Prognosis Of ccRCC Research Articles

Multi-omics analysis of Prolyl 3-hydroxylase 1 as a prognostic biomarker for immune infiltration in ccRCC

The formation of human collagen requires the presence of Prolyl 3-hydroxylase 1 (P3H1), but the regulatory mechanism of P3H1 remained insufficiently understood. Our study aimed to identify the role of P3H1 in clear cell renal cell carcinoma (ccRCC). P3H1 expression in ccRCC was validated using multiple databases and in vitro experiments. We performed a correlation analysis of P3H1 with drug sensitivity, immune checkpoints, and immune cell infiltration using transcriptome and single-cell sequencing. Drawing upon the Encyclopedia of RNA Interactomes database, we selected P3H1 as the focal point of our investigation, meticulously uncovering the intricate network of microRNAs and lncRNAs that potentially orchestrate ceRNA mechanisms. This study employs a multidimensional approach integrating vitro assays and multi-omics bioinformatics analyses to investigate P3H1’s impact on ccRCC prognosis, immune modulation, immune checkpoints, ceRNA regulatory network, drug sensitivity, and therapeutic responses, aiming to uncover new insights into its therapeutic potential and inform future clinical strategies.

NEDD4L Suppresses Proliferation and Promotes Apoptosis by Ubiquitinating RAC2 Expression and Acts as a Prognostic Biomarker in Clear Cell Renal Cell Carcinoma

Neural precursor cell expressed developmentally down-regulated 4-like (NEDD4L) is an HECT (homologous to E6AP C terminus)-type E3 ubiquitin ligase. As previously documented, bioinformatics analysis revealed NEDD4L is downregulated in clear cell renal cell carcinoma (ccRCC). However, the target substrate regulated by NEDD4L in ccRCC remains unknown. Here, we assessed whether NEDD4L regulates Ras-related C3 botulinum toxin substrate 2 (RAC2) expression in ccRCC. In our study, integrated bioinformatics analysis indicated that low expression of NEDD4L and high expression of RAC2 were both associated with poor prognosis of ccRCC, pro-tumorigenic immunity, and multiple tumor-associated pathways. Our data confirmed the hypothesis indicated in the previous studies related to the downregulation of NEDD4L in ccRCC. NEDD4L was identified to target the RAC2 threonine 108–proline motif, and RAC2 overexpression rescued NEDD4L-mediated cell apoptosis and inhibition of cell growth and migration. Therefore, RAC2 is a novel and first identified target of NEDD4L in ccRCC, and the aberrant less expression of NEDD4L and consequent RAC2 upregulation may contribute to renal carcinogenesis. Our study offers insight into NEDD4L as a potential future therapeutic target for renal cell carcinoma or as a novel prognostic biomarker.

Identification of exosomal ceRNA networks as prognostic markers in clear cell renal cell carcinoma.

Aggressive clear cell renal cell carcinoma (ccRCC) has a bad prognosis. We seek new ccRCC biomarkers for diagnosis and treatment. We used exoRBase and The Cancer Genome Atlas Database to compare DEmRNAs, DEmiRNAs, DElncRNAs, and DEcircRNAs in ccRCC and normal renal tissues. CircRNAs and circRNAs targeting microRNAs (miRNAs) were anticipated and taken intersections, and several databases assessed the targeted link between common miRNAs and messenger RNAs (mRNAs). The Cancer Genome Atlas database was used to create a predictive mRNA signature that was validated in E-MTAB-1980. Finally, we examined competing endogenous RNA network miRNAs and long noncoding RNAs for ccRCC predictive biomarkers using overall survival analysis. We built the first competing endogenous RNA regulation network of circRNA-lncRNA-miRNA-mRNA and found that it substantially correlates with ccRCC prognosis. We unveiled ccRCC's posttranscriptional regulation mechanism in greater detail. Our findings identified novel biomarkers for ccRCC diagnosis, therapy, and prognosis.

ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC. We analyzed the expression levels of ERBB2 in various cancers from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA-seq data were analyzed using R packages to identify differentially expressed genes between the high and low ERBB2 expression groups in the TCGA-KIRC dataset. Spearman correlation analysis was performed to determine the correlation between ERBB2 expression and immune cell infiltration, immune checkpoint expression, and PTEN expression. DNA methylation changes and genetic alterations in ERBB2 were assessed using the MethSurv and cBioPortal databases. Logistic regression analysis was performed to determine the correlation between ERBB2 expression and the clinicopathological characteristics of ccRCC patients. The diagnostic and prognostic value of ERBB2 was assessed using Kaplan‒Meier (K‒M) survival curves, diagnostic ROC curves, time-dependent ROC curves, nomogram models, and Cox regression models. The expression level of ERBB2 is lower in tumor tissues of ccRCC patients than in the corresponding control tissues. Differentially expressed genes associated with ERBB2 were significantly enriched in the pathways “BMP2WNT4FOXO1 pathway in primary endometrial stromal cell differentiation” and “AMAN pathway”. In ccRCC tissues, ERBB2 expression levels were associated with immune cell infiltration, immune checkpoints, and PTEN. The DNA methylation status of 10 CpG islands in the ERBB2 gene was associated with the prognosis of ccRCC. ERBB2 expression levels in ccRCC tissues were associated with race, sex, T stage, M stage, histological grade, and pathological stage. Cox regression analysis showed that ERBB2 was a potential independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in ccRCC patients. ROC curve analysis showed that the expression level of ERBB2 could accurately distinguish between ccRCC tissue and adjacent normal renal tissue. Our study showed that ERBB2 expression in ccRCC tissues can be of clinical importance as a potential diagnostic and prognostic biomarker.

Construction and experimental verification of a novel nine-glycosylation-related gene prognostic risk model for clear cell renal carcinoma

ObjectivePatients with clear cell renal carcinoma (ccRCC) typically have poor prognosis. Glycosylation modification plays an important role in ccRCC. This study aimed to develop a novel signature for predicting ccRCC prognosis based on glycosylation-related genes (GRGs). MethodsDifferentially expressed GRGs (DE_GRGs) were identified using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus and used for constructing the risk model. The function of key genes was validated. ResultsTwenty-two DE_GRGs were intersected between GSE53757 and TCGA. Patients with ccRCC were divided into two clusters based on the expression profile of these DE_GRGs. Significant differences in the infiltration of 10 immune cell types were observed between two subclusters. Subsequently, the prognostic signatures of nine DE_GRGs (CHST9, COLGALT1, FUT3, FUT6, HS3ST2, POMGNT2, ST8SIA4, UGT3A1, and UGT8) were established. Patients in the high-risk group showed a poorer prognosis relative to the low-risk group. According to univariate and multivariate Cox regression analyses, the risk score, stage, and grade could be independent prognostic factors. A nomogram incorporating information on gender, age, risk group, TNM stage, and clinical stage showed accurate prediction in the survival probability. Except for CHST9, HS3ST2, and ST8SIA4, expression patterns of the remaining 6 DE_GRGs in Caki-1and 786-O cells were confirmed by quantitative real-time PCR. FUT6 overexpression resulted in the inhibition of proliferation, migration, and invasion of ccRCC cells. ConclusionThis study established a nine-DE_GRG-based prognostic signature, which independently predicted ccRCC prognosis. This finding emphasizes that GRGs are stratification factors for the precise prognosis of ccRCC.

CTCF-activated FUCA1 functions as a tumor suppressor by promoting autophagy flux and serum α-L-fucosidase serves as a potential biomarker for prognosis in ccRCC.

Notably, clear cell renal cell carcinoma (ccRCC) is characterized by a distinct metabolic tumor phenotype that involves the reprogramming of multiple metabolic pathways. Although there is increasing evidence linking FUCA1 to malignancies, its specific role and downstream signaling pathways in ccRCC remain poorly understood. Here we found that FUCA1 expression was significantly downregulated in ccRCC tissues, which also predicts poor prognosis of ccRCCpatients. Moreover, enhancing FUCA1 expression resulted in reduced invasion and migration of ccRCC cells, further indicating its protective role. CHIP-qPCR and luciferase assays showed that CTCF was an upstream transcription factor of FUCA1 and could reverse the effects caused by FUCA1 inactivation. The change in FUCA1 led to changes in the results of various autophagy-related proteins and the mRFP-GFP-LC3 dual fluorescence system, indicating that it may play a role in the fusion stage of autophagy. Protein-protein interaction analysis revealed that FUCA2 exhibited the closest interaction with FUCA1 and strongly predicted the prognosis of ccRCC patients. Additionally, serum AFU encoded by FUCA2 could serve as a valuable predictor for survival in ccRCC patients. FUCA1 suppresses invasion and migration of ccRCC cells, with its activity being modulated by CTCF. FUCA1 regulates the autophagy process in ccRCC cells by influencing the fusion between autophagosomes and lysosomes. FUCA2 shares similarities with FUCA1, and elevated serum AFU levels along with increased expression of FUCA2 are indicative of a favorable prognosis in ccRCC.

Identification of a novel PANoptosis-related gene signature for predicting the prognosis in clear cell renal cell carcinoma.

PANoptosis has been shown to play an important role in tumorigenesis and gain more attention. Yet, the prognostic significance of PANoptosis-related genes has not been investigated more in clear cell renal cell carcinoma (ccRCC). The aim of this research was designed to identify and create a signature of PANoptosis-related genes which was expected to predict prognosis of ccRCC more effectively. The transcriptome data and clinical information were collected from The Cancer Genome Atlas database and the Gene Expression Omnibus database. Optimal differentially expressed PANoptosis-related genes, which were closely associated with prognosis and employed to construct a risk score, were extracted by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression and multivariate Cox analysis. We performed Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curves to complete this process. By adopting univariate and multivariate analysis, the constructed risk score was assessed to verify whether it could be taken as an independent contributor for prognosis. Moreover, we created a nomogram in order to predict overall survival (OS) of ccRCC. Five differentially expressed PANoptosis-related genes were screened out and used to construct a risk score. Our results showed that ccRCC patients with high risk score had a poor prognosis and shorter OS. The results of Kaplan-Meier curves and the area under the receiver operating characteristic curves of 1-, 3-, and 5-year OS indicated that the prediction performance was satisfactory. Additionally, the risk model could be taken as an independent prognostic factor in training and validation cohorts. The nomogram exhibited excellent reliability in predicting OS, which was validated by calibration curves. We identified 5 PANoptosis-related genes, which were used to construct a risk score and a nomogram for prognostic prediction with reliable predictive capability. The present study may provide new potential therapeutic targets and precise treatment strategies for ccRCC.

Identification of HDAC10 as a candidate oncogene in clear cell renal carcinoma that facilitates tumor proliferation and metastasis

BackgroundClear cell renal cell carcinoma (ccRCC) remains one of the most lethal urological malignancies even though a great number of improvements in diagnosis and management have achieved over the past few decades. Accumulated evidence revealed that histone deacetylases (HDACs) play vital role in cell proliferation, differentiation and apoptosis. Nevertheless, the biological functions of histone deacetylation modification related genes in ccRCC remains poorly understood.MethodBulk transcriptomic data and clinical information of ccRCC patients were obtained from the TCGA database and collected from the Chinese PLA General Hospital. A total of 36 histone deacetylation genes were selected and studied in our research. Univariate cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, random forest (RF) analysis, and protein-protein interaction (PPI) network analysis were applied to identify key genes affecting the prognosis of ccRCC. The ‘oncoPredict’ algorithm was utilized for drug-sensitive analysis. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the potential biological function. The ssGSEA algorithm was used for tumor immune microenvironment analysis. The expression levels of HDAC10 were validated by RT-PCR and immunohistochemistry (IHC). 5-ethynyl-2′-deoxyuridine (EdU assay), CCK-8 assay, cell transwell migration and invasion assay and colony formation assay were performed to detect the proliferation and invasion ability of ccRCC cells. A nomogram incorporating HDAC10 and clinicopathological characteristics was established to predict the prognosis of ccRCC patients.ResultTwo machine learning algorithms and PPI analysis identified four histone deacetylation genes that have a significant association with the prognosis of ccRCC, with HDAC10 being the key gene among them. HDAC10 is highly expressed in ccRCC and its high expression is associated with poor prognosis for ccRCC patients. Pathway enrichment and the experiments of EdU staining, CCK-8 assay, cell transwell migration and invasion assay and colony formation assay demonstrated that HDAC10 mediated the proliferation and metastasis of ccRCC cells and involved in reshaping the tumor microenvironment (TME) of ccRCC. A clinically reliable prognostic predictive model was established by incorporating HDAC10 and other clinicopathological characteristics ( https://nomogramhdac10.shinyapps.io/HDAC10_Nomogram/ ).ConclusionOur study found the increased expression of HDAC10 was closely associated with poor prognosis of ccRCC patients. HDAC10 showed a pro-tumorigenic effect on ccRCC and promote the proliferation and metastasis of ccRCC, which may provide new light on targeted therapy for ccRCC.

Prognosis and progression of phagocytic regulatory factor-related gene combinations in clear cell renal cell carcinoma (ccRCC).

Developing signatures based on specific characteristics to predict prognosis has become a research hotspot in oncology. However, the prognostic value of phagocytosis regulators in clear cell renal cell carcinoma (ccRCC) remains unclear. The aim of the present study was to investigate the prognostic significance of phagocytosis regulators in ccRCC by constructing a prognostic model related to phagocytosis regulators, and to use this model to evaluate the prognosis and treatment effects in ccRCC patients. Firstly, kidney renal clear cell carcinoma (KIRC) transcriptome data (RNA-Seq) and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Based on literatures PMID 34497417 and PMID 30397336, 167 of the 173 phagocytosis regulator genes collected in the literature were expressed in TCGA-KIRC. The relationship between these regulators and macrophages was revealed through single-sample gene set enrichment analysis (ssGSEA), and their biological and pathway involvements were further analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) method were employed to further select phagocytosis regulators with prognostic potential, leading to the construction of a prognostic regression model. Additionally, univariate and multivariate Cox regression analyses were conducted to confirm the prognostic independence of genes associated with phagocytosis regulators. Finally, the relationship between phagocytosis regulator-related genes and patients' immune microenvironments and immunotherapy responses was explored. We have constructed a prognostic model of a combination of genes associated with phagocytosis regulators using LASSO Cox regression analysis of genes, and our combined model was shown to be an independent prognostic factor. The model had optimal performance in predicting long-term survival. Clinical features were significantly correlated with phagocytosis regulatory gene scores. Tumors with higher levels of grade and stage were more prone to have higher phagocytosis regulatory genes. And our study suggests that phagocytosis regulatory genes do not play an ideal role in predicting the efficacy of immunotherapy in patients. We have constructed a prognostic model using a combination of genes associated with phagocytosis regulators, providing new insights into the prognosis and progression of ccRCC.

Prognostic value of KLFs family genes in renal clear cell carcinoma

Numerous studies have shown that the Krüppel-like factors (KLFs) family of transcription factors regulate various eukaryotic physiological processes including the proliferation, differentiation, senescence, death, and carcinogenesis of animal cells. In addition, they are involved in the regulation of key biological processes such as cell cycle, DNA repair, and immune response. Current studies focus on investigating the role of KLFs in normal physiological conditions and the incidence and development of diseases. However002C the significance of KLFs family genes in clear cell renal cell carcinoma (ccRCC) remains partly understood; therefore, an in-depth investigation of their role and clinical value in this cancer is desired. The study aimed to investigate the role of KLF family genes in the incidence, development, and prognosis of ccRCC, and to identify the related potential biomarkers and therapeutic targets. The expression of KLFs in the RNA sequencing data of 613 ccRCCs from the TCGA database was analyzed using R software, and UALCAN and GEPIA assessed the expression of KLF genes in ccRCC. Real-time fluorescence quantitative PCR analysis was performed using 10 pairs of paired ccRCC sample tissues and renal cancer cell lines from the First Affiliated Hospital of Nanchang University. Overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) of Kidney Clear Cell Carcinoma (KIRC) samples at differential expressions of KLFs in the TCGA database were analyzed using the R software, followed by generating a nomogram prediction model. GSCALite assessed the interactions of KLF genes with miRNAs and generated network maps. Protein interaction network maps of 50 neighboring genes associated with KLF mutations were analyzed using STRING with GO and KEGG functional enrichment analyses. The cBioPortal determined the probability of KLF gene mutations and their impact on OS and disease-free survival (DFS) in patients with ccRCC. Immune cell infiltration of KLFs was analyzed using TIMER. Finally, GSCALite was used to analyze the drug sensitivity and associated pathways of action of KLFs. Correlation validation using cellular experiments. KLF3/5/9/15 were significantly downregulated in ccRCC tissues, whereas KLF16/17 were upregulated compared with the adjacent tissues. Patients with high mRNA levels of KLF16/17 showed significantly lower OS, PFI, and DSS, whereas KLF3/5/9 showed a reverse trend. In patients with ccRCC, a significant correlation was observed between KLF mutations and OS and DSS. Furthermore, the correlation of KLF3/5/9 with immune cell infiltration was stronger than that of KLF15/16, while KLF17 was significantly associated with the Epithelial-Mesenchymal Transition (EMT) pathway. Overexpression of KLF5 inhibits the proliferative and migratory capacity of renal cancer cells (786-O and OS-RC-2), as well as their sensitivity to relevant small molecule drugs. Our research revealed the expression levels and biological significance of KLF genes in ccRCC, particularly highlighting the potential of KLF5 as a promising biomarker and therapeutic target for effective prognosis and diagnosis of ccRCC.

SHC1 serves as a prognostic and immunological biomarker in clear cell renal cell carcinoma: a comprehensive bioinformatics and experimental analysis

SHC1 plays a crucial regulatory role in various tumors, but its significance in predicting prognosis and immune response in clear cell renal cell carcinoma (ccRCC) is yet to be determined. In this study, we conducted a bioinformatics analysis of SHC1 expression, prognosis, and immunological functions in ccRCC using multiple databases. The association between SHC1 and immune infiltration, immune escape, and immunotherapy in ccRCC was systematically established. In addition, we validated our results by western blot of tumor and adjacent-tumor samples from nine ccRCC patients, as well as three renal carcinoma cell lines compared to a normal renal cell line. Our analysis revealed that the mRNA expression level of SHC1 in ccRCC tissues is significantly higher than that in normal tissues. Consistently, western blot experiment showed ccRCC tissues and cell lines exhibit higher protein levels that normal tissues and cell lines. Importantly, patients with low expression of SHC1 demonstrated a higher survival rate, indicating that SHC1 could serve as an independent prognostic factor for predicting survival in ccRCC. Additionally, high expression of SHC1 was associated with increased severe immune cell infiltration, enhanced immune escape, and higher immunotherapy scores. Hence, SHC1 emerges as a novel and easily detectable biomarker for predicting clinical outcomes, immune escape, and immunotherapy response in patients with ccRCC.

The role of BUD31 in clear cell renal cell carcinoma: prognostic significance, alternative splicing, and tumor immune environment

BUD31, a splicing factor, is linked to various cancers. This study examines BUD31's expression, prognostic value, mutation profile, genomic instability, tumor immune environment, and role in clear cell renal cell carcinoma (ccRCC), focusing on cell cycle regulation via alternative splicing. BUD31 expression was analyzed using TCGA and GTEx databases across 33 cancers. Techniques included IHC staining, survival analysis, Cox regression, and nomogram construction. Mutation landscape, genomic instability, and tumor immune microenvironment were evaluated. Functional assays on ccRCC cell lines involved BUD31 knockdown, RNA sequencing, and alternative splicing analysis. BUD31 was upregulated in multiple tumors, including ccRCC. High BUD31 expression correlated with worse survival outcomes and was identified as an independent predictor of poor prognosis in ccRCC. High BUD31 expression also correlated with increased genomic instability and a less active immune microenvironment. BUD31 knockdown inhibited cell proliferation, migration, and invasion in vitro and reduced tumor growth in vivo. RNA sequencing identified 390 alternative splicing events regulated by BUD31, including 17 cell cycle-related genes. KEGG analysis highlighted pathways involved in cell cycle regulation, indicating BUD31's role in promoting cell cycle progression through alternative splicing. BUD31 is upregulated in various tumors and is associated with poor outcomes, increased genomic instability, and a suppressed immune microenvironment in ccRCC. BUD31 promotes cell cycle progression via alternative splicing, suggesting it as a prognostic biomarker and potential therapeutic target in ccRCC.

Construction of an autophagy-related genes risk model as predicting prognosis: BAG1 suppresses growth of clear cell renal cell carcinoma

BackgroundThe incidence of clear cell renal cell carcinoma (ccRCC) is increasing annually. While the cure rate and prognosis of early ccRCC are promising, the 5-year survival rate of patients with metastatic ccRCC is below 12%. Autophagy disfunction is closely related to infection, cancer, neurodegeneration and aging. Nevertheless, there has been limited exploration of the association between autophagy and ccRCC through bioinformatics analysis. MethodsA novel risk model of autophagy-related genes (ARGs) was constructed to predict the prognosis of patients with ccRCC and guide the individualized treatment to some extent. Relevant data samples were obtained from the TCGA database, and ccRCC-related ARGs were identified by Pearson correlation analysis, leading to the establishment of a risk model covering 10 ccRCC-related ARGs. Many indicators were used to assess the accuracy of the risk model. ResultsReceiver operating characteristic (ROC) curve analysis showed that the risk model had high accuracy, indicating that the risk model could predict the prognosis of ccRCC patients. Moreover, the findings revealed significant differences about immune and metabolic features in low- and high-risk groups. The study also found that BAG1 within the risk model was closely related to the prognosis of ccRCC and an independent risk factor. In vitro and in vivo experiments validated for the first time that BAG1 could suppress the proliferation, migration, and invasion of ccRCC. ConclusionThe construction of ARGs risk model, can well predict the prognosis of ccRCC patients, and provide guidance for individual therapy to patients. It was also found that BAG1 has significant prognostic value for ccRCC patients and acts as a tumor suppressor gene in ccRCC. These findings have crucial implications for the prognosis and treatment of ccRCC patients.

MDK promotes M2 macrophage polarization to remodel the tumour microenvironment in clear cell renal cell carcinoma

The efficacy of immunotherapy for clear cell renal cell carcinoma (ccRCC), especially advanced ccRCC, is limited, presenting a clinical challenge. This limitation is closely tied to the immune regulation network. Understanding the heterogeneity of the tumour microenvironment (TME) is crucial for developing advanced ccRCC therapies. Using publicly available ccRCC data (scRNA-seq, bulk RNA-seq, and somatic mutation data), a multiomics study was performed to explore TME heterogeneity. Three distinct ccRCC immune subtypes were identified through combined scRNA-seq and bulk RNA-seq analysis. A prognostic model based on unique cell signalling molecules in immunosuppressive tumour subtype was validated in the TCGA and CheckMate cohorts. MDK emerged as a critical regulatory gene in the immunosuppressive subtype, predicting a poor ccRCC prognosis and a poor immunotherapy response. MDK promotes M2 macrophage polarization via the MDK-LRP1 interaction, and the inhibition of MDK suppressed M2 polarization. This study revealed the heterogeneity of the ccRCC TME and a reliable prognostic model, shedding light on the vital role of MDK in the immunosuppressive TME and paving the way for optimized ccRCC immunotherapy.

53 Associations between body composition, ClearCode34, and clinical outcomes in localized clear cell renal cell carcinoma

Abstract Background Emerging evidence suggests that pre-surgical body composition is a prognostic factor for cancer outcomes. Lower skeletal muscle quantity and radiodensity have been associated with renal cell carcinoma (RCC) outcomes in other studies, while reports of the relationship between visceral adipose tissue and RCC outcomes have been inconsistent. Mechanisms underlying these associations are unclear but may relate to tumor biology. We leveraged a large molecular epidemiology study of localized clear cell renal cell carcinoma (ccRCC) patients to examine how pre-surgical body composition features were associated with survival post-nephrectomy as well as ClearCode34 status, a previously validated prognostic gene expression signature. Methods The RESOLVE study at Memorial Sloan Kettering Cancer Center is a retrospective study of 1,239 patients with stage I-III ccRCC undergoing nephrectomy without systemic therapy. Pre-surgical CT scans at the third lumbar vertebrae were segmented for the cross-sectional areas and radiodensities of skeletal muscle, subcutaneous adipose and visceral adipose tissues using Automatica software. Formalin-fixed, paraffin-embedded tumor tissue samples were available for 929 patients, which were sent to the University of North Carolina at Chapel Hill and assayed for gene expression. RNA was extracted from these samples and analyzed using the Nanostring nCounter system on a custom panel of 356 genes, including the 34 genes used in the ClearCode34 assay. Of the 929 patients with tumor tissue available, gene expression data from 837 patients (90.1%) passed RNA extraction and data QC. Samples were classified into either ccA or ccB ClearCode34 classes using a reference data set and PAM (prediction analysis of microarrays) centroid-based classification. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for disease-free survival (DFS) within five years of diagnosis using Cox proportional hazards models for both body composition variables and ClearCode34 subtype. We also estimated odds ratios (ORs) and 95% CIs for associations between ClearCode34 subtype and body composition with logistic regression. All multivariable models were adjusted for age, sex, and all body composition variables. Results Of the 837 patients in our analytic sample, 219 (26%) had ccB tumors. Men, patients with high stage or grade tumors, and patients with chronic kidney disease prior to nephrectomy were more likely to present with ccB tumors. Lower skeletal muscle density (SMD) was significantly associated with lower five-year DFS [HR (95% CI) per 10 HU decrease in SMD: 1.7 (1.2, 2.3)]. While no other body composition features were significantly associated, we also observed non-significantly increased HRs for VATI and VATD [HR (95% CIs): 1.3 (0.8, 2.0) and 1.5 (0.9, 2.7), respectively]. ClearCode34 subtype was significantly associated with five-year DFS, where patients with ccB tumors had poorer DFS [HR (95% CI): 1.7 (1.1, 2.5)] compared to patients with ccA tumors. Notably, we observed no significant associations between any body composition feature and ClearCode34 in univariable analyses. However, in multivariable models that accounted for all body composition variables simultaneously as well as age and sex, lower SMD emerged as significantly associated with ccB subtype [OR (95% CI) per 10 HU decrease in SMD: 1.3 (1.0, 1.7)]. Conclusions Our findings suggest that the associations observed between body composition features and clinical outcomes in ccRCC may be related to tumor biology. Lower pre-surgical SMD, which may represent myosteatosis and metabolic dysregulation in ccRCC patients, was associated with both decreased five-year DFS and an increased likelihood of presenting with a more aggressive ccB tumor. Future studies should investigate body composition features related to ccRCC prognosis and additional markers of tumor biology, such as immune-related gene expression patterns, to extend these findings.

Clear Cell Renal Cell Carcinoma: A Comprehensive Review of its Histopathology, Genetics, and Differential Diagnosis.

Clear cell renal cell carcinoma (ccRCC) is the predominant subtype of renal epithelial tumor, accounting for roughly 2% of all malignancies. Clinically, it often presents in the sixth to seventh decade of life, predominantly in men. Pathologically, these tumors exhibit a distinctive golden yellow cut surface, usually arising from the renal cortex. Their microscopic features are characterized by solid and nested architectures of cells with clear or eosinophilic granular cytoplasm and a prominent vascular network. A hallmark genetic feature is the inactivation of the VHL gene situated on chromosome 3p25. The majority of ccRCCs are sporadic (over 95%), typically presenting as a single mass; and a small percentage have a hereditary basis, often associated with VHL disease, characterized by multiple bilateral tumors with an earlier onset. Immunohistochemically, ccRCC tumors express PAX8, CA9 box like pattern, and CD10 but are generally negative for AMACR (35% positive) and KRT7 (15% positive). The prognosis of ccRCC is largely determined by its TNM stage, ISUP/WHO nucleolar grade, and the presence of specific aggressive features. This review article delves into the detailed gross, microscopic, molecular, and clinical features of ccRCC, offering comprehensive insights into its diagnosis, management, and prognosis.

Epigenetic modification of PHLDA2 is associated with tumor microenvironment and unfavorable outcome of immune checkpoint inhibitor-based therapies in clear cell renal cell carcinoma

BackgroundA substantial proportion of patients with metastatic clear cell renal cell carcinoma (ccRCC) cannot derive benefit from immune checkpoint inhibitor (ICI) plus anti-angiogenic agent combination therapy, making identification of predictive biomarkers an urgent need. The members of pleckstrin homology-like domain family A (PHLDA) play critical roles in multiple cancers, whereas their roles in ccRCC remain unknown.MethodsTranscriptomic, clinical, genetic alteration and DNA methylation data were obtained for integrated analyses from TCGA database. RNA sequencing was performed on 117 primary tumors and 79 normal kidney tissues from our center. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis were performed to explore transcriptomic features. Data from three randomized controlled trials (RCT), including CheckMate025, IMmotion151, JAVELIN101, were obtained for validation.ResultsMembers of PHLDA family were dysregulated in pan-cancer. Elevated PHLDA2 expression was associated with adverse clinicopathologic parameters and worse prognosis in ccRCC. Aberrant DNA hypomethylation contributed to up-regulation of PHLDA2. An immunosuppressive microenvironment featured by high infiltrates of Tregs and cancer-associated fibroblasts, was observed in ccRCC with higher PHLDA2 expression. Utilizing data from three RCTs, the association of elevated PHLDA2 expression with poor therapeutic efficacy of ICI plus anti-angiogenic combination therapy was confirmed.ConclusionsOur study revealed that elevated PHLDA2 expression regulated by DNA hypomethylation was correlated with poor prognosis and immunosuppressive microenvironment, and highlighted the role of PHLDA2 as a robust biomarker for predicting therapeutic efficacy of ICI plus anti-angiogenic agent combination therapy in ccRCC, which expand the dimension of precision medicine.

Comprehensive analysis of MAPK genes in the prognosis, immune characteristics, and drug treatment of renal clear cell carcinoma using bioinformatic analysis and Mendelian randomization

Mitogen-activated protein kinase (MAPK) signalling is vitally important in tumour development and progression. This study is the first to comprehensively analyse the role of MAPK-family genes in the progression, prognosis, immune-cell infiltration, methylation, and potential therapeutic value drug candidates in ccRCC. We identified a novel prognostic panel of six MAPK-signature genes (MAP3K12, MAP3K1, MAP3K5, MAPK1, MAPK8, MAPK9), and introduced a robust MAPK-signature risk model for predicting ccRCC prognosis. Model construction, evaluation, and external validation using datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database demonstrated its stability, as well as high sensitivity and specificity. Enrichment analysis suggested the participation of immune-mediated mechanism in MAPK dysregulation in ccRCC. Immune-infiltration analysis confirmed the relationship and revealed that the MAPK-signature risk model might stratify immunotherapy response in ccRCC, which was verified in drug sensitivity analysis and validated in external ccRCC immunotherapy dataset (GSE67501). Potential therapeutic drug predictions for key MAPKs using DSigDB, Network Analyst, CTD, and DGIdb were subsequently verified by molecular docking with AutoDock Vina and PyMol. Mendelian randomization further demonstrated the possibilities of the MAPK-signature genes as targets for therapeutic drugs in ccRCC. Methylation analysis using UALCAN and MethSurv revealed the participation of epigenetic modifications in dysregulation and survival difference of MAPK pathway in ccRCC. Among the key MAPKs, MAP3K12 exhibited the highest significance, indicating its independent prognostic value as single gene in ccRCC. Knockout and overexpression validation experiments in vitro and in vivo found that MAP3K12 acted as a promoter of tumour progression in RCC, suggesting a pivotal role for MAP3K12 in the proliferation, migration, and invasion of RCC cells. Our findings proposed the potential of MAPK-signature genes as biomarkers for prognosis and therapy response, as well as targets for therapeutic drugs in ccRCC.

Prognostic Model and Immune Response of Clear Cell Renal Cell Carcinoma Based on Co-Expression Genes Signature

BackgroundThe identification of reliable prognostic markers is crucial for optimizing patient management and improving clinical outcomes in clear cell renal cell carcinoma (ccRCC). MethodsWe used the GSE89563 dataset from the GEO database and the Kidney Clear Cell Carcinoma (KIRC) dataset from the TCGA database to develop a prognostic model based on weighted gene co-expression network analysis (WGCNA) and non-negative matrix factorization (NMF) to predict disease progression and prognosis in ccRCC. ResultWe utilized WGCNA to identify risk genes and applied NMF to stratify high-risk populations in ccRCC. We characterized the immune gene features of these high-risk groups and ultimately developed a risk prediction model for ccRCC patients using a Lasso regression approach. The risk score was calculated as follows: Risk score = SUM (-0.136394797 ANK3 + 0.004238138 BIVM_ERCC5 - 0.046248451 C4orf19 - 0.036013206 F2RL3 - 0.125531316 GNG7 - 0.012698109 METTL7A + 0.078462369 MSTO1 - 0.050450656 PINK1 - 0.059446590 SLC16A12 - 0.039883686 SLC2A9 + 0.083310722 TLCD1 - 0.059801739 WDR72 + 0.071430088 ZNF117). ConclusionWe develop a prognostic model for clear cell renal cell carcinoma and analyzed immune response in subgroups and confirmed protein-level expression concordance.

Identification of a cancer driver gene-associated lncRNA signature for prognostic prediction and immune response evaluation in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) predominates among kidney cancer cases and is influenced by mutations in cancer driver genes (CDGs). However, significant obstacles persist in the early diagnosis and treatment of ccRCC. While various genetic models offer new hopes for improving ccRCC management, the relationship between CDG-related long non-coding RNAs (CDG-RlncRNAs) and ccRCC remains poorly understood. Therefore, this study aims to construct prognostic molecular features based on CDG-RlncRNAs to predict the prognosis of ccRCC patients, and aims to provide a new strategy to enhance clinical management of ccRCC patients. This study employed Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses to comprehensively investigate the association between lncRNAs and CDGs in ccRCC. Leveraging The Cancer Genome Atlas (TCGA) dataset, we identified 97 prognostically significant CDG-RlncRNAs and developed a robust prognostic model based on these CDG-RlncRNAs. The performance of the model was rigorously validated using the TCGA dataset for training and the International Cancer Genome Consortium (ICGC) dataset for validation. Functional enrichment analysis elucidated the biological relevance of CDG-RlncRNA features in the model, particularly in tumor immunity. Experimental validation further confirmed the functional role of representative CDG-RlncRNA SNHG3 in ccRCC progression. Our analysis revealed that 97 CDG-RlncRNAs are significantly associated with ccRCC prognosis, enabling patient stratification into different risk groups. Development of a prognostic model incorporating key lncRNAs such as HOXA11-AS, AP002807.1, APCDD1L-DT, AC124067.2, and SNHG3 demonstrated robust predictive accuracy in both training and validation datasets. Importantly, risk stratification based on the model revealed distinct immune-related gene expression patterns. Notably, SNHG3 emerged as a key regulator of the ccRCC cell cycle, highlighting its potential as a therapeutic target. Our study established a concise CDG-RlncRNA signature and underscored the pivotal role of SNHG3 in ccRCC progression. It emphasizes the clinical relevance of CDG-RlncRNAs in prognostic prediction and targeted therapy, offering potential avenues for personalized intervention in ccRCC.