Identification of cell division cycle 20 as a candidate biomarker and potential therapeutic target in bladder cancer using bioinformatics analysis.

Bioscience Reports
Peilin ShenMingen Lin

Abstract

As bladder cancer (BC) is very heterogeneous and complicated in the genetic level, exploring genes to serve as biomarkers and therapeutic targets is practical. We searched Gene Expression Omnibus (GEO) and downloaded the eligible microarray datasets. After intersection analysis for identified differentially expressed genes (DEGs) of included datasets, overlapped DEGs were identified and subsequently analyzed with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Protein-Protein Interaction (PPI) and hub genes identification. Hub genes were further analyzed with mRNA expression comparation in Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) database, proteomics-based validation in The Human Protein Atlas (THPA) and survival analysis in GEO and Oncolnc database. We analyzed five eligible GEO datasets and identified 76 overlapped DEGs mapped into PPI network with 459 edges which were mainly enriched in cell cycle pathway and related terms in GO and KEGG analysis. Among five identified hub genes, which are Cyclin-Dependent Kinase 1 (CDK1), Ubiquitin-Conjugating Enzyme E2 C (UBE2C), Cell Division Cycle 20 (CDC20), Microtubule Nucleation Factor (TPX2) and Cell Division Cycle Associated 8 (CDCA8); ...Continue Reading

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Datasets Mentioned

BETA
GSE65635
GSE121711
GSE31189
GSE52519

Software Mentioned

R language
SPSS
clusterProfiler
Oncolnc
Search Tool for the Retrieval
Cytoscape
R
Linear Models for Microarray ( LIMMA )
Venn diagram
ggplot2

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