Identification of ribosomal protein family in triple-negative breast cancer by bioinformatics analysis.

Triple-negative breast cancer (TNBC) accounts for ~20% of all breast cancer cases. The management of TNBC represents a challenge due to its worse prognosis, heterogeneity and lack of targeted therapy. Moreover, its mechanisms are not fully clear. The aim of the study is to identify crucial genes between TNBC and non-TNBC for underlying targets for diagnostic and therapeutic methods of TNBC. The differentially expressed genes (DEGs) between TNBC and non-TNBC were selected from the Gene Expression Omnibus (GEO) database after the integrated analysis of two datasets (GSE65194 and GSE76124). Then Gene ontology (GO) and KEGG analysis were performed by DAVID database, protein-protein interaction (PPI) of DEGs was constructed by STRING database. Furthermore, centrality analysis and module analysis were carried out by Cytoscape to analysis the TNBC-related PPI. Subsequently, overall survival analysis was performed by GEPIA. Finally, the expressions of these key genes in TNBC and non-TNBC tissues were tested by qRT-PCR. The results showed that 955 DEGs were obtained, which were mainly enriched in ribosome, ribosomal subunit, and so on. Moreover, 19 candidate genes were focused on by centrality analysis and module analysis. Furthermore, we found the low expressions of RPS9, RPS14, RPS27, RPL11 and RPL14 were related to a poor overall survival (OS) in breast cancer patients. Additionally, qRT-PCR results suggested that these five genes were notably down-regulated in TNBC tissues. In summary, the present study suggests that ribosomal proteins are related to TNBC, and they may play an important role in the diagnosis, treatment and prognosis of TNBC.