Genomic Landscape in Chinese Clear Cell Renal Cell Carcinoma Patients

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). The genomic landscape in Chinese ccRCC needs to be elucidated. Herein, we investigated the molecular features of Chinese ccRCC patients. Genomic profiling of DNA was performed through next-generation sequencing (NGS) in Chinese patients with ccRCC between January 2017 and March 2020. Clinical information including age, gender, and tumor histology was collected. Immunohistochemistry (IHC) staining for PD-L1 expression was performed using PD-L1 IHC 22C3 pharmDx assay or Ventana PD-L1 SP263 assay. Data analyses were performed using R 3.6.1. A total of 880 Chinese ccRCC patients who have undergone NGS were included in this study. The most common somatic alterations were detected in VHL (59.7%), PBRM1 (18.0%), SETD2 (12.2%), BAP1 (10.2%), and TP53 (9.4%). Compared with The Cancer Genome Atlas (TCGA) database, a higher mutation frequency of VHL (59.7% vs. 50.0%, p < 0.001) and TP53 (9.4% vs. 3.5%, p < 0.001) and a lower mutation frequency of PBRM1 (18.0% vs. 31.0%, p < 0.001) were found in the Chinese cohort. Of the 460 patients who were evaluated for PD-L1 expression, 139 (30.2%) had positive PD-L1 expression. The median tumor mutational burden (TMB) value was 4.5 muts/Mb (range, 0–46.0). Five (0.7%) patients were identified as microsatellite instability-high (MSI-H). Furthermore, 52 (5.9%) patients were identified to carry pathogenic or likely pathogenic germline mutations in 22 cancer predisposition genes. This is the first large-scale comprehensive genomic analysis for Chinese ccRCC patients, and these results might provide a better understanding of molecular features in Chinese ccRCC patients, which can lead to an improvement in the personalized treatment for these patients.

The Role of Epigenetics in the Progression of Clear Cell Renal Cell Carcinoma and the Basis for Future Epigenetic Treatments

Simple Summary

The accumulated evidence on the role of epigenetic markers of prognosis in clear cell renal cell carcinoma (ccRCC) is reviewed, as well as state of the art on epigenetic treatments for this malignancy. Several epigenetic markers are likely candidates for clinical use, but still have not passed the test of prospective validation. Development of epigenetic therapies, either alone or in combination with tyrosine-kinase inhibitors of immune-checkpoint inhibitors, are still in their infancy.

Abstract

Clear cell renal cell carcinoma (ccRCC) is curable when diagnosed at an early stage, but when disease is non-confined it is the urologic cancer with worst prognosis. Antiangiogenic treatment and immune checkpoint inhibition therapy constitute a very promising combined therapy for advanced and metastatic disease. Many exploratory studies have identified epigenetic markers based on DNA methylation, histone modification, and ncRNA expression that epigenetically regulate gene expression in ccRCC. Additionally, epigenetic modifiers genes have been proposed as promising biomarkers for ccRCC. We review and discuss the current understanding of how epigenetic changes determine the main molecular pathways of ccRCC initiation and progression, and also its clinical implications. Despite the extensive research performed, candidate epigenetic biomarkers are not used in clinical practice for several reasons. However, the accumulated body of evidence of developing epigenetically-based biomarkers will likely allow the identification of ccRCC at a higher risk of progression. That will facilitate the establishment of firmer therapeutic decisions in a changing landscape and also monitor active surveillance in the aging population. What is more, a better knowledge of the activities of chromatin modifiers may serve to develop new therapeutic opportunities. Interesting clinical trials on epigenetic treatments for ccRCC associated with well established antiangiogenic treatments and immune checkpoint inhibitors are revisited.

Radiomic profiling of clear cell renal cell carcinoma reveals subtypes with distinct prognoses and molecular pathways

•

Radiomics profile of clear cell renal cell carcinoma is heterogeneity.

•

Multi-scale Radiogenomics could link molecular features and images.

•

Radiomic subtypes could be used for risk stratification.

Background

To identify radiomic subtypes of clear cell renal cell carcinoma (ccRCC) patients with distinct clinical significance and molecular characteristics reflective of the heterogeneity of ccRCC.

Methods

Quantitative radiomic features of ccRCC were extracted from preoperative CT images of 160 ccRCC patients. Unsupervised consensus cluster analysis was performed to identify robust radiomic subtypes based on these features. The Kaplan–Meier method and chi-square test were used to assess the different clinicopathological characteristics and gene mutations among the radiomic subtypes. Subtype-specific marker genes were identified, and gene set enrichment analyses were performed to reveal the specific molecular characteristics of each subtype. Moreover, a gene expression-based classifier of radiomic subtypes was developed using the random forest algorithm and tested in another independent cohort (n = 101).

Results

Radiomic profiling revealed three ccRCC subtypes with distinct clinicopathological features and prognoses. VHL, MUC16, FBN2, and FLG were found to have different mutation frequencies in these radiomic subtypes. In addition, transcriptome analysis revealed that the dysregulation of cell cycle-related pathways may be responsible for the distinct clinical significance of the obtained subtypes. The prognostic value of the radiomic subtypes was further validated in another independent cohort (log-rank P = 0.015).

Conclusion

In the present multi-scale radiogenomic analysis of ccRCC, radiomics played a central role. Radiomic subtypes could help discern genomic alterations and non-invasively stratify ccRCC patients.

Integrative radiogenomics analysis for predicting molecular features and survival in clear cell renal cell carcinoma

Objectives: To assess the feasibility of predicting molecular characteristics by computed tomography (CT) radiomics features, and predicting overall survival (OS) using combination of omics data in clear cell renal cell carcinoma (ccRCC).

Methods: Genetic data of 207 ccRCC patients was retrieved from The Cancer Genome Atlas (TCGA) and matched contrast-enhanced CT images were obtained from The Cancer Imaging Archive (TCIA). Another cohort of 175 ccRCC patients from West China Hospital was used as external validation. We first applied radiomics features and machine learning algorithms to predict genetic mutations and mRNA-based molecular subtypes. Next, we established predictive models for OS based on single omics, combined omics (radiomics+genomics, radiomics+transcriptomics, radiomics+proteomics) and all features (multi-omics).

Results: Using radiomics features, random forest algorithm showed good capacity to identify the mutations VHL (AUC=0.971), BAP1 (AUC=0.955), PBRM1 (AUC=0.972), SETD2 (AUC=0.949), and molecular subtypes m1 (AUC=0.973), m2 (AUC=0.968), m3 (AUC=0.961), m4 (AUC=0.953). The TCGA cohort was divided into training (n=104) and validation (n=103) sets. The radiomics model had promising prognostic value for OS in validation set (5-year AUC=0.775) and external validation set (5-year AUC=0.755). In the validation set, the radiomics+omics models enhanced predictive accuracy than single-omics models, and the multi-omics model made further improvement (5-year AUC=0.846). High-risk group of validation set predicted by multi-omics model showed significantly poorer OS (HR=6.20, 95%CI: 3.19-8.44, p<0.0001).

Conclusions: CT radiomics might be a feasible approach to predict genetic mutations, molecular subtypes and OS in ccRCC patients. Integrative analysis of radiogenomics may improve the survival prediction of ccRCC patients.

[Ginsenoside 20(S)-Rg3 upregulates tumor suppressor VHL gene expression by suppressing DNMT3A-mediated promoter methylation in ovarian cancer cells]

OBJECTIVE

To explore the mechanism by which ginsenoside 20(S)-Rg3 upregulates the expression of tumor suppressor von Hippel-Lindau (VHL) gene in ovarian cancer cells.

METHODS

Ovarian cancer cell line SKOV3 treated with 20(S)-Rg3 were examined for mRNA and protein levels of VHL, DNMT1, DNMT3A and DNMT3B by real-time PCR and Western blotting, respectively. The changes in VHL mRNA expression in SKOV3 cells in response to treatment with 5-Aza-CdR, a DNA methyltransferase inhibitor, were detected using real-time PCR. VHL gene promoter methylation was examined with methylation-specific PCR and VHL expression levels were determined with real-time PCR and Western blotting in non-treated or 20(S)-Rg3-treated SKOV3 cells and in 20(S)-Rg3-treated DNMT3A-overexpressing SKOV3 cells. VHL and DNMT3A protein levels were detected by immunohistochemistry in subcutaneous SKOV3 cell xenografts in nude mice.

RESULTS

Treatment of SKOV3 cells with 20(S)-Rg3 significantly upregulated VHL and downregulated DNMT3A expressions at both the mRNA and protein levels (P < 0.05) and upregulated DNMT3B expression only at the mRNA level, but did not cause significant changes in either the mRNA or protein level of DNMT1. Treatment of the cells with 2 and 5 μmol/L 5-Aza-CdR obviously increased VHL mRNA expression by by over 3 folds (P < 0.05). 20(S)-Rg3 significantly decreased the methylation level in the promoter region of VHL gene, and this effect was abrogated by DNMT3A overexpression in the cells (P < 0.05). Immunohistochemisty showed a significantly increased VHL expression but a lowered DNMT3A expression in subcutaneous SKOV3 cell xenografts in 20 (S)-Rg3-treated nude mice.

CONCLUSIONS

Ginsenoside 20(S)-Rg3 upregulates VHL expression in ovarian cancer cells by suppressing DNMT3A-mediated DNA methylation.

Genomic characterization of clear cell renal cell carcinoma using targeted gene sequencing

Kidney cancer is one of the most lethal cancer types worldwide. The most common subtype of kidney cancer is clear cell renal cell carcinoma (ccRCC), and the somatic mutations of ccRCC have been identified through the development of large databases. The present study aimed to validate the status of the associated gene mutations in a Taiwanese cohort. Targeted sequencing was used to validate the mutation status of genes related to ccRCC in Taiwanese patients who had nephrectomy for kidney cancer. The top eight mutated genes in the Catalogue Of Somatic Mutations In Cancer (COSMIC) were selected. These genes were VHL, protein polybromo-1 (PBRM1), histone-lysine N-methyltransferase SETD2, BRCA1-associated protein-1 (BAP1), lysine-specific demethylase 5C (KDM5C), TP53, MTOR and PTEN. The association between the gene mutation status of VHL, PBRM1, SETD2 and BAP1 was validated with clinicopathological parameters as well as overall survival time. Tumor cells from 96 patients with ccRCC were target sequenced. The order of mutation rate of the eight aforementioned genes was similar to that reported within COSMIC. The present Taiwanese cohort exhibited lower PBRM1 and BAP1 mutation rates compared with average, with increased mutation rates for SETD2 and KDM5C. BAP1 mutation was associated with the tumor and cancerous stage. None of these four genes were positively associated with the overall survival of patients. The PBRM1 and SETD2 mutations were mutually exclusive to BAP1 mutation. Overall, the present study provided data confirming gene alteration in Taiwanese patients with ccRCC and showed some differences when compared with Western countries. Further comprehensive genomic and epigenomic studies, as well as downstream validation, are necessary to evaluate the impact of these differences.

Integrated bioinformatics analysis for the identification of potential key genes affecting the pathogenesis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (CCRCC) is a typical type of RCC with the worst prognosis among the common epithelial neoplasms of the kidney. However, its molecular pathogenesis remains unknown. Therefore, the aim of the present study was to screen for effective and potential pathogenic biomarkers of CCRCC. The gene expression profile of the GSE16441, GSE36895, GSE40435, GSE46699, GSE66270 and GSE71963 datasets were downloaded from the Gene Expression Omnibus database. First, the limma package in R language was used to identify differentially expressed genes (DEGs) in each dataset. The robust and strong DEGs were explored using the robust rank aggregation method. A total of 980 markedly robust DEGs were identified (429 upregulated and 551 downregulated). According to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, these DEGs exhibited an obvious enrichment in various cancer-related biological pathways and functions. The Search Tool for the Retrieval of Interacting Genes/Proteins database was used for the construction of a protein-protein interaction (PPI) network, the Cytoscape MCODE plug-in for module analysis and the cytoHubba plug-in to identify hub genes from the aforementioned DEGs. A total of four key modules were identified in the PPI network. A total of six hub genes, including C-X-C motif chemokine ligand 12, bradykinin receptor B2, adenylate cyclase 7, calcium sensing receptor (CASR), kininogen 1 and lysophosphatidic acid receptor 5, were identified. The DEG results of the hub genes were verified using The Cancer Genome Atlas database, and CASR was found to be significantly associated with the prognosis of patients with CCRCC. In conclusion, the present study provided new insight and potential biomarkers for the diagnosis and prognosis of CCRCC.

The evolving role of cytoreductive nephrectomy: incorporating genomics of metastatic renal cell carcinoma into treatment decisions

PURPOSE OF REVIEW

Recent publications evaluating cytoreductive nephrectomy in the era of targeted therapy emphasize the importance of patient selection. We reviewed the predictive role of genetic alterations in patients with metastatic renal cell carcinoma (mRCC) undergoing cytoreductive nephrectomy.

RECENT FINDINGS

Studies evaluating the association between genetic alterations and outcomes following systemic treatment for mRCC include mainly patients after cytoreductive nephrectomy. Expression of proangiogenic genes, single nucleotide polymorphisms involving genes of the vascular-endothelial growth factor (VEGF) pathway and somatic mutations of chromatin remodeling genes were associated with response to VEGF-targeted therapy. Outcomes following treatment with mammalian target of rapamycin (mTOR) inhibitors were initially associated with mTOR/TSC1/TSC2 mutations; however, subsequent studies did not validate these findings but rather found an association between loss of PTEN expression and PBRM1 mutations and improved outcomes. Loss of PBRM1 was initially linked to response to immunotherapy; however, larger studies question this association and showed high expression of T-effector gene signature predicted improved outcome. Primary tumors with low intratumor heterogeneity but elevated somatic copy-number alterations were associated with rapid progression at multiple sites.

SUMMARY

Genetic alterations may help select patients for cytoreductive nephrectomy and optimize timing of treatment. Intratumor heterogeneity and genetic discordance between primary and metastatic tumors may limit clinical applicability. Future studies should evaluate approaches to overcome these limitations.

Extracellular Vesicles and Carried miRNAs in the Progression of Renal Cell Carcinoma

The formation and maintenance of renal cell carcinomas (RCC) involve many cell types, such as cancer stem and differentiated cells, endothelial cells, fibroblasts and immune cells. These all contribute to the creation of a favorable tumor microenvironment to promote tumor growth and metastasis. Extracellular vesicles (EVs) are considered to be efficient messengers that facilitate the exchange of information within the different tumor cell types. Indeed, tumor EVs display features of their originating cells and force recipient cells towards a pro-tumorigenic phenotype. This review summarizes the recent knowledge related to the biological role of EVs, shed by renal tumor cells and renal cancer stem cells in different aspects of RCC progression, such as angiogenesis, immune escape and tumor growth. Moreover, a specific role for renal cancer stem cell derived EVs is described in the formation of the pre-metastatic niche. We also highlight the tumor EV cargo, especially the oncogenic miRNAs, which are involved in these processes. Finally, the circulating miRNAs appear to be a promising source of biomarkers in RCC.