Abstract
Breast cancer is one of the most common cancers. Although the present molecular classification improves the treatment effect and prognosis of breast cancer, the heterogeneity of the molecular subtype remains very complex, and the applicability and effectiveness of treatment methods are still limited leading to poorer patient prognosis than expected. Further identification of more refined molecular typing based on gene expression profile will yield better understanding of the heterogeneity, improving treatment effects and prolonging prognosis of patients. Here, we downloaded the mRNA expression profiles and corresponding clinical data of patients with breast cancer from public databases and performed typical molecular typing using PAM50 (Prediction Analysis of Microarray 50) method. Comparative analyses were performed to screen the common and specific differentially expressed genes (DEGs) between cancer and corresponding para-cancerous tissues in each breast cancer subtype. The GO and KEGG analyses of the DEGs were performed to enrich the common and specific functional progress and signaling pathway involved in breast cancer subtypes. A total of 38 key common and specific DEGs were identified and selected based on the validated results, GO/KEGG enrichments, and the priority of expression, including four common DEGs and 34 specific DEGs in different subtypes. The prognostic value of these key common and specific DEGs was further analyzed to obtain useful potential markers in clinic. Finally, the potential roles and the specific prognostic values of the common and specific DEGs were speculated and summarized in total breast cancer and different subtype breast cancer based on the results of these analyses. The findings of our study provide the basis of more refined molecular typing of breast cancer, potential new therapeutic targets and prognostic markers for different breast cancer subtypes
Highlights
Breast cancer is one of the few tumor types with good molecular classification and targeted therapies (Barry et al, 2010; Prat et al, 2015)
Using the PAM50 method, the breast cancer samples (1,091 cases) in The Cancer Genome Atlas (TCGA) database were divided into five molecular subtypes: Basal-like
A comparative analysis of gene expression was performed between cancer tissues and corresponding paracancerous tissues in all breast cancer and different subtypes’ breast cancer, and the significantly differentially expressed genes were screened out
Summary
Breast cancer is one of the few tumor types with good molecular classification and targeted therapies (Barry et al, 2010; Prat et al, 2015). PAM50 (Prediction Analysis of Microarray 50) gene signatures are a second-generation multi-gene expression assay used for quantifying the mRNA expression of 50 genes, including ER, PR, and Her2 It is currently recognized in the industry as a molecular subtype classification method for breast cancer. According to the PAM50 method, breast cancer can be divided into the following five molecular subtypes: Basal-like, LumA, LumB, Her, and Normallike (Perou et al, 2000). The PAM50 classification improves the treatment effect and prognosis of breast cancer, the problems remain. As the heterogeneity of the same molecular subtype remains very complex, the applicability and effectiveness of treatment methods are still very limited, resulting in poorer patient prognosis than expected (Sotiriou et al, 2003). The differences in the molecular characteristics and pathways among patients with Basal-like, Her, LumA, LumB, and Normal-like breast cancer subtypes are still not well understood
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
