Identification of key pathways and drug repurposing for anaplastic thyroid carcinoma by integrated bioinformatics analysis.
- Author:
Zongfu PAN
1
;
Qilu FANG
1
;
Yiwen ZHANG
1
;
Li LI
2
;
Ping HUANG
1
Author Information
- Publication Type:Journal Article
- MeSH: Computational Biology; Drug Repositioning; Gene Expression Profiling; Humans; Phosphatidylinositol 3-Kinases; Protein Interaction Maps; Thyroid Carcinoma, Anaplastic; Thyroid Neoplasms
- From: Journal of Zhejiang University. Medical sciences 2018;47(2):187-193
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo identify hub genes and key pathways associated with anaplastic thyroid carcinoma (ATC), and to explore possible intervention strategy.
METHODSThe differentially expressed genes (DEGs) in ATC were identified by Gene Expression Omnibus (GEO) combined with using R language; the pathway enrichment of DEGs were performed by using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The protein-protein interaction (PPI) network of DEGs was constructed by STRING database and visualized by Cytoscape. Furthermore, the hub genes and key nodes were calculated by MCODE. Finally, the drug repurposing was performed by L1000CDS.
RESULTSA total of 2087 DEGs were identified. The DEGs were clustered based on functions and pathways with significant enrichment analysis, among which PI3K-Akt signaling pathway, p53 signaling pathway, inflammatory response, extracellular matrix organization were significantly upregulated. The PPI network was constructed and the most significant three modules and nine genes were filtered. Twenty-two potential compounds were repurposed for ATC treatment.
CONCLUSIONSUsing integrated bioinformatics analysis, we have identified hub genes and key pathways in ATC, and provide novel strategy for the treatment of ATC.
