Cargando…

Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis

BACKGROUND: Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer (BC) and links to poor outcomes. As the molecular mechanism of BLBC has not yet been completely discovered, identification of key pathways and hub genes of this disease is an important way for providing new i...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Kaidi, Gao, Jian, Luo, Mao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388944/
https://www.ncbi.nlm.nih.gov/pubmed/30863098
http://dx.doi.org/10.2147/OTT.S158619
_version_ 1783397848965971968
author Yang, Kaidi
Gao, Jian
Luo, Mao
author_facet Yang, Kaidi
Gao, Jian
Luo, Mao
author_sort Yang, Kaidi
collection PubMed
description BACKGROUND: Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer (BC) and links to poor outcomes. As the molecular mechanism of BLBC has not yet been completely discovered, identification of key pathways and hub genes of this disease is an important way for providing new insights into exploring the mechanisms of BLBC initiation and progression. OBJECTIVE: The aim of this study was to identify potential gene signatures of the development and progression of the BLBC via bioinformatics analysis. METHODS AND RESULTS: The differential expressed genes (DEGs) including 40 up-regulated and 21 down-regulated DEGs were identified between GSE25066 and GSE21422 microarrays, and these DEGs were significantly enriched in the terms related to oncogenic or suppressive roles in BLBC progression. In addition, KEGG pathway and GSEA (Gene Set Enrichment Analysis) enrichment analyses were performed for DEGs between the basal type and non-basal-type breast cancer from GSE25066 microarray. These DEGs were enriched in pathways such as cell cycle, cytokine-cytokine receptor interaction, chemokine signaling pathway, central carbon metabolism signaling and TNF signaling pathway. Moreover, the protein-protein interaction (PPI) network was constructed with those 61 DEGs using the Cytoscape software, and the biological significance of putative modules was established using MCODE. The module 1 was found to be closely related with a term of mitosis regulation and enriched in cell cycle pathway, and thus confirmed the pathological characteristic of BLBC with a high mitotic index. Furthermore, prediction values of the top 10 hub genes such as CCNB2, BUB1, NDC80, CENPE, KIF2C, TOP2A, MELK, TPX2, CKS2 and KIF20A were validated using Oncomine and Kaplan-Meier plotter. CONCLUSION: Our results suggest the intriguing possibility that the hub genes and modules in the PPI network contributed to in-depth knowledge about the molecular mechanism of BLBC, paving a way for more accurate discovery of potential treatment targets for BLBC patients.
format Online
Article
Text
id pubmed-6388944
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Dove Medical Press
record_format MEDLINE/PubMed
spelling pubmed-63889442019-03-12 Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis Yang, Kaidi Gao, Jian Luo, Mao Onco Targets Ther Original Research BACKGROUND: Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer (BC) and links to poor outcomes. As the molecular mechanism of BLBC has not yet been completely discovered, identification of key pathways and hub genes of this disease is an important way for providing new insights into exploring the mechanisms of BLBC initiation and progression. OBJECTIVE: The aim of this study was to identify potential gene signatures of the development and progression of the BLBC via bioinformatics analysis. METHODS AND RESULTS: The differential expressed genes (DEGs) including 40 up-regulated and 21 down-regulated DEGs were identified between GSE25066 and GSE21422 microarrays, and these DEGs were significantly enriched in the terms related to oncogenic or suppressive roles in BLBC progression. In addition, KEGG pathway and GSEA (Gene Set Enrichment Analysis) enrichment analyses were performed for DEGs between the basal type and non-basal-type breast cancer from GSE25066 microarray. These DEGs were enriched in pathways such as cell cycle, cytokine-cytokine receptor interaction, chemokine signaling pathway, central carbon metabolism signaling and TNF signaling pathway. Moreover, the protein-protein interaction (PPI) network was constructed with those 61 DEGs using the Cytoscape software, and the biological significance of putative modules was established using MCODE. The module 1 was found to be closely related with a term of mitosis regulation and enriched in cell cycle pathway, and thus confirmed the pathological characteristic of BLBC with a high mitotic index. Furthermore, prediction values of the top 10 hub genes such as CCNB2, BUB1, NDC80, CENPE, KIF2C, TOP2A, MELK, TPX2, CKS2 and KIF20A were validated using Oncomine and Kaplan-Meier plotter. CONCLUSION: Our results suggest the intriguing possibility that the hub genes and modules in the PPI network contributed to in-depth knowledge about the molecular mechanism of BLBC, paving a way for more accurate discovery of potential treatment targets for BLBC patients. Dove Medical Press 2019-02-18 /pmc/articles/PMC6388944/ /pubmed/30863098 http://dx.doi.org/10.2147/OTT.S158619 Text en © 2019 Yang et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed
spellingShingle Original Research
Yang, Kaidi
Gao, Jian
Luo, Mao
Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis
title Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis
title_full Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis
title_fullStr Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis
title_full_unstemmed Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis
title_short Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis
title_sort identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388944/
https://www.ncbi.nlm.nih.gov/pubmed/30863098
http://dx.doi.org/10.2147/OTT.S158619
work_keys_str_mv AT yangkaidi identificationofkeypathwaysandhubgenesinbasallikebreastcancerusingbioinformaticsanalysis
AT gaojian identificationofkeypathwaysandhubgenesinbasallikebreastcancerusingbioinformaticsanalysis
AT luomao identificationofkeypathwaysandhubgenesinbasallikebreastcancerusingbioinformaticsanalysis