Literature DB >> 29534586

Identification of biomarkers and potential molecular mechanisms of clear cell renal cell carcinoma.

F Wu, S Wu, X Gou.   

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer in adults. The aim of this study is to identify the biomarkers and potential molecular mechanisms of ccRCC. Three gene expression profiles and two miRNA expression profiles were downloaded from GEO database. A total of 330 up-regulated differentially expressed genes (DEGs), 545 down-regulated DEGs, 26 up-regulated differentially expressed miRNAs (DEMs) and 11 down-regulated DEMs were identified by GEO2R. The gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by KOBAS software. The results showed that GO terms of the up-regulated DEGs were mostly enriched in response to stimulus at BP level, cell periphery at CC level and binding at MF level, while the GO terms of down-regulated DEGs were enriched in single-organism process at BP level, extracellular exosome at CC level and catalytic activity at MF level. As for KEGG pathways, HIF-1 signaling pathway, focal adhesion, PI3K-Akt signaling pathway and metabolic pathways were significantly enriched. Then, protein-protein interaction (PPI) network and miRNA-gene network were constructed and analyzed by Cytoscape. A total of eight DEGs were identified as biomarkers, including VEGFA, PPARA, CCND1, FLT1, CXCL12, FN1, DCN and ERBB4. Expression validation and survival analysis were performed by GEPIA and OncoLnc, respectively. Four biomarkers were verified by quantitative real-time PCR (qPCR) in 786-O cell line and HK-2 cell line. All four genes had the same expression trend as predicted. Our study provides a series of biomarkers and molecular mechanisms for the deeper research of ccRCC.

Entities:  

Keywords:  clear cell renal cell carcinoma; differentially expressed gene; miRNA survival analysis.; protein-protein interaction network

Mesh:

Substances:

Year:  2018        PMID: 29534586     DOI: 10.4149/neo_2018_170511N342

Source DB:  PubMed          Journal:  Neoplasma        ISSN: 0028-2685            Impact factor:   2.575


  4 in total

1.  Integrated bioinformatics analysis for the identification of potential key genes affecting the pathogenesis of clear cell renal cell carcinoma.

Authors:  Hao Cui; Lei Xu; Zhi Li; Ke-Zuo Hou; Xiao-Fang Che; Bo-Fang Liu; Yun-Peng Liu; Xiu-Juan Qu
Journal:  Oncol Lett       Date:  2020-06-05       Impact factor: 2.967

2.  Identification of significant genes with prognostic influence in clear cell renal cell carcinoma via bioinformatics analysis.

Authors:  Fangyuan Zhang; Pengjie Wu; Yalong Wang; Mengxian Zhang; Xiaodan Wang; Ting Wang; Shengwen Li; Dong Wei
Journal:  Transl Androl Urol       Date:  2020-04

3.  Mitochondrial Ndufa4l2 Enhances Deposition of Lipids and Expression of Ca9 in the TRACK Model of Early Clear Cell Renal Cell Carcinoma.

Authors:  Kristian B Laursen; Qiuying Chen; Francesca Khani; Nabeel Attarwala; Steve S Gross; Lukas Dow; David M Nanus; Lorraine J Gudas
Journal:  Front Oncol       Date:  2021-12-14       Impact factor: 6.244

Review 4.  The Role of CXCL12 in Kidney Diseases: A Friend or Foe?

Authors:  Anni Song; Anni Jiang; Wei Xiong; Chun Zhang
Journal:  Kidney Dis (Basel)       Date:  2021-04-06
  4 in total

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