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The Role of Long Non-coding RNA Prostate Cancer-Associated Transcript 1 in Prostate Cancer.

Authors :
Yang Y
Yang W
Jin L
Source :
Journal of computational biology : a journal of computational molecular cell biology [J Comput Biol] 2019 Sep; Vol. 26 (9), pp. 975-984. Date of Electronic Publication: 2019 May 15.
Publication Year :
2019

Abstract

This study aimed to investigate the role of prostate cancer associated transcript 1 (PCAT1) underlying the molecular mechanisms of prostate cancer. Using GSE29886 data set downloaded from Gene Expression Omnibus database, we screened the differentially expressed genes (DEGs) in PCAT1-siRNA interfering (PCAT1-siRNA) LNCaP cells compared with control-siRNA cells. Transcription factor (TF) and tumor-associated genes database were used to obtain oncogenes and tumor suppressor genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to investigate the function and pathways of DEGs. Subnetwork was further analyzed using BioNet. A total of 93 DEGs were identified. KEGG analysis showed downregulated TF genes (ID1 and ID3) were enriched in transforming growth factor- β pathway, whereas upregulated genes were involved in pathways associated with immune system, environmental sensing, and metabolism. GO analysis showed that downregulated genes were primarily enriched in cell cycle-related biological functions and upregulated DEGs were related to immune response, exogenous genetic material response, and viral response. Centromere protein F (CENPF) was identified as the central node of the regulatory subnetwork. In the PCAT1 knockdown LNCaP cells, the CENPF, ID1, and ID3 were obviously decreased based on the RT-PCR (quantitative real-time reverse transcription PCR) analysis. PCAT1 may be involved in cell cycle and proliferation of prostate cancers by mediating the expression of CENPF , ID1 , and ID3 .

Details

Language :
English
ISSN :
1557-8666
Volume :
26
Issue :
9
Database :
MEDLINE
Journal :
Journal of computational biology : a journal of computational molecular cell biology
Publication Type :
Academic Journal
Accession number :
31090454
Full Text :
https://doi.org/10.1089/cmb.2018.0240