AUTHOR=Wang Ke , Li Ling , Fu Liang , Yuan Yongqiang , Dai Hongying , Zhu Tianjin , Zhou Yuxi , Yuan Fang 

TITLE=Integrated Bioinformatics Analysis the Function of RNA Binding Proteins (RBPs) and Their Prognostic Value in Breast Cancer

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2019.00140

DOI=10.3389/fphar.2019.00140

ISSN=1663-9812

ABSTRACT=Breast cancer is one of the leading causes of death among women. RNA binding proteins (RBPs) plays a vital role in the progression of many cancers. Functional investigation of RBPs may contribute to elucidate mechanism underlying tumor initiation, progression, and invasion, therefore provides novel insights into future diagnosis, treatment and prognosis. Methods: We downloaded RNA sequencing data from the cancer genome atlas (TCGA) by UCSC Xena, and identified relevant RBPs through integrated bioinformatics analysis. Then we analyzed biological processes of differentially expressed genes (DEGs) by DAVID, and established their interaction networks and performed pathway analysis through STRING database to find out potential biological effects of these RBPs. Besides, we also explored the relationship between these RBPs and the prognosis of breast cancer patients. Result: In the present study, we obtained 287 breast tumor samples and 41 normal controls. After data analysis, we identified 90 upregulated and 115 downregulated RBPs in breast cancer. GO and KEGG pathways analysis indicated that these significantly changed gene were mainly involved in RNA processing, splicing, localization and RNA silencing, DNA transposition regulation and methylation, alkylation, mitochondrial gene expression and transcription regulation. In addition, some RBPs were related to histone H3K27 methylation, estrogen response, inflammatory mediators and translation regulation. Our study also identified five RBPs associated with breast cancer prognosis. Survival analysis found that overexpression of DCAF13, EZR and MRPL13 showed worse survival but overexpression of APOBEC3C and EIF4E3 showed better survival. Conclusion: In conclusion, we identified key RBPs of breast cancer through comprehensive bioinformatics analysis. These RBPs were involved in varieties of biological and molecular pathways in breast cancer. Furthermore, we identified five RBPs as potential prognostic biomarker of breast cancer. Our study provided novel insights to understand breast cancer at molecular level.