Identification of genes that correlate clear cell renal cell carcinoma and obesity and exhibit potential prognostic value.
Ontology highlight
ABSTRACT: Background
Renal cell carcinoma (RCC) is a common urologic malignancy. Although the relationship between clear cell RCC (ccRCC) and obesity has been well-established by several large-scale retrospective studies, the molecular mechanisms and genetic characteristics behind this correlation remains unclear. In the current study, several bioinformatics tools were used to identify the key genes in ccRCC related to obesity.Methods
Microarray data comparing ccRCC with normal renal tissues in patients with and without obesity were downloaded from the GEO database for screening of differentially expressed genes (DEGs). The DEGs were verified with expression level and survival analysis using several online bioinformatics tools.Results
In the current study, the differential expression of five genes correlated with both ccRCC and obesity; IGHA1 and IGKC as oncogenes, and MAOA, MUC20 and TRPM3 as tumor suppressor genes. These genes were verified by comparing the relationship between the expression levels and survival outcomes from open-source data in The Cancer Genome Atlas (TCGA) dataset.Conclusions
In conclusion, the five genes differentially expressed in ccRCC and obesity are related to disease progression and prognosis, and therefore could provide prognostic value for patients with ccRCC.
SUBMITTER: Zhou J
PROVIDER: S-EPMC7947457 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:m6A, the main form of mRNA modification, participates in regulating multiple normal and pathological biological events, especially in tumorigenesis. However, there is little known about the association of m6A-related genes with prognosis of clear cell renal cell cancer (ccRCC). Therefore, the prognostic value of m6A-related genes was investigated using Kaplan-Meier curves of overall survival (OS) with the log-rank test and Cox regression analysis. The differential expression of YTHDF2 mRNA in ccRCC and tumor-adjacent normal tissues and associated with clinicopathological characteristics was also analyzed. The alteration of cancer signaling pathways was screened by Gene Set Enrichment Analysis (GSEA). Univariate analysis showed that 15 m6A-related genes (including YTHDF2) were closely related to prognosis. Multivariate analysis further confirmed that YTHDF2 could serve as an independent prognostic factor for the OS of ccRCC patients (P < 0.001). Low-level expression of YTHDF2 had poor prognosis in ccRCC patients with lower tumor-node-metastasis (TNM) stage, age > 61, non-distant metastasis, non-lymph node metastasis, female gender, and higher histological grade (P < 0.05). Moreover, YTHDF2 expression in ccRCC tissues (N = 529) is significantly lower than that of tumor-adjacent normal tissues (N = 72, P = 0.0086). Furthermore, GSEA demonstrated that AKT/mTOR/GSK3 pathway, EIF4 pathway, CHREBP2 pathway, MET pathway, NFAT pathway, FAS pathway, EDG1 pathway, and CTCF pathway are altered in tumors with high YTHDF2 expression. Taken together, our results demonstrated that YTHDF2 (an m6A-related gene) could serve as a potential prognostic biomarker of ccRCC, and targeting epigenetic modification may be a novel therapeutic strategy for the treatment of ccRCC.
| S-EPMC7546891 | biostudies-literature
Project description:PurposeClear cell renal cell carcinoma (ccRCC) is among the most common malignant tumors worldwide, with a high incidence rate and poor prognosis. Currently, there are no biomarkers that can accurately guide prognostic evaluation and therapeutic strategy for ccRCC. The prognostic value and potential biological function of claudin-8 (CLDN8), a critical component of tight junctions in ccRCC, remain unclear.MethodsSequencing data were obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, and Gene Expression Omnibus databases. R packages were used to explore CLDN8 mRNA expression levels and analyze differentially expressed genes. Results were validated in clinical specimens and cell lines, and bioinformatics analyses were conducted to explore the potential biological functions of CLDN8. Finally, functional analyses were carried out using 786-O ccRCC cell line.ResultsBoth CLDN8 mRNA and protein expression levels were significantly lower in ccRCC compared with the normal control tissues. Kaplan-Meier analyses showed that low CLDN8 expression levels were associated with the poor overall survival, while univariate and multivariate Cox regression indicated that CLDN8 could serve as an independent prognostic factor in patient with ccRCC. Bioinformatic and Western blot analyses showed that CLDN8 suppressed proliferation, migration, and invasion of 786-O ccRCC cells through the epithelial-mesenchymal transition and AKT pathways.ConclusionCLDN8 could serve as an independent prognostic factor in ccRCC, in which it suppresses 786-O proliferation, migration, and invasion through EMT and AKT pathways.
| S-EPMC7501992 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma, and immune-related genes (IRGs) are key contributors to its development. In this study, the gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database and the cBioPortal database, respectively. IRGs were obtained from the ImmPort database. We analyzed the expression of IRGs in ccRCC, and discovered 681 that were differentially expressed between ccRCC and normal kidney tissues. Univariate Cox regression analysis was used to identify prognostic differentially expressed IRGs (PDEIRGs). Using Lasso regression and multivariate Cox regression analyses, we detected seven optimal PDEIRGs (PLAU, ISG15, IRF9, ARG2, RNASE2, SEMA3G and UCN) and used them to construct a risk model to predict the prognosis of ccRCC patients. This model accurately stratified patients with different survival outcomes and precisely identified patients with different mutation burdens. Our findings suggest the seven PDEIRGs identified in this study are valuable prognostic predictors in ccRCC patients. These genes could be used to investigate the developmental mechanisms of ccRCC and to design individualized treatments for ccRCC patients.
| S-EPMC6932908 | biostudies-literature
Project description: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.
| S-EPMC11364764 | biostudies-literature
Project description:Epithelial-to-mesenchymal transition (EMT) is important in tumor invasiveness and metastasis. We aimed to determine prognostic value of six key EMT markers (CDH1, CDH2, SNAI1, SNAI2, VIM, TWIST1) in clear cell renal cell carcinoma (ccRCC). A total of 533 ccRCC patients with RNASeq data from The Cancer Genome Atlas (TCGA) cohort were included for analysis. Gene expression of these EMT markers was compared between tumor and normal tissues based on Oncomine database and TCGA cohort. Their correlations with progression-free survival (PFS) and overall survival (OS) were also examined in both TCGA cohort and FUSCC (Fudan University Shanghai Cancer Center) cohort. Cox proportional hazards regression model and Kaplan-Meier plot were used to assess the relative factors. Functional enrichment analyses were utilized to describe biologic function annotations and significantly involved hallmarks pathways of each gene. We found that Epithelial marker, CDH1 expression was lower, while mesenchymal markers (CDH2, SNAI1, VIM, TWIST1) expression was higher in ccRCC primary tumors. In the TCGA cohort, we found that patients with higher expression of VIM, TWIST1 or lower expression of CDH1 had worse prognosis. Further, in the FUSCC cohort, we confirmed the predictive ability of mesenchymal markers and epithelial marker expression in PFS and OS of ccRCC patients. After generating Cox regression models, EMT markers (CDH1, SNAI1, VIM, and TWIST1) were independent prognostic factors of both PFS and OS in ccRCC patients. Our preliminary EMT prediction model can facilitate further screening of EMT biomarkers and cast a better understanding of EMT gene function in ccRCC.
| S-EPMC6977664 | biostudies-literature
Project description:Multiple targeted therapy for advanced clear-cell renal cell carcinoma (RCC) has substantially improved patient outcome, but complete remission is uncommon and many tumors eventually develop resistance. Mechanistic, preclinical, and early clinical data highlight c-Met / hepatocyte growth factor receptor as a promising target for RCC therapeutic agents.We have examined MET expression, frequency of MET gene copy gains and MET gene mutation in a large, hospital-based series of renal cell carcinomas with long-term follow-up information.Out of a total of 572 clear-cell RCC, only 17% were negative for MET expression whereas 32% showed high protein levels. High MET expression and MET copy number gains were associated with an aggressive phenotype and an unfavorable patient outcome. Elevated protein levels in absence of gene amplification were not attributed to mutations, based on results of targeted next-generation sequencing.Our data reveal that clear-cell RCC with MET upregulation show an aggressive behavior and MET copy number increase is evident in a substantial percentage of patients with high-grade carcinomas and metastatic disease. Diagnostic assessment of MET expression and amplification may be of predictive value to guide targeted therapy against MET signaling in patients with clear-cell RCC.
| S-EPMC5352033 | biostudies-literature
Project description: Not available
| S-BSST812 | biostudies-other
Project description:Background RNA binding proteins (RBPs) have previously been demonstrated to be involved in the initiation and development of human cancers. However, its role in clear cell renal cell carcinoma (ccRCC) is not yet clear. The study was intended to explore the diagnostic and prognostic value of RBPs in ccRCC via bioinformatics methods of public datasets. Methods Data download from the Cancer Genome Atlas (TCGA) database was used to identify differentially expressed RBPs between normal renal samples and cancerous samples. Then, we performed the gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of differentially expressed genes (DEGs) using the ClusterProfiler package. Next, the protein-protein interaction (PPI) network was built by the online tool STRING database and Cytoscape software. The significant module and hub genes were screened by MCODE and Cytohubba plugin, respectively. Lastly, we performed a systematical analysis to investigate the diagnostic and prognostic value of candidate RBPs. Results A total of 133 DEGs, including 39 upregulated RBPs and 94 downregulated RBPs, were screened between ccRCC samples and noncancerous samples. From these data, eight candidate RBPs (RPS2, GAPDH, RPS20, EIF4A1, RPL18, RPL13, RPL18A, and RPS19) were identified. Conclusions In summary, we screened differentially expressed RBPs of ccRCC, which were enriched mainly in various biological processes and signaling pathways. Furthermore, we identified eight candidate RBPs, which could serve as potential biomarkers of ccRCC.
| S-EPMC8797574 | biostudies-literature
Project description:Aquaporins (AQPs) are a kind of transmembrane proteins that exist in various organs of the human body. AQPs play an important role in regulating water transport, lipid metabolism and glycolysis of cells. Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the kidney, and the prognosis is worse than other types of renal cell cancer (RCC). The impact of AQPs on the prognosis of ccRCC and the potential relationship between AQPs and the occurrence and development of ccRCC are demanded to be investigated. In this study, we first explored the expression pattern of AQPs by using Oncomine, UALCAN, and HPA databases. Secondly, we constructed protein-protein interaction (PPI) network and performed function enrichment analysis through STRING, GeneMANIA, and Metascape. Then a comprehensive analysis of the genetic mutant frequency of AQPs in ccRCC was carried out using the cBioPortal database. In addition, we also analyzed the main enriched biological functions of AQPs and the correlation with seven main immune cells. Finally, we confirmed the prognostic value of AQPs throughGEPIA and Cox regression analysis. We found that the mRNA expression levels of AQP0/8/9/10 were up-regulated in patients with ccRCC, while those of AQP1/2/3/4/5/6/7/11 showed the opposite. Among them, the expression differences of AQP1/2/3/4/5/6/7/8/9/11 were statistically significant. The differences in protein expression levels of AQP1/2/3/4/5/6 in ccRCC and normal renal tissues were consistent with the change trends of mRNA. The biological functions of AQPs were mainly concentrated in water transport, homeostasis maintenance, glycerol transport, and intracellular movement of sugar transporters. The high mRNA expression levels of AQP0/8/9 were significantly correlated with worse overall survival (OS), while those of AQP1/4/7 were correlated with better OS. AQP0/1/4/9 were prognostic-related factors, and AQP1/9 were independent prognostic factors. In general, this research has investigated the values of AQPs in ccRCC, which could become new survival markers for ccRCC targeted therapy.
| S-EPMC8896691 | biostudies-literature
Project description:Tumor immune microenvironment (TIME) plays an important role in tumor diagnosis, prevention, treatment and prognosis. However, the correlation and potential mechanism between clear cell renal cell carcinoma (ccRCC) and its TIME are not clear. Therefore, we aimed to identify potential prognostic biomarkers related to TIME of ccRCC. Unsupervised consensus clustering analysis was performed to divide patients into different immune subgroups according to their single-sample gene set enrichment analysis (ssGSEA) scores. Then, we validated the differences in immune cell infiltration, prognosis, clinical characteristics and expression levels of HLA and immune checkpoint genes between different immune subgroups. Weighted gene coexpression network analysis (WGCNA) was used to identify the significant modules and hub genes that were related to the immune subgroups. A nomogram was established to predict the overall survival (OS) outcomes after independent prognostic factors were identified by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses. Five clusters (immune subgroups) were identified. There was no significant difference in age, sex or N stage. And there were significant differences in race, T stage, M stage, grade, prognosis and tumor microenvironment. WGCNA revealed that the red module has an important relationship with TIME, and obtained 14 hub genes. In addition, the nomogram containing LAG3 and GZMK accurately predicted OS outcomes of ccRCC patients. LAG3 and GZMK have a certain correlation with the prognosis of ccRCC patients, and play an important role in the TIME. These two hub genes deserve further study as biomarkers of the TIME.
| S-EPMC9037198 | biostudies-literature