Key genes associated with prognosis and metastasis of clear cell renal cell carcinoma

Background Clear cell renal cell carcinoma (ccRCC) is a tumor that frequently shows the hematogenous pathway and tends to be resistant to radiotherapy and chemotherapy. However, the exact mechanism of ccRCC metastasis remains unknown. Methods Differentially expressed genes (DEGs) of three gene expression profiles (GSE85258, GSE105288 and GSE22541) downloaded from the Gene Expression Omnibus (GEO) database were analyzed by GEO2R analysis, and co-expressed DEGs among the datasets were identified using a Venn drawing tool. The co-expressed DEGs were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and hub genes were determined based on the protein-protein interaction network established by STRING. After survival analysis performed on UALCAN website, possible key genes were selected and verified in ccRCC cell lines and ccRCC tissues (n = 44). Statistical analysis was conducted using GraphPad Prism (Version 8.1.1). Results A total of 104 co-expressed DEGs were identified in the three datasets. Pathway analysis revealed that these genes were enriched in the extracellular matrix (ECM)–receptor interaction, protein digestion and absorption and focal adhesion. Survival analysis on 17 hub genes revealed that four key genes with a significant impact on survival: procollagen C-endopeptidase enhancer (PCOLCE), prolyl 4-hydroxylase subunit beta (P4HB), collagen type VI alpha 2 (COL6A2) and collagen type VI alpha 3 (COL6A3). Patients with higher expression of these key genes had worse survival than those with lower expression. In vitro experiments revealed that the mRNA expression levels of PCOLCE, P4HB and COL6A2 were three times higher and that of COL6A3 mRNA was 16 times higher in the metastatic ccRCC cell line Caki-1 than the corresponding primary cell line Caki-2. Immunohistochemistry revealed higher expression of the proteins encoded by these four genes in metastatic ccRCC compared with tumors from the corresponding primary sites, with statistical significance. Conclusion PCOLCE, P4HB, COL6A2 and COL6A3 are upregulated in metastatic ccRCC and might be related to poor prognosis and distant metastases.

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Key Genes Associated With Prognosis and Metastasis of Clear Cell Renal Cell Carcinoma

10.21203/rs.3.rs-202214/v1 ◽

2021 ◽

Author(s):

Tingting Zhong ◽

Zeying Jiang ◽

Xiangdong Wang ◽

Honglei Wang ◽

Meiyi Song ◽

...

Keyword(s):

Gene Expression ◽

Renal Cell Carcinoma ◽

Survival Analysis ◽

Collagen Type ◽

Clear Cell ◽

Hub Genes ◽

Cell Renal Cell Carcinoma ◽

Collagen Type Vi ◽

Key Genes ◽

Ccrcc Cell

Abstract Background: Clear cell renal cell carcinoma (ccRCC) is a tumor with frequent hematogenous metastasis and is usually resistant with radiotherapy and chemotherapy. The mechanism of ccRCC metastasis still needs to be illustrated.Material and methods: The differentially expressed genes (DEGs) of three gene expression profiles (GSE85258, GSE105288 and GSE22541) downloaded from Gene Expression Omnibus (GEO) database were analyzed by GEO2R analysis, and co-expressed DEGs among them were sorted out by the online Venn drawing tool. The co-expressed DEGs were then investigated using Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and hub genes would be screened out based on protein-protein interaction network (PPI) established by STRING. After survival analysis performed on UALCAN website, possible key genes would be selected and then verified in ccRCC cell lines and ccRCC tissues (n=40). Statistical analysis of the above results was conducted using GraphPad Prism (Version 8.1.1).Results: 104 co-expressed DEGs were sorted from the three profiles. KEGG pathways revealed that these genes were enriched in the extracellular matrix (ECM)-receptor interaction, focal adhesion and PI3K-Akt signaling pathway. Survival analysis showed that among 17 hub genes, patients with higher expression of Procollagen C-Endopeptidase Enhancer (PCOLCE), Prolyl 4-Hydroxylase Subunit Beta (P4HB), Collagen Type VI Alpha 2 (COL6A2), and Collagen Type VI Alpha 3 (COL6A3) had a worse survival than those with lower expression. In vitro, the mRNA expression level of PCOLCE, P4HB and COL6A2 were 3 times, and COL6A3 16 times higher in metastatic ccRCC cell line Caki-1 than in corresponding primary cell line Caki-2. Immunohistochemistry results also showed higher expression of these 4 genes in metastatic ccRCC with statistical significance.Conclusion: PCOLCE, P4HB, COL6A2 and COL6A3 are upregulated in metastatic ccRCC and might be related to poor prognosis and distant metastases.

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Screening and identification of novel promoter signatures in clear cell renal cell carcinoma metastasis.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.6_suppl.737 ◽

2020 ◽

Vol 38 (6_suppl) ◽

pp. 737-737

Author(s):

Yuan-Yuan Qu ◽

Xi Tian ◽

Wenhao Xu ◽

Aihemutaijiang Anwaier ◽

Dingwei Ye ◽

...

Keyword(s):

Gene Expression ◽

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Cox Regression ◽

Clear Cell ◽

Expression Profiles ◽

Functional Enrichment ◽

Hub Genes ◽

Cell Renal Cell Carcinoma

737 Background: Clear cell renal cell carcinoma (ccRCC) patient usually face aggressive progression when metastasis occurs. Therefore, in-depth investigation is needed to elucidate underlying mechanisms behind the metastasis of ccRCC to promote therapeutic benefits.This study aims to explore and investigate prognostic gene expression profiles based on multi-cohorts. Methods: Three microarray datasets were obtained from the Gene Expression Omnibus (GEO) database to screen and identify differentially expressed genes (DEGs) according to normalization annotation information. A total of 112 DEGs with functional enrichment were identified as candidate prognostic biomarkers. A protein–protein interaction network (PPI) of DEGs was developed, and the modules were analyzed using STRING and Cytoscape. Results: LASSO Cox regression suggested 31 significant involved genes, and 10 hub genes were identified as independent oncogenes in ccRCC patients. Distinct integrated scores of the hub genes mRNA expression showed statistical significance in predicting disease-free survival (DFS; p<0.001) and overall survival (OS; p<0.001) in TCGA and real-world cohorts. Meanwhile, ROC curves were constructed to validate specificity and sensitivity of the Cox regression penal to predict prognosis. The AUC index for the integrated genes scores was 0.758 for OS and 0.772 for DFS. Conclusions: In conclusion,the present study identifies DEGs and hub genes that may be involved in earlier recurrence and poor prognosis of ccRCC. The expression levels of ADAMTS9, C1S, DPYSL3, H2AFX, MINA, PLOD2, RUNX1, SLC19A1, TPX2 and TRIB3 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ccRCC.

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Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-Analysis

BioMed Research International ◽

10.1155/2019/6480865 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Sheng Wang ◽

Zhi-hong Yu ◽

Ke-qun Chai

Keyword(s):

Renal Cell Carcinoma ◽

Survival Analysis ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Meta Analysis ◽

Ppi Network ◽

Hub Genes ◽

Cell Renal Cell Carcinoma ◽

Kegg Analysis

Clear cell renal cell carcinoma (ccRCC) was the most aggressive histological type of renal cell carcinoma (RCC) and accounted for 70–80% of cases of all RCC. The aim of this study was to identify the potential biomarker in ccRCC and explore their underlying mechanisms. Four profile datasets were downloaded from the GEO database to identify DEGs. GO and KEGG analysis of DEGs were performed by DAVID. A protein–protein interaction (PPI) network was constructed to predict hub genes. The hub gene expression within ccRCC across multiple datasets and the overall survival analysis were investigated utilizing the Oncomine Platform and UALCAN dataset, separately. A meta-analysis was performed to explore the relationship between the hub genes: EGFR and ccRCC. 127 DEGs (55 upregulated genes and 72 downregulated genes) were identified from four profile datasets. Integrating the result from PPI network, Oncomine Platform, and survival analysis, EGFR, FLT1, and EDN1 were screened as key factors in the prognosis of ccRCC. GO and KEGG analysis revealed that 127 DEGs were mainly enriched in 21 terms and 4 pathways. The meta-analysis showed that there was a significant difference of EGFR expression between ccRCC tissues and normal tissues, and the expression of EGFR in patients with metastasis was higher. This study identified 3 importance genes (EGFR, FLT1, and EDN1) in ccRCC, and EGFR may be a potential prognostic biomarker and novel therapeutic target for ccRCC, especially patients with metastasis.

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Bioinformatics analysis of C3 and CXCR4 demonstrates their potential as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC)

BMC Cancer ◽

10.1186/s12885-021-08525-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jing Quan ◽

Yuchen Bai ◽

Yunbei Yang ◽

Er Lei Han ◽

Hong Bai ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Therapeutic Targets ◽

Disease Free Survival ◽

Prognostic Biomarkers ◽

Hub Genes ◽

Cell Renal Cell Carcinoma ◽

Upregulated Genes

Abstract Background The molecular prognostic biomarkers of clear cell renal cell carcinoma (ccRCC) are still unknown. We aimed at researching the candidate biomarkers and potential therapeutic targets of ccRCC. Methods Three ccRCC expression microarray datasets (include GSE14762, GSE66270 and GSE53757) were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) between ccRCC and normal tissues were explored. The potential functions of identified DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). And then the protein - protein interaction network (PPI) was established to screen the hub genes. After that, the expressions of hub genes were identified by the oncomine database. The hub genes’ prognostic values of patients with ccRCC were analyzed by GEPIA database. Results A total of 137 DEGs were identified by utilizing the limma package and RRA method, including 63 upregulated genes and 74 downregulated genes. It is found that 137 DEGs were mainly enriched in 82 functional terms and 24 pathways in accordance with the research results. Thirteen highest-scoring genes were screened as hub genes (include 10 upregulated genes and 3 downregulated candidate genes) by utilizing the PPI network and module analysis. Through integrating the oncoming database and GEPIA database, the author found that C3 and CXCR4 are not only overexpressed in ccRCC, but also associated with the prognosis of ccRCC. Further results could reveal that patients with high C3 expression had a poor overall survival (OS), while patients with high CTSS and TLR3 expressions had a good OS; patients with high C3 and CXCR4 expressions had a poor disease-free survival (DFS), while ccRCC patients with high TLR3 expression had a good DFS. Conclusion These findings suggested that C3 and CXCR4 were the candidate biomarkers and potential therapeutic targets of ccRCC patients.

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PD57-01 WHOLE-TRANSCRIPTOME SEQUENCING IDENTIFIED GENE EXPRESSION SIGNATURES ASSOCIATED WITH AGGRESSIVE CLEAR CELL RENAL CELL CARCINOMA

The Journal of Urology ◽

10.1016/j.juro.2018.02.2645 ◽

2018 ◽

Vol 199 (4S) ◽

Author(s):

Ken Batai ◽

Elliot Imler ◽

Michael Phung ◽

Robert Bell ◽

Aye Lwin ◽

...

Keyword(s):

Gene Expression ◽

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Transcriptome Sequencing ◽

Clear Cell ◽

Cell Renal Cell Carcinoma ◽

Gene Expression Signatures ◽

Whole Transcriptome Sequencing ◽

Whole Transcriptome

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Identification of potential key genes and key pathways related to clear cell renal cell carcinoma through bioinformatics analysis

Acta Biochimica et Biophysica Sinica ◽

10.1093/abbs/gmaa068 ◽

2020 ◽

Vol 52 (8) ◽

pp. 853-863

Author(s):

Wenxin Zhai ◽

Haijiao Lu ◽

Shenghua Dong ◽

Jing Fang ◽

Zhuang Yu

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Phosphoenolpyruvate Carboxykinase ◽

Bioinformatics Analysis ◽

Clear Cell ◽

Interaction Network ◽

Polymerase Chain Reaction Analysis ◽

Cell Renal Cell Carcinoma ◽

Key Genes

Abstract Clear cell renal cell carcinoma (ccRCC) is a common malignancy of the genitourinary system and is associated with high mortality rates. However, the molecular mechanism of ccRCC pathogenesis is still unclear, which translates to few effective diagnostic and prognostic biomarkers. In this study, we conducted a bioinformatics analysis on three Gene Expression Omnibus datasets and identified 437 differentially expressed genes (DEGs) related to ccRCC development and prognosis, of which 311 and 126 genes are respectively down-regulated and up-regulated. The protein–protein interaction network of these DEGs consists of 395 nodes and 1872 interactions and 2 prominent modules. The Staphylococcus aureus infection and complement and coagulation cascades are significantly enriched in module 1 and are likely involved in ccRCC progression. Forty-two hub genes were screened, of which von Willebrand factor, TIMP metallopeptidase inhibitor 1, plasminogen, formimidoyltransferase cyclodeaminase, solute carrier family 34 member 1, hydroxyacid oxidase 2, alanine-glyoxylate aminotransferase 2, phosphoenolpyruvate carboxykinase 1, and 3-hydroxy-3-methylglutaryl-CoA synthase 2 are possibly related to the prognosis of ccRCC. The differential expression of all nine genes was confirmed by quantitative real-time polymerase chain reaction analysis of the ccRCC and normal renal tissues. These key genes are potential biomarkers for the diagnosis and prognosis of ccRCC and warrant further investigation.

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