Co-expression of key gene modules and pathways of human breast cancer cell lines.
Biosci Rep
; 39(7)2019 07 31.
Article
en En
| MEDLINE
| ID: mdl-31285391
Breast cancer (BC) is the most common leading cause of cancer-related death in women worldwide. Gene expression profiling analysis for human BCs has been studied previously. However, co-expression analysis for BC cell lines is still devoid to date. The aim of the study was to identify key pathways and hub genes that may serve as a biomarker for BC and uncover potential molecular mechanism using weighted correlation network analysis. We analyzed microarray data of BC cell lines (GSE 48213) listed in the Gene Expression Omnibus database. Gene co-expression networks were used to construct and explore the biological function in hub modules using the weighted correlation network analysis algorithm method. Meanwhile, Gene ontology and KEGG pathway analysis were performed using Cytoscape plug-in ClueGo. The network of the key module was also constructed using Cytoscape. A total of 5000 genes were selected, 28 modules of co-expressed genes were identified from the gene co-expression network, one of which was found to be significantly associated with a subtype of BC lines. Functional enrichment analysis revealed that the brown module was mainly involved in the pathway of the autophagy, spliceosome, and mitophagy, the black module was mainly enriched in the pathway of colorectal cancer and pancreatic cancer, and genes in midnightblue module played critical roles in ribosome and regulation of lipolysis in adipocytes pathway. Three hub genes CBR3, SF3B6, and RHPN1 may play an important role in the development and malignancy of the disease. The findings of the present study could improve our understanding of the molecular pathogenesis of breast cancer.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Mama
/
Regulación Neoplásica de la Expresión Génica
/
Células Epiteliales
/
Redes Reguladoras de Genes
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Biosci Rep
Año:
2019
Tipo del documento:
Article
País de afiliación:
China
Pais de publicación:
Reino Unido