Biomarker For ccRCC Research Articles

Angiogenesis-Related Molecular Subtypes and a Novel Prognostic Signature in Clear Cell Renal Cell Carcinoma Patients.

BackgroundThis study aimed to develop and validate a novel angiogenesis-related gene (ARG) signature and molecular subtypes by bioinformatics analysis.Materials and MethodsThe transcriptome data and clinical data were obtained from TCGA and ICGC database. We performed consensus clustering analysis to identify angiogenesis molecular subtypes for ccRCC. Univariate and multivariate Cox regression analyses were used to develop a novel ARG-related signature as a prognostic biomarker for ccRCC. Internal and external validation were then performed in TCGA and ICGC cohort, respectively.ResultsWe identified a total of two angiogenesis molecular subtypes of ccRCC. The overall survival (OS) of subtype 1 ccRCC was significantly decreased compared with that of subtype 2 ccRCC (P=0.001). These two molecular subtypes have significantly different tumor microenvironment and immune checkpoint inhibitor sensitivities (P<0.05). Besides, we developed a novel signature based on three ARGs (including MSX1, TIMP1 and JAG2) for subtype 1 ccRCC. The difference in OS between high- and low-risk group was statistically significant in training cohort (P=0.009), test cohort (P=0.024), the whole type 1 cohort (P<0.001), and validation cohort (P=0.041). The AUC for one-year OS prediction was 0.732, 0.710, 0.725, and 0.645 in training cohort, test cohort, the whole type 1 cohort, and validation cohort, respectively. Independent prognostic analysis showed that this signature was an independent predictor for OS of subtype 1 ccRCC (P=0.028914). The power of this prognostic signature was superior to other signatures reported in previous studies.ConclusionWe developed and successfully validated a novel ARG signature for predicting prognosis of subtype 1 ccRCC, which was superior to several previous signatures.

Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma.

BackgroundSLFN11 has been found to regulate the development and progression of a variety of cancers and is associated with drug therapy, while its role in clear cell renal cell carcinoma (ccRCC) remains unclear; therefore, the aim of this study was to investigate SLFN11 expression in ccRCC patients and its correlations with clinicopathological and immunological features.MethodsGene profiles of ccRCC and the clinicopathological information of patients were downloaded from the TCGA database. Microarrays from the GEO database were used as a validation set for SLFN11 expression, which was experimentally verified in renal cancer cell lines by quantitative polymerase chain reaction (qPCR); protein expression and methylation levels were obtained from the HPA database and the UALCAN database. ROC curves, Kaplan–Meier survival analysis and Cox analysis were used to assess the diagnostic and predictive value of SLFN11 in ccRCC. Protein–protein interaction (PPI) networks for SLFN11 were obtained from the STRING website, and the TISIDB and TIMER 2.0 databases were used to study the relationship between SLFN11 and immune infiltration in the tumour microenvironment (TME).ResultsSLFN11 was significantly overexpressed in ccRCC tissues and renal cancer cell lines, which may be closely related to its hypermethylation status (P < 0.001). SLFN11 was positively correlated with a highly aggressive disease state, with the ROC curve showing an AUC value of 0.910 for SLFN11 in diagnosing ccRCC, and Kaplan–Meier and Cox analyses also revealed that upregulation of SLFN11 predicted a poor prognosis for ccRCC patients (P < 0.05). In addition, enrichment analysis showed that SLFN11 was closely associated with immune-related signalling pathways, and further exploration comprehensively demonstrated strong positive correlations with tumour immune lymphocytes, immune checkpoint genes, chemokines and chemokine receptors.ConclusionOverall, our data analysis shows that SLFN11 is a strong diagnostic and prognostic biomarker for ccRCC and is also associated with immune infiltration in the TME.

The Downregulation of Prognosis- and Immune Infiltration-Related Gene CYFIP2 Serves as a Novel Target in ccRCC.

BackgroundIncreasing evidence indicated that the aberrant expression of the cytoplasmic FMR1-interacting protein (CYFIP) family might possess critical role and potential functions in cancer. But the role of CYFIP2 in clear cell renal cell carcinoma (ccRCC) is still uncharacteristic.MethodsWe investigated the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC) database for the expression profile, clinicopathological variables, clinical prognosis information, and promoter methylation levels of CYFIPs in ccRCC. The aberrant CYFIP2 protein expression was validated by the Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to uncover CYFIP2 mRNA levels in 28 pairs of ccRCC cancer tissues. Kaplan–Meier analysis, univariate and multivariate Cox proportional hazard regression were performed to assess CYFIPs’ prognosis value. Gene set enrichment analysis (GSEA) was used to determined hallmark functions, gene ontology of CYFIP2. TIMER database was utilized to assess the correlation with immune infiltration in ccRCC.ResultsResults showed CYFIP2 was downregulated in ccRCC, relative to paired normal tissues in TCGA-KIRC database and 28 pairs of clinical samples (P < 0.0001). Similarly, a decreased CYFIP2 protein expression was confirmed by ccRCC tissues. The results showed CYFIP2 was negatively regulated by promoter DNA methylation. Survival analysis results showed CYFIP2 could be an independent biomarker for ccRCC and its reduction predicted a poor overall survival (OS) and disease-free survival (DFS). GSEA showed CYFIP2 was involved in metabolic pathways and epithelial–mesenchymal transition (EMT). Immune infiltration analysis revealed that a list of immune markers was significantly correlated with CYFIP2 expression especially with CD4+ cells and CD8+ cells in ccRCC.ConclusionThese results show that CYFIP2 was downregulated in ccRCC patients and predicted an unfavorable prognosis. CYFIP2 might be a potential novel prognostic molecule, and related to immune infiltration, the metabolism, as well as EMT process in ccRCC. CYFIP2 could act as tumor suppressor gene in ccRCC and positive modulation of CYFIP2 might lead to development of a novel strategy for ccRCC treatment.

Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis.

BackgroundClear cell renal cell carcinoma (ccRCC) is a common genitourinary cancer type with a high mortality rate. Due to a diverse range of biochemical alterations and a high level of tumor heterogeneity, it is crucial to select highly validated prognostic biomarkers to be able to identify subtypes of ccRCC early and apply precision medicine approaches.MethodsTranscriptome data of ccRCC and clinical traits of patients were obtained from the GSE126964 dataset of Gene Expression Omnibus and The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) database. Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening were applied to detect common differentially co-expressed genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, survival analysis, prognostic model establishment, and gene set enrichment analysis were also performed. Immunohistochemical analysis results of the expression levels of prognostic genes were obtained from The Human Protein Atlas. Single-gene RNA sequencing data were obtained from the GSE131685 and GSE171306 datasets.ResultsIn the present study, a total of 2,492 DEGs identified between ccRCC and healthy controls were filtered, revealing 1,300 upregulated genes and 1,192 downregulated genes. Using WGCNA, the turquoise module was identified to be closely associated with ccRCC. Hub genes were identified using the maximal clique centrality algorithm. After having intersected the hub genes and the DEGs in GSE126964 and TCGA-KIRC dataset, and after performing univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, ALDOB, EFHD1, and ESRRG were identified as significant prognostic factors in patients diagnosed with ccRCC. Single-gene RNA sequencing analysis revealed the expression profile of ALDOB, EFHD1, and ESRRG in different cell types of ccRCC.ConclusionsThe present results demonstrated that ALDOB, EFHD1, and ESRRG may act as potential targets for medical therapy and could serve as diagnostic biomarkers for ccRCC.

MP39-14 IDENTIFICATION OF RECURRENT SOMATIC SPLICE SITE VARIANTS ACROSS MULTIPLE CLEAR CELL RENAL CELL CARCINOMA COHORTS

You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology I (MP39)1 Sep 2021MP39-14 IDENTIFICATION OF RECURRENT SOMATIC SPLICE SITE VARIANTS ACROSS MULTIPLE CLEAR CELL RENAL CELL CARCINOMA COHORTS Nicholas Chakiryan, Timothy Robinson, Dongliang Du, Ali Hajiran, Logan Zemp, Youngchul Kim, Jad Chahoud, Philippe Spiess, Liang Wang, James Mule, and Brandon Manley Nicholas ChakiryanNicholas Chakiryan More articles by this author , Timothy RobinsonTimothy Robinson More articles by this author , Dongliang DuDongliang Du More articles by this author , Ali HajiranAli Hajiran More articles by this author , Logan ZempLogan Zemp More articles by this author , Youngchul KimYoungchul Kim More articles by this author , Jad ChahoudJad Chahoud More articles by this author , Philippe SpiessPhilippe Spiess More articles by this author , Liang WangLiang Wang More articles by this author , James MuleJames Mule More articles by this author , and Brandon ManleyBrandon Manley More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002054.14AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Splice-site variants (SV) are DNA mutations that ultimately result in abnormal mRNA splicing and a dramatically altered protein-coding sequence. SVs in clear cell renal cell carcinoma (ccRCC) have been largely unexplored. Our primary objective was to identify the most prevalent SVs in ccRCC, and determine their prevalence in other malignancies and adjacent normal kidney tissue. METHODS: Specific SVs were identified in RCC cell lines from the Broad Institute Cancer Cell Line Encyclopedia. Patients with a diagnosis of ccRCC were then identified in the Moffitt Cancer Center Total Cancer Care (TCC) cohort and RNA-seq data was utilized in a bioinformatics pipeline to identify the SVs among the TCC cohort. SVs identified in the TCC ccRCC cohort were then identified in TCC patients with non-ccRCC malignancies. This process was then repeated for the ccRCC RNA-seq data from CPTAC and TCGA, as well as from adjacent normal kidney tissue from these data sets. The most prevalent SVs among the ccRCC were selected for analysis, using a minimum SV read count threshold of 10. RESULTS: Among the three ccRCC datasets, 756 patients with ccRCC tumor samples were identified (N: TCC 104, CPTAC 111, TCGA 541). Eight distinct SVs were found to have high ccRCC prevalence and low prevalence in adjacent normal kidney tissue and non-ccRCC malignancies (Figure 1A). Genes with multiple distinct SVs were classified separately. The GAL3ST1-a and GAL3ST1-b SVs had the highest prevalence in ccRCC, as well as the highest read count per patient (Figure 1B). In the TCC ccRCC cohort, low read counts of SVs from the GAL3ST1 gene were associated with stage cM1. CONCLUSIONS: We identified eight novel SVs that are highly prevalent in ccRCC tumors and minimally prevalent in adjacent normal kidney tissue and other malignancies. Particularly striking were four distinct SVs affecting the the GAL3ST1 gene. These novel SVs warrant further investigation as potential biomarkers in ccRCC. Source of Funding: N/A © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e709-e710 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nicholas Chakiryan More articles by this author Timothy Robinson More articles by this author Dongliang Du More articles by this author Ali Hajiran More articles by this author Logan Zemp More articles by this author Youngchul Kim More articles by this author Jad Chahoud More articles by this author Philippe Spiess More articles by this author Liang Wang More articles by this author James Mule More articles by this author Brandon Manley More articles by this author Expand All Advertisement Loading ...

Discovery and construction of prognostic model for clear cell renal cell carcinoma based on single-cell and bulk transcriptome analysis.

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common malignant kidney tumor in adults. Single-cell transcriptome sequencing can provide accurate gene expression data of individual cells. Integrated single-cell and bulk transcriptome data from ccRCC samples provide comprehensive information, which allows the discovery of new understandings of ccRCC and the construction of a novel prognostic model for ccRCC patients.MethodsSingle-cell transcriptome sequencing data was preprocessed by using the Seurat package in R software. Principal component analysis (PCA) and the t-distributed stochastic neighbor embedding (t-SNE) algorithm were used to perform cluster classification. Two subtypes of cancer cells were identified, pseudotime trajectory analysis and gene ontology (GO) analysis were conducted with the monocle and clusterProfiler packages. Two novel cancer cell biomarkers were identified according to the single-cell sequencing and were confirmed by The Cancer Genome Atlas (TCGA) data. T cell-related marker genes according to single-cell sequencing were screened by a combination of Kaplan-Meier (KM) analysis, univariate Cox analysis, least absolute shrinkage and selection operator (Lasso) regression and multivariate Cox analysis of TCGA data. Four survival predicting genes were screened out to develop a risk score model. A nomogram consisting of the risk score and clinical information was constructed to predict the prognosis for ccRCC patients.ResultsA total of 5,933 cells were included in the study after quality control. Fifteen cell clusters were classified by PCA and t-SNE algorithm. Two clusters of cancer cells with distinct differentiation status were identified. Besides, GO analysis revealed that biological processes were different between the two subgroups. Egl-9 family hypoxia-inducible factor 3 (EGLN3) and nucleolar protein 3 (NOL3) were specifically expressed in cancer cell clusters, bulk RNA sequencing data from TCGA confirmed their high expression in ccRCC tissues. GTSE1, CENPF, SMC2 and H2AFV were screened out and applied to the construction of risk score model. A nomogram was generated to predict prognosis of ccRCC by combing the risk score and clinical parameters.ConclusionsWe integrated single-cell and bulk transcriptome data from ccRCC in this study. Two subtypes of ccRCC cells with different biological characteristics and two potential biomarkers of ccRCC were discovered. A novel prognostic model was constructed for clinical application.

Comprehensive analysis of lncRNAs as biomarkers for diagnosis, prognosis, and treatment response in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common histological type of renal carcinoma and has a high recurrence rate and poor outcome. Accurate patient risk stratification based on genetic markers can help to identify the high-risk patient for early and further treatments and would promote patient survival. Long non-coding RNAs (lncRNAs) have attracted widespread attention as biomarkers for early diagnosis, treatment, and prognosis because of their high specificity and sensitivity. Here, we performed a systematic search in NCBI PubMed and found 44 lncRNAs as oncogenes, 18 lncRNAs as tumor suppressors, 199 lncRNAs as diagnostic biomarkers, 62 lncRNAs as prognostic biomarkers, and 3 lncRNAs as predictive biomarkers for ccRCC. We also comprehensively discuss the biological functions and molecular regulatory mechanisms of lncRNAs in ccRCC. Overall, the present study is a systemic analysis to assess the expression and clinical value of lncRNAs in ccRCC, and lncRNAs hold promise to be diagnostic, prognostic, and predictive biomarkers.

Comprehensive analysis of new prognostic signature based on ferroptosis-related genes in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is an aggressive tumor and the most common subtype of RCC. Ferroptosis is a novel form of regulated cell death, and ferroptosis-related genes (FRGs) have been associated with the prognosis of patients with certain cancers. However, the detailed prognostic correlation between FRGs and ccRCC has not yet been elucidated. To address this, the current study used The Cancer Genome Atlas (TCGA) dataset to explore 64 FRGs and determine their prognostic value in ccRCC. Results showed that 52 out of the 64 genes displayed significantly different expression levels in tumor tissue, and 35 out of the 52 differentially expressed genes (DEGs) were associated with overall survival. Subsequently, a four-gene prognostic signature (CD44, DPP4, NCOA4 and SLC7A11) was constructed and could successfully distinguish ccRCC patients with different prognosis in TCGA train and test sets. Furthermore, clinical ccRCC samples from our medical center were used to verify the application value of the new prognostic signature through immunohistochemistry and quantitative real-time polymerase chain reaction (qRT-PCR). Biological functional analysis implied that immune-related functions and pathways were enriched in the TCGA cohort and the immune status scores were significantly different between high- and low-risk sets. These results suggest that the four ferroptosis-related regulatory genes can act as reliable prognostic biomarkers of ccRCC, and might be exploited as potential targets of therapeutic strategies.

LncRNA DGCR5 Isoform-1 Silencing Suppresses the Malignant Phenotype of Clear Cell Renal Cell Carcinoma via miR-211-5p/Snail Signal Axis.

Long non-coding RNAs (lncRNAs) play important roles during the initiation and progression of cancer. We identified DiGeorge Syndrome Critical Region Gene 5 (DGCR5) as a clear cell renal cell carcinoma (ccRCC) cancer- and lineage-specific lncRNA. Agarose gel electrophoresis analysis and sanger sequencing verified two main isoforms of DGCR5 in ccRCC patient tissues and cell lines. Quantitative polymerase chain reaction further demonstrated that the expression level of DGCR5 major isoform (isoform-1) was higher in ccRCC tissues than that in papillary/chromophobe RCC and other multiple solid malignant tumors. We investigate the biological functions of DGCR5 isoform-1 in ccRCC and show that DGCR5 isoform-1 exerts a tumor-promoting effect in ccRCC. DGCR5 isoform-1 is localized in cytoplasm and shares the same binding sequence to the tumor-suppressive miR-211-5p with the epithelial-to-mesenchymal transition key component SNAI. Furthermore, cellular and molecular experiments demonstrate that DGCR5 isoform-1 could sequester miR-211-5p, leading to the elevation of Snail protein and downregulation of its downstream targets and further promoting ccRCC cell proliferation and migration. Thus, our study indicates that DGCR5 isoform-1 could contribute to ccRCC progression by sponging miR-211-5p through regulating the expression of Snail protein and could serve as a reliable diagnostic biomarker in ccRCC.

GNRH1 and LTB4R might be novel immune-related prognostic biomarkers in clear cell renal cell carcinoma (ccRCC)

BackgroundClear cell renal cell carcinoma (ccRCC) occupied most of renal cell carcinoma (RCC), which associated with poor prognosis. The purpose of this study is to screen novel and prognostic biomarkers for patients with ccRCC.Methods and resultsFirstly, Gene Expression Omnibus database was used to collect microarray data for weighted gene co-expression network construction. Gene modules related to prognosis which interest us most were picked out. 90 hub genes were further chosen in the key modules, two of which including gonadotropin releasing hormone 1 (GNRH1) and leukotriene B4 receptor (LTB4R) were screened and validated as immune-related prognostic biomarkers. Based on several public databases and ccRCC tissues collected by ourselves, we performed survival analysis, spearman correlation analysis, receiver operating characteristic (ROC) analysis, quantitative real-time PCR (qRT-PCR), western blotting, immunofluorescence (IF) and immunohistochemistry (IHC) staining for the validation of immune-related prognostic biomarkers. We further explored the relationship between immune-related prognostic biomarker expressions and immunocytes. Finally, gene set enrichment analysis (GSEA) demonstrated that the two immune-related prognostic biomarkers were significantly correlated with cell cycle.ConclusionsGenerally speaking, the present study has identified two novel prognostic biomarkers for patients with ccRCC, which showed strong correlation with prognosis of patients with ccRCC, could further be used as potential prognostic biomarkers in ccRCC.

Expression of AOX1 Predicts Prognosis of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer worldwide, and appropriate cancer biomarkers facilitate early diagnosis, treatment, and prognosis prediction in cancer management. However, an accurate biomarker for ccRCC is lacking. This study identified 356 differentially expressed genes in ccRCC tissues compared with normal kidney tissues by integrative analysis of eight ccRCC datasets. Enrichment analysis of the differentially expressed genes unveiled improved adaptation to hypoxia and metabolic reprogramming of the tumor cells. Aldehyde oxidase 1 (AOX1) gene was identified as a biomarker for ccRCC among all the differentially expressed genes. ccRCC tissues expressed significantly lower AOX1 than normal kidney tissues, which was further validated by immunohistochemistry at the protein level and The Cancer Genome Atlas (TCGA) data mining at the mRNA level. Higher AOX1 expression predicted better overall survival in ccRCC patients. Furthermore, AOX1 DNA copy number deletion and hypermethylation were negatively correlated with AOX1 expression, which might be the potential mechanism for its dysregulation in ccRCC. Finally, we illustrated that the effect of AOX1 as a tumor suppressor gene is not restricted to ccRCC but universally exists in many other cancer types. Hence, AOX1 may act as a potential prognostic biomarker and therapeutic target for ccRCC.

Abstract 226: Tumor-infiltrating lymphocyte diversity and clear cell renal cell carcinoma

Abstract The availability of systemic treatments of metastatic clear cell renal cell carcinoma (ccRCC) has evolved steadily over the past decade, particularly with the availability of drugs that work in the microenvironment through immune checkpoint blockade (ICB). However, various studies have indicated that response to ICB is not likely driven only by mutational burden, neoantigen burden, or PD-L1 status. We here employed genomics approaches to recover V(D)J recombination sequences from primary tumor bulk RNA sequencing from two ccRCC cohorts; Moffitt Total Cancer Care Cohort (n=105) and the Clinical Proteomic Tumor Analysis Consortium Cohort (n=110). We applied an ecological generalized diversity index (GDI) to quantify tumor infiltration by CDR3 sequences from patient tumors using three point-estimate descriptions: richness, evenness, and inflection point of the GDI. GDI has multiple properties that render it more flexible than the commonly used Shannon index, e.g. the inflection point q, which can be understood as a dataset specific diversity estimate that specifically balances richness and evenness of the distribution that defines diversity. Individuals with larger and more aggressive tumors had increased richness diversity of tumoral CDR3 sequences, specifically in sequences recovered from T-cell receptor alpha (TRA) and B-cell immunoglobulin lambda light chain. Furthermore, the TRA inflection point q diversity stratified patients based on survival, with individuals that had a larger inflection point q diversity having improved overall survival (hazard ratio of 0.526, p-value 0.036 from multivariate Cox regression). We also found significant discrimination of diversity between racial and gender differences in tumor-infiltrating lymphocyte diversity. Non-white patients showed a 2.1-fold increase in evenness in B-cell receptors compared to white patients; T-cell receptors gamma and delta inflection point q diversity was increased at least 1.7-fold in female patients compared to male patients. These demographic differences highlight the need to further investigate race- and gender-related differences in immune infiltration in ccRCC. With ICB being first line therapy of metastatic ccRCC, it is critical to define and evaluate novel analytical tools to characterize the level of immune cell infiltration and diversity. We have demonstrated here that the ecological generalized diversity index shows promise as a novel quantitative, prognostic biomarker for ccRCC, with the potential to extend to other malignancies. Citation Format: Meghan C. Ferrall-Fairbanks, Nicholas Chakiryan, Boris I. Chobrutskiy, Youngchul Kim, Jamie K. Teer, Anders Berglund, James Mulé, Michelle Fournier, Erin M. Siegel, Esther N. Katende, George Blanck, Brandon J. Manley, Philipp M. Altrock. Tumor-infiltrating lymphocyte diversity and clear cell renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 226.

Low Expression Levels of SLC22A12 Indicates a Poor Prognosis and Progresses Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) accounts for approximately 4/5 of all kidney cancers. Accumulation of minor changes in the cellular homeostasis may be one cause of ccRCC. Therefore, we downloaded the RNA sequencing and survival data of the kidney renal cell carcinoma (KIRC) cohort from the Cancer Genome Atlas (TCGA) database. After the univariate and multivariate Cox regression analyses, 19 kidney-specific differentially expressed genes (DEGs) were found. Solute Carrier Family 22 Member 12 (SLC22A12) resulted in an independent prognostic predictor for both overall survival (OS) and disease-free survival (DFS). SLC22A12 expression was lower in tumoral tissue compared to normal tissue. Moreover, patients in the SLC22A12 low expression group had a higher pathological stage and worse survival than the high expression group. Additionally, qRT-PCR assay, immunoblotting test (IBT), and immunohistochemical (IHC) analyses of cancer tissues/cells and the corresponding normal controls verified that SLC22A12 is downregulated in ccRCC. Receiver operator characteristic (ROC) curves showed that the low expression level of SLC22A12 could be a good diagnostic marker for ccRCC (AUC=0.7258; p <0.0001). Gene set enrichment analysis (GSEA) showed that SLC22A12 expression levels are related to metabolism, cell cycle, and tumor-related signaling pathways. GO and KEGG analyses revealed that SLC22A12 transports multiple organic compounds, ions, and hormones and participates in the extracellular structure organization. Furthermore, SLC22A12 over-expression in vitro inhibited the proliferation, migration, and invasion of renal cancer cells by regulating PI3K/Akt pathways. Such effects were reversed when knocking out SLC22A12. In summary, as a transporter for many vital metabolites, SLC22A12 may affect tumor cell survival through its impacts on the mentioned metabolites. In conclusion, this study uncovered that SLC22A12 is a promising prognostic and diagnostic biomarker for ccRCC.

Detection of von Hippel-Lindau gene mutation in circulating cell-free DNA for clear cell renal cell carcinoma.

The therapeutic landscape of metastatic clear cell renal cell carcinoma (ccRCC) has rapidly expanded, and there is an urgent need to develop noninvasive biomarkers that can select an optimal therapy or evaluate the response in real time. To evaluate the clinical utility of circulating tumor DNA (ctDNA) analysis in ccRCC, we established a highly sensitive assay to detect mutations in von Hippel‐Lindau gene (VHL) using a combination of digital PCR and multiplex PCR–based targeted sequencing. The unique assay could detect VHL mutations with a variant allele frequency (VAF) <1.0%. Further, we profiled the mutation status of VHL in 76 cell‐free DNA (cfDNA) and 50 tumor tissues from 56 patients with ccRCC using the assay. Thirteen VHL mutations were identified in cfDNA from 12 (21.4%) patients with a median VAF of 0.78% (range, 0.13%‐4.20%). Of the 28 patients with VHL mutations in matched tumor tissues, eight (28.6%) also had VHL mutation in cfDNA with a median VAF of 0.47% (range, 0.13%‐2.88%). In serial ctDNA analysis from one patient, we confirmed that the VAF of VHL mutation changed consistent with tumor size by radiographic imaging during systemic treatment. In conclusion, VHL mutation in cfDNA was detected only in a small number of patients even using the highly sensitive assay; nevertheless, we showed the potential of ctDNA analysis as a novel biomarker in ccRCC.

Circ_RPL23A acts as a miR-1233 sponge to suppress the progression of clear cell renal cell carcinoma by promoting ACAT2.

Clear cell renal cell carcinoma (ccRCC) is a prevalent urological carcinoma with high metastatic risk. Circular RNAs (circRNAs) have been identified as effective diagnostic and therapeutic biomarkers for ccRCC. This research aims to disclose the effect and regulatory mechanism of circRNA ribosomal protein L23a (circ_RPL23A) in ccRCC. We performed quantitative real-time polymerase chain reaction (qRT-PCR) to examine circ_RPL23A, microRNA-1233 (miR-1233) and acetyl-coenzyme A acetyltransferase 2 (ACAT2). Cell cycle progression, apoptosis, cell viability, invasion and migration, which were respectively conducted by using flow cytometry, 3-(4, 5-dimethylthiazol-2-y1)-2, 5-diphenyl tetrazolium bromide (MTT), transwell assays. The levels of ACAT2 protein and cell cycle proteins, proliferation-associated protein, and epithelial-mesenchymal transition (EMT) associated proteins were measured by western blot. Target relationship was analyzed via dual-luciferase reporter assay and RNA pull down assay. The animal model was used to study how circ_RPL23A affects in vivo. Circ_RPL23A was lower expressed in ccRCC tissues and cells. The elevated circ_RPL23A suppressed cell cycle progression, proliferation, migration and invasion but promoted apoptosis in ccRCC cells. MiR-1233 was a target of circ_RPL23A and direct targeted to ACAT2. Besides, circ_RPL23A exerted its anti-tumor effect by sponging miR-1233, and then relieved the inhibition effect of miR-1233 on ACAT2. Overexpression of circ_RPL23A also curbed ccRCC tumor growth in vivo. Circ_RPL23A inhibited ccRCC progression by upregulating ACAT2 expression by competitively binding miR-1233, which might provide an in-depth cognition for ccRCC pathogenesis and circ_RPL23A might be a promising biomarker in ccRCC diagnosis and treatment.

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

Simple SummaryThe 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.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.

Celastrol Attenuates Lipid Accumulation and Stemness of Clear Cell Renal Cell Carcinoma via CAV-1/LOX-1 Pathway.

Clear cell renal cell carcinoma (ccRCC) is characterized by abnormal lipid accumulation. Celastrol is a pentacyclic triterpene extracted from Tripterygium wilfordii Hook F with anti-cancer activity. In the present study, the anticancer effects of celastrol on ccRCC and the underlying mechanisms were studied. Patients with reduced high density lipoprotein (HDL) and elevated levels of triglyceride (TG), total cholesterol (TC), low density lipoprotein (LDL) was found to have higher risk of ccRCC. In ccRCC clinical samples and cell lines, caveolin-1 (CAV-1) was highly expressed. CAV-1 was identified as a potential prognostic biomarker for ccRCC. Celastrol inhibited tumor growth and decreased lipid deposition promoted by high-fat diet in vivo. Celastrol reduced lipid accumulation and caveolae abundance, inhibited the binding of CAV-1 and lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) in ccRCC cells. Furthermore, celastrol attenuated stemness through blocking Wnt/β-catenin pathway after knockdown of CAV-1 and LOX-1. Therefore, the findings suggest that celastrol may be a promising active ingredient from traditional Chinese medicine for anti-cancer therapy.

Cancer Cells' Metabolism Dynamics in Renal Cell Carcinoma Patients' Outcome: Influence of GLUT-1-Related hsa-miR-144 and hsa-miR-186.

Simple SummaryRenal cell carcinoma (RCC) is a metabolic associated cancer and the most common and lethal neoplasia in the adult kidney. This study aimed to understand the potential role of hsa-miR-144-5p and hsa-miR-186-3p (which target Glucose Transporter 1—GLUT-1) in clear cell RCC (ccRCC) glycolysis status, as well as their potential as biomarkers. A decrease of intracellular levels of these miRNAs and increase of their excretion was associated with an increase of GLUT-1’s levels and glycolysis’ markers. RCC patients presented higher plasmatic levels of hsa-miR-186-3p than healthy individuals and hsa-miR144-5p’s higher levels were associated with early clinical stages of RCC. Additionally, patients with low plasmatic levels of hsa-miR-144-5p and high plasmatic levels of hsa-miR-186-3p (high-risk group) showed a worse overall survival. Overall, these results indicate that circulating hsa-miR-144-5p and hsa-miR-186-3p may be potential biomarkers of ccRCC prognosis.The cancer cells’ metabolism is altered due to deregulation of key proteins, including glucose transporter 1 (GLUT-1), whose mRNA levels are influenced by microRNAs (miRNAs). Renal cell carcinoma (RCC) is the most common and lethal neoplasia in the adult kidney, mostly due to the lack of accurate diagnosis and follow-up biomarkers. Being a metabolic associated cancer, this study aimed to understand the hsa-miR-144-5p and hsa-miR-186-3p’s potential as biomarkers of clear cell RCC (ccRCC), establishing their role in its glycolysis status. Using three ccRCC lines, the intra- and extracellular levels of both miRNAs, GLUT-1’s mRNA expression and protein levels were assessed. Glucose consumption and lactate production were evaluated as glycolysis markers. A decrease of intracellular levels of these miRNAs and increase of their excretion was observed, associated with an increase of GLUT-1’s levels and glycolysis’ markers. Through a liquid biopsy approach, we found that RCC patients present higher plasmatic levels of hsa-miR-186-3p than healthy individuals. The Hsa-miR144-5p’s higher levels were associated with early clinical stages. When patients were stratified according to miRNAs plasmatic levels, low plasmatic levels of hsa-miR-144-5p and high plasmatic levels of hsa-miR-186-3p (high-risk group) showed the worst overall survival. Thus, circulating levels of these miRNAs may be potential biomarkers of ccRCC prognosis.

Urinary Volatilomics Unveils a Candidate Biomarker Panel for Noninvasive Detection of Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer usually associated with asymptomatic development and risk of systemic progression. Hence, reliable molecular biomarkers of ccRCC are needed to provide early and minimally invasive detection. In this study, urinary volatilome profiling of patients diagnosed with ccRCC (n = 75), and cancer-free controls (n = 75), was performed to investigate the presence of a volatile signature characteristic of ccRCC. Volatile organic compounds (VOCs) in general, and more specifically volatile carbonyl compounds (VCCs), present in urine were extracted by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS). Supervised multivariate models showed a good discriminatory power of ccRCC patients from controls in urine. Overall, 22 volatile metabolites were found significantly altered between the two groups, including aldehydes, ketones, aromatic hydrocarbons, and terpenoids. A candidate six-biomarker panel, comprising octanal, 3-methylbutanal, benzaldehyde, 2-furaldehyde, 4-heptanone, and p-cresol, depicted the best performance for ccRCC detection with 83% sensitivity, 79% specificity, and 81% accuracy. Moreover, the ccRCC urinary volatilome signature suggested dysregulation of energy metabolism and overexpression of enzymes associated with carcinogenesis. These findings provide the molecular basis for the fine-tuning of gas-sensing materials for application in the development of a bioelectronic sensor.

Nuclear and cytosolic pS727-STAT3 levels correlate with overall survival of patients affected by clear cell renal cell carcinoma (ccRCC)

Clear cell renal cell carcinoma (ccRCC) is the most frequent and aggressive subtype of renal carcinoma. So far, the basis of its oncogenesis remains unclear resulting in a deficiency of usable and reliable biomarkers for its clinical management. Previously, we showed that nuclear expression of the signal transducer and activator of transcription 3 (STAT3), phosphorylated at its serine 727 (pS727), was inversely proportional to the overall survival of ccRCC patients. Therefore, in the present study, we validated the value of pS727-STAT3 as a clinically relevant biomarker in ccRCC. This work is a retrospective study on 82 ccRCC patients treated with nephrectomy and followed-up for 10 years. Immunohistochemical expression of pS727-STAT3 was analyzed on a tissue microarray and nuclear and cytosolic levels were correlated with clinical outcome of patients. Our results showed that pS727-STAT3 levels, whether in the nucleus (p = 0.002; 95% CI 1.004–1.026) or the cytosol (p = 0.040; 95% CI 1.003–1.042), significantly correlate with patients’ survival in an independent-manner of clinicopathological features (Fuhrman grade, risk group, and tumor size). Moreover, we report that patients with high pS727-STAT3 levels who undergone adjuvant therapy exhibited a significant stabilization of the disease (~ 20 months), indicating that pS727-STAT3 can pinpoint a subset of patients susceptible to respond well to treatment. In summary, we demonstrated that high pS727-STAT3 levels (regardless of their cellular location) correlate with low overall survival of ccRCC patients, and we suggested the use of pS727-STAT3 as a prognostic biomarker to select patients for adjuvant treatment to increase their survival.