Identification of Subtype-Specific Prognostic Biomarkers in Breast Cancer

Abstract

Breast cancer (BC) is a heterogeneous disease divided into four molecular subtypes that display different prognoses. Molecular alterations in breast cells contribute to breast carcinogenesis. However, the molecular characteristics involved in developing BC subtypes remain largely unknown. Further identification of molecular mechanisms involved in different BC subtypes might help improve treatment strategies and prognosis of patients. In the present study, two microarray datasets (GSE57297 and GSE65194) containing four BC subtypes were downloaded from the Gene Expression Omnibus (GEO) database. Comparative analyses were performed to identify specific differentially expressed genes (DEGs) for each BC subtype, as well as overlapped (core) between all subtypes. bc-GenExMiner and Kaplan-Meier plotter databases were respectively utilized to investigate the differential expression and prognostic value of DEGs. A total of 25 DEGs (12 specific and 13 core) were found to be significantly associated with prognosis. We found that a high level of C9orf116 predicted better OS in the Luminal A subtype. Also, increased transcription levels of FAM13A and RASIP1 were associated with shorter OS in the Luminal B subtype. High mRNA expression of PDE7A, and COTL1 conferred longer OS, while elevated expression of TM4SF1 and AREG predicted shorter OS in the TNBC subtype. Increased mRNA levels of GSR, and DAPK2 conferred better OS in the HER2 subtype; however, increased expression levels of HOTAIR, PLEKHG4, and POU6F1 predicted poor OS. For the core DEGs, increased expression of IFI6 and UBE2S predicted shorter OS. Meanwhile, increased mRNA levels of AK5, C2orf40, CNN1, HOXA5, NTRK2, PAMR1, PROS1, SCARA5, SDPR, TGFBR3, and TSHZ2 conferred better OS. In conclusion, this study strictly identified specific genes that may help to select precision prognostic biomarkers in different BC subtypes.