Identification of KIF20A as a tumor biomarker and forwarder of clear cell renal cell carcinoma.
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ABSTRACT:
SUBMITTER: Xiao W
PROVIDER: S-EPMC8439995 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The last decade has witnessed revolutionary advances taken in immunotherapy for various malignant tumors. However, immune-related molecules and their characteristics in the prediction of clinical outcomes and immunotherapy response in clear cell renal cell carcinoma (ccRCC) remain largely unclear. C-C Motif Chemokine Ligand 4 (CCL4) was extracted from the intersection analysis of common differentially expressed genes (DEGs) of four microarray datasets from the Gene Expression Omnibus database and immune-related gene lists in the ImmPort database using Cytoscape plug-ins and univariate Cox regression analysis. Subsequential analysis revealed that CCL4 was highly expressed in ccRCC patients, and positively correlated with multiple clinicopathological characteristics, such as grade, stage and metastasis, while negatively with overall survival (OS). We performed gene set enrichment analysis (GSEA) and gene set variant analysis (GSVA) with gene sets coexpressed with CCL4, and observed that gene sets positively related to CCL4 were enriched in tumor proliferation and immune-related pathways while metabolic activities in the negatively one. To further explore the correlation between CCL4 and immune-related biological process, the CIBERSORT algorithm, ESTIMATE method, and tumor mutational burden (TMB) score were employed to evaluate the tumor microenvironment (TME) characteristics of each sample and confirmed that high CCL4 expression might give rise to high immune cell infiltration. Moreover, correlation analysis revealed that CCL4 was positively correlated with common immune checkpoint genes, such as programmed cell death protein 1 (PD-1), cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and lymphocyte activating 3 (LAG3). Overall, this study demonstrated that CCL4 might serve as a potential immune-related prognostic biomarker to predict clinical outcomes and immunotherapy response in ccRCC. Moreover, CCL4 might contribute to TME modulation, indicating the mechanism CCL4 involved in tumor proliferation and metastasis, which could provide novel therapeutic perceptions for ccRCC patients.
| S-EPMC8652234 | biostudies-literature
Project description:Background:Aurora kinase B (AURKB) is an important carcinogenic factor in various tumors, while its role in clear cell renal cell carcinoma (ccRCC) still remains unclear. This study aimed to investigate its prognostic value and mechanism of action in ccRCC. Methods:Gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. R software was utilized to analyze the expression and prognostic role of AURKB in ccRCC. Gene set enrichment analysis (GSEA) was used to analyze AURKB related signaling pathways in ccRCC. Results:AURKB was expressed at higher levels in ccRCC tissues than normal kidney tissues. Increased AURKB expression in ccRCC correlated with high histological grade, pathological stage, T stage, N stage and distant metastasis (M stage). Kaplan-Meier survival analysis suggested that high AURKB expression patients had a worse prognosis than patients with low AURKB expression levels. Multivariate Cox analysis showed that AURKB expression is a prognostic factor of ccRCC. GSEA indicated that genes involved in autoimmune thyroid disease, intestinal immune network for IgA production, antigen processing and presentation, cytokine-cytokine receptor interaction, asthma, etc., were differentially enriched in the AURKB high expression phenotype. Conclusions:AURKB is a promising biomarker for predicting prognosis of ccRCC patients and a potential therapeutic target. In addition, AURKB might regulate progression of ccRCC through modulating intestinal immune network for IgA production and cytokine-cytokine receptor interaction, etc. signaling pathways. However, more research is necessary to validate the findings.
| S-EPMC6752188 | biostudies-literature
Project description:ObjectiveTo study the expression of adipophilin (PLIN2), a lipid storage-associated cell protein, in different subtypes of renal cell cancer and to elucidate its prognostic value.Materials and methodsTwo-hundred-seventy-five patients with renal cell carcinoma (RCC) were included in this study. Immunohistochemistry with a polyclonal antibody to adipophilin was used on the tissue microarray (formalin-fixed, paraffin-embedded tissue) for detection of adipophilin. Median follow-up time was 91 (range 1-159) months in the whole cohort and 100 (1-159) months for patients with clear-cell RCC. Additional validation for adipophilin was performed using publicly available gene expression data for clear cell RCC from The Cancer Genome Atlas (TCGA).ResultsAdipophilin expression was detected in 14.3% of papillary RCC, in 0% of chromophobe RCC and in 58.7% of clear-cell RCC in the cytoplasm or at the membrane. Only membrane expression was correlated with other clinical parameters (pT-stage, pN-stage, R-status, sex) and showed a prognostic significance in univariate analysis with regard to overall survival of patients with clear cell subtype (HR 2.90, 95% CI 1.55-5.42, p=0.001), which failed significance on multivariate analysis. mRNA expression of PLIN2 on TCGA data using best selected cut-off was prognostically significant in both univariate (HR 1.76, 95% CI 1.28-2.42, p = 0.0005) and multivariate analyses (HR 1.46, 95% CI 1.05-2.04, p = 0.0257).ConclusionsAdipophilin is a novel and still understudied prognostic biomarker in clear cell renal cell carcinoma which deserves further study.
| S-EPMC5438682 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies and lacks reliable biomarkers for diagnosis and prognosis, which results in high incidence and mortality rates of ccRCC. In this study, ISG20, HJURP, and FOXM1 were identified as hub genes via weighted gene co-expression network analysis (WGCNA) and Cox regression analysis. Samples validation showed that only ISG20 was up-regulated in ccRCC. Therefore, ISG20 was selected for further study. High ISG20 expression was associated with poor overall survival and disease-free survival. Furthermore, the expression of ISG20 could effectively differentiate ccRCC from normal tissues and was positively correlated to clinical stages. Functional experiments proved that knockdown of ISG20 expression could obviously inhibit cell growth, migration, and invasion in ccRCC cells. To find the potential mechanisms of ISG20, gene set enrichment analysis (GSEA) was performed and revealed that high expression of ISG20 was significantly involved in metastasis and cell cycle pathways. In addition, we found that ISG20 could regulate the expression of MMP9 and CCND1. In conclusion, these findings suggested that ISG20 promoted cell proliferation and metastasis via regulating MMP9/CCND1 expression and might serve as a potential biomarker and therapeutic target in ccRCC.
| S-EPMC7053611 | biostudies-literature
Project description:Invasion and metastasis are the main causes of poor prognosis in patients with clear cell renal cell carcinoma (ccRCC). The homeodomain interacting protein kinases (HIPKs) can regulate cell proliferation and apoptosis. Little is known about the prognostic role of HIPKs in ccRCC. Here we use Kaplan-Meier survival analysis and multivariate analysis to analyze the correlation of overall survival (OS) and disease-free survival (DFS). ROC curves analyzed the relationship between clinicopathological parameters and HIPK3 expression in ccRCC. Univariate analysis and multivariate analysis confirmed that the expression of HIPK3 was associated with OS (HR, 0.701; P=0.041) and DFS (HR, 0.630; P=0.012). Low HIPK3 expression was a poor prognostic factor and HIPK3 expression was significantly down-regulated in ccRCC cancer tissues when compared with normal renal tissues. In vitro cell results also confirmed that HIPK3 over-expression could inhibit tumor growth and malignant characteristics. The results indicate that low expression of HIPK3 in ccRCC tissues is significantly associated with poor survival rates in tumor patients, and HIPK3 may be used as a valuable biomarker and inhibitor of ccRCC.
| S-EPMC7906163 | biostudies-literature
Project description:Background:Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer, which represents the 9th most frequently diagnosed cancer. However, the molecular mechanism of occurrence and development of ccRCC is indistinct. Therefore, the research aims to identify the hub biomarkers of ccRCC using numerous bioinformatics tools and functional experiments. Methods:The public data was downloaded from the Gene Expression Omnibus (GEO) database, and the differently expressed genes (DEGs) between ccRCC and normal renal tissues were identified with GEO2R. Protein-protein interaction (PPI) network of the DEGs was constructed, and hub genes were screened with cytoHubba. Then, ten ccRCC tumor samples and ten normal kidney tissues were obtained to verify the expression of hub genes with the RT-qPCR. Finally, the neural network model was constructed to verify the relationship among the genes. Results:A total of 251 DEGs and ten hub genes were identified. AURKB, CCNA2, TPX2, and NCAPG were highly expressed in ccRCC compared with renal tissue. With the increasing expression of AURKB, CCNA2, TPX2, and NCAPG, the pathological stage of ccRCC increased gradually (P < 0.05). Patients with high expression of AURKB, CCNA2, TPX2, and NCAPG have a poor overall survival. After the verification of RT-qPCR, the expression of hub genes was same as the public data. And there were strong correlations between the AURKB, CCNA2, TPX2, and NCAPG with the verification of the neural network model. Conclusion:After the identification and verification, AURKB, CCNA2, TPX2, and NCAPG might be related to the occurrence and malignant progression of ccRCC.
| S-EPMC7317307 | biostudies-literature
Project description:BackgroundAntiangiogenic agents that specifically target vascular endothelial growth factor receptor (VEGFR), such as sunitinib, have been utilized as the standard therapy for metastatic clear cell renal cell carcinoma (ccRCC) patients. However, most patients eventually show no responses to the targeted drugs, and the mechanisms for the resistance remain unclear. This study is aimed to identify pivotal molecules and to uncover their potential functions involved in this adverse event in ccRCC treatment.MethodsTwo datasets, GSE64052 and GSE76068, were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the limma package in R software. The gene set enrichment analysis (GSEA) was conducted using clusterProfiler package. A protein-protein interaction (PPI) network was built using the STRING database and Cytoscape software. Kaplan-Meier survival curves were plotted using R software. qRT-PCR and Western blotting were used to detect the MX2 and pathway expression in RCC cell lines. Sunitinib-resistant cell lines were constructed, and loss-of-function experiments were conducted by knocking down MX2. All statistical analyses were performed using R version 3.6.1 and SPSS 23.0.ResultsA total of 760 DEGs were derived from two datasets in GEO database, and five hub genes were identified, among which high-level MX2 exhibited a pronounced correlation with poor overall survival (OS) in sunitinib-resistant ccRCC patients. Clinical correlation analysis and Gene Set Variation Analysis (GSVA) on MX2 showed that the upregulation of MX2 was significantly related to the malignant phenotype of ccRCC, and it was involved in several pathways and biological processes associated with anticancer drug resistance. qRT-PCR and Western blotting revealed that MX2 was distinctly upregulated in sunitinib-resistant RCC cell lines. Colony formation assay and Cell Counting Kit-8 (CCK8) assay showed that MX2 strongly promoted resistant capability to sunitinib of ccRCC cells.ConclusionMX2 is a potent indicator for sunitinib resistance and a therapeutic target in ccRCC patients.
| S-EPMC8299280 | biostudies-literature
Project description:BackgroundClear cell renal cell carcinoma (ccRCC), derived from renal tubular epithelial cells, is the most common malignant tumor of the kidney. The study of key genes related to the pathogenesis of ccRCC has become important for gene target therapy.MethodsBioinformatics analysis of The Cancer Genome Atlas (TCGA), the NCBI Gene Expression Omnibus (GEO) database, USUC Xena database, cBioPortal for Cancer Genomics, and MethSurv were performed to examine the aberrant genetic pattern and prognostic significance of leucine-rich repeat kinase 2 (LRRK2) expression and its relationship to clinical parameters. Immunohistochemistry and Western blot were performed to verify LRRK2 expression. The regulation of ccRCC tumor cell lines proliferation by LRRK2 was examined by CCK8 assay.ResultsBioinformatics analysis showed that LRRK2 expression was up-regulated and largely correlated with DNA methylation in ccRCC. The up-regulation of LRRK2 was confirmed in ccRCC tissue immunohistochemically and by protein analysis. The level of expression was related to gender, pathological grade, stage, and metastatic status of ccRCC patients. Meanwhile, Kaplan-Meier analysis showed that high expression of LRRK2 correlates to a better prognosis; knockdown of LRRK2 expression attenuated the proliferation ability of ccRCC tumor cell lines; protein-protein interaction network analysis showed that LRRK2 interacts with HIF1A and EGFR.ConclusionWe found that LRRK2 may play an important role in the tumorigenesis and progression of ccRCC. Our findings provided a potential predictor and therapeutic target in ccRCC.
| S-EPMC8254929 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. Progression in immunotherapy has provided novel options for the ccRCC treatment. However, the understanding of the ccRCC microenvironment and the potential therapeutic targets in the microenvironment is still unclear. Here, we analyzed the gene expression profile of ccRCC tumors from the Cancer Genome Atlas (TCGA) and calculated the abundance ratios of immune cells for each sample. Then, seven types of immune cells were found to be correlated to overall survival, and 3863 immune-related genes were identified by analyzing differentially expressed genes. We also found that the function of immune-related genes was mainly focused on ligand-receptor binding and signaling pathway transductions. Additionally, we identified 13 hub genes by analyzing the protein-protein interaction network, and seven of them are related to overall survival. Our study not only expands the understanding of fundamental biological features of microenvironment but also provides potential therapeutic targets.
| S-EPMC7493752 | biostudies-literature
Project description: Not available
| S-DIXA-D-1153 | biostudies-other