The Role of Long Non-coding RNA Prostate Cancer-Associated Transcript 1 in Prostate Cancer.
J Comput Biol
; 26(9): 975-984, 2019 09.
Article
en En
| MEDLINE
| ID: mdl-31090454
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-ß 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.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Próstata
/
Regulación Neoplásica de la Expresión Génica
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Redes Reguladoras de Genes
/
ARN Largo no Codificante
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
/
Male
Idioma:
En
Revista:
J Comput Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
/
INFORMATICA MEDICA
Año:
2019
Tipo del documento:
Article
País de afiliación:
China