Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer.
Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.
a Department of Breast Surgery , Yantaishan Hospital , Yantai , China and.
Hongyan
H
Zang
b Department of Human Anatomy , School of Basic Medicine, Shandong University of Traditional Chinese Medicine , Jinan , China.
Ning
N
Li
b Department of Human Anatomy , School of Basic Medicine, Shandong University of Traditional Chinese Medicine , Jinan , China.
Yuling
Y
Pan
a Department of Breast Surgery , Yantaishan Hospital , Yantai , China and.
Jingguang
J
Hao
D000328:Adult; D001940:Breast / Q000378:metabolism / Q000601:surgery; D001943:Breast Neoplasms / Q000378:metabolism* / Q000601:surgery; D018797:Cell Cycle Proteins / Q000235:genetics / Q000378:metabolism; D066289:Data Curation; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D006801:Humans; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000235:genetics / Q000378:metabolism*; D060888:Real-Time Polymerase Chain Reaction; D020133:Reverse Transcriptase Polymerase Chain Reaction; D051720:Upstream Stimulatory Factors / Q000378:metabolism*
D018797:Cell Cycle Proteins; D009363:Neoplasm Proteins; D051720:Upstream Stimulatory Factors
Breast cancer; differentially expressed genes; gene expression data; transcription factor