Dataset Information

Identification of KIF23 as a Prognostic Biomarker Associated With Progression of Clear Cell Renal Cell Carcinoma.

ABSTRACT: About 3% of adult cancers are caused by renal cell carcinoma (RCC) and its pathogenesis remains elusive. Among RCC, clear cell renal cell carcinoma (ccRCC) is the predominant histological subtype. Resistance to conventional treatments leaves few treatment options for advanced ccRCC. Although the transcriptome profile of primary ccRCC has been comprehensively summarized, the transcriptome profile of metastatic ccRCC is still lacking. In this study we identified a list of metastasis-related genes and constructing a metastasis-associated prognostic gene signature. By analyzing data from GSE85258 and GSE105288 datasets, 74 genes were identified as metastasis-related genes. To construct prognostic features, we downloaded the expression data of ccRCC from the Cancer Genome Atlas (TCGA). Metastasis-associated genes were initially selected through the LASSO Cox regression analysis and 12 metastasis-related were included to construct prognostic model. Transcriptome profile, patient prognosis, and immune cell infiltration characteristics differed between low- and high-risk groups after grouping according to median risk score. Through explored the functions of differentially expressed genes (DEGs) between the two groups. Kinesin family member 23 (KIF23) was identified as a prognostic marker in ccRCC patients. Furthermore, inhibition of KIF23 expression reduced the proliferation, migration and invasion of ccRCC cells. We further demonstrated that KIF23 promote nuclear translocation of β-catenin in ccRCC cells, which provides novel insight into the functions and molecular machinery of KIF23 in ccRCC.

SUBMITTER: Wu Z

PROVIDER: S-EPMC9035542 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of KIF23 as a Prognostic Biomarker Associated With Progression of Clear Cell Renal Cell Carcinoma.

Wu Zonglong Z Song Yimeng Y Wu Yaqian Y Ge Liyuan L Liu Zhuo Z Du Tan T Zhang Shudong S Ma Lulin L

Frontiers in cell and developmental biology 20220411

About 3% of adult cancers are caused by renal cell carcinoma (RCC) and its pathogenesis remains elusive. Among RCC, clear cell renal cell carcinoma (ccRCC) is the predominant histological subtype. Resistance to conventional treatments leaves few treatment options for advanced ccRCC. Although the transcriptome profile of primary ccRCC has been comprehensively summarized, the transcriptome profile of metastatic ccRCC is still lacking. In this study we identified a list of metastasis-related genes ...[more]

PMID: 35478956

Similar Datasets

Project description:BackgroundOne of the widespread forms of kidney tumor is clear cell renal cell carcinoma (ccRCC), with poor prognosis and insensitivity to radio chemotherapy as there is limited capacity to understand the disease mechanism. This study aims at identifying potential biomarkers and the underlying processes of ccRCC using bioinformatics analysis.MethodsTranscriptome data of relevant samples were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to screen differentially expressed genes (DEGs) using the "edgeR" package. Two types of analysis-Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment-were accomplished by applying Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Search Tool for the Retrieval of Interacting Genes database (STRING) online bioinformatics tools. A protein-protein interaction (PPI) network of the identified DEGs was constructed using Cytoscape software, and hub genes were subsequently selected via the Cytohubba plug-in. The selected genes were input into Oncomine for verification. Finally, selected hub genes were analyzed by doing survival analysis to notice the relationship between survival (OS) rate and the selected genes' level of expression.ResultsThere were 1,855 DEGs found connected to ccRCC, with 1,207 upregulated genes and 648 downregulated genes. G-protein-coupled receptor signaling pathway, integral component of membrane, calcium ion binding, and cytokine-cytokine receptor interaction were among the DEGs discovered. Oncomine confirmed the top six hub genes from the PPI network (C3, CXCR3, CXCL10, CCR5, CCL4, and CCL5). A high level of expression of CXCL10, one of these hub genes, was linked to a poor prognosis in individuals with ccRCC. The results of survival analysis showed that the expression level of CXCL10 was significantly correlated with the prognosis of ccRCC patients (p < 0.05).ConclusionsFrom the analysis, the following results were drawn: CXCL10 might be a potential prognostic biomarker and novel therapeutic target for ccRCC.

Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is a type of life-threatening malignant tumor of the urinary system. IL20RB, interleukin 20 receptor subunit beta, is a cytokine receptor subunit coding gene and was initially found to play a vital role in human cancers, while its role in ccRCC still remains unclear.MethodsIn this work, we explored the prognostic value and therapeutic potential of IL20RB in ccRCC mainly by online tools. Firstly, we used UALCAN and GEPIA to explore the expression profile and prognostic value of IL20RB in various cancers; the expression profile in tumor cell lines was also analysed with CCLE and Expression Atlas. Then, we decided to focus on ccRCC for further analysis; we further demonstrated the significant correlation between expression and clinical features by GEPIA and UALCAN. In order to reveal the potential intrinsic mechanism responsible for the upregulation of IL20RB in ccRCC, we made genetic alternation analysis and methylation analysis. cBioPortal was used for genetic alternation analysis. UALCAN, MethSurv, and Xena were used for methylation analysis. To learn details of how IL20RB might function in ccRCC, we further conducted functional analysis and immune infiltration analysis. STRING and GSEA were used to do functional analysis. TIMER was used for immune infiltration analysis; KM plotter was used for survival analysis.ResultsResults show that IL20RB is upregulated in ccRCC, and low methylation may be responsible for its upregulation. Both high expression and low methylation of IL20RB predict worse survival, and both have a strong positive correlation with clinical characteristics. In addition, results indicate that there exists a crosstalk between IL20RB and neutrophils. Furthermore, the immune microenvironment could influence the prognosis predicting ability of IL20RB.ConclusionsIn conclusion, IL20RB plays an important role in ccRCC and is identified as a novel prognostic and potential therapeutic biomarker in ccRCC.

Project description:Background: Up frameshift protein 1 (UPF1) is a key component of nonsense-mediated mRNA decay (NMD) of mRNA containing premature termination codons (PTCs). The dysregulation of UPF1 has been reported in various cancers. However, the expression profile of UPF1 and its clinical significance in clear cell renal cell carcinoma (ccRCC) remains unclear. Methods: In order to detect UPF1 expression in ccRCC and its relationship with the clinical features of ccRCC, bulk RNA sequencing data were analyzed from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and ArrayExpress databases. The impact of UPF1 on the immune microenvironment of ccRCC was evaluated by multiple immune scoring algorithms to identify the cell groups that typically express UPF1 using ccRCC single cell sequencing (scRNA) data. In addition, genes co-expressed with UPF1 were identified by the weighted gene correlation network analysis (WGCNA), followed by KEGG and Reactome enrichment analysis. A series of functional experiments were performed to assess the roles of UPF1 in renal cancer cells. Finally, pan-cancer analysis of UPF1 was also performed. Results: Compared with normal tissues, the expression levels of UPF1 mRNA and protein in tumor tissues of ccRCC patients decreased significantly. In addition, patients with low expression of UPF1 had a worse prognosis. Analysis of the immune microenvironment indicated that UPF1 immune cell infiltration was closely related and the ccRCC scRNA-seq data identified that UPF1 was mainly expressed in macrophages. WGCNA analysis suggested that the functions of co-expressed genes are mainly enriched in cell proliferation and cellular processes. Experimental tests showed that knockdown of UPF1 can promote the invasion, migration and proliferation of ccRCC cells. Lastly, pan-cancer analysis revealed that UPF1 disorders were closely associated with various cancer outcomes. Conclusions: UPF1 may play a tumor suppressive role in ccRCC and modulate the immune microenvironment. The loss of UPF1 can predict the prognosis of ccRCC, making it a promising biomarker and providing a new reference for prevention and treatment.

Dataset Information

Identification of KIF23 as a Prognostic Biomarker Associated With Progression of Clear Cell Renal Cell Carcinoma.

Publications

Identification of KIF23 as a Prognostic Biomarker Associated With Progression of Clear Cell Renal Cell Carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets