Epithelial splicing regulatory protein 1 is overexpressed in breast cancer and predicts poor prognosis for breast cancer patients

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Abstract

Background: Epithelial splicing regulatory proteins (ESRPs), including ESRP1 and ESRP2, are important proteins for alternative splicing of mRNAs and are reported to promote or inhibit the progression of some tumors. However, the effects of ESRPs in breast cancer are still unknown. Material/Methods: In this study, we detected the transcriptional level and alterations of ESRP1 in patients with breast cancer based on the Oncomine, Gene Expression Profiling Interactive Analysis, Gene Expression-Based Outcome for Breast Cancer Online, and cBioPortal databases. Using immunohistochemistry and quantitative polymerase chain reaction, the expression pattern of ESRP1 in breast cancer was analyzed. Analysis of the clinicopathological characteristics and function of ESRP1 in breast cancer were actualized through the University of Alabama Cancer database and Database for Annotation, Visualization and Integrated Discovery. Using the Kaplan-Meier plotter, the prognostic values of ESRP1 in patients with breast cancer were analyzed. The Encyclopedia of RNA Interactomes database was used to predict miRNAs that regulated ESRP1. Results: We found that ESRP1 was significantly overexpressed in patients with breast cancer, compared with patients without breast cancer, and had statistically significant clinicopathological characteristics. Kaplan-Meier plotter analysis indicated that the elevated expression of ESRP1 was associated with poor prognosis in patients with breast cancer. Furthermore, hsa-miR-181c-5p was identified to be potentially involved in the regulation of ESRP1. Conclusions: These results suggest that ESRP1 is a valuable target for the precise treatment of breast cancer and a potential biomarker for the prognosis of patients with breast cancer.

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Liu, X., Wang, Q., Song, S., Feng, M., Wang, X., Li, L., … Shi, C. (2020). Epithelial splicing regulatory protein 1 is overexpressed in breast cancer and predicts poor prognosis for breast cancer patients. Medical Science Monitor, 27. https://doi.org/10.12659/MSM.931102

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