Mining Prognostic Significance of MEG3 in Human Breast Cancer Using Bioinformatics Analysis

Abstract

Background/aims: Maternally expressed gene 3 (MEG3) is an imprinted gene with maternal expression, which may function as a tumor suppressor by inhibiting angiogenesis. To identify the prognostic value of MEG3 in breast cancer, systematic analysis was performed in this study.

Methods: To evaluate gene alteration during breast carcinogenesis, we explored MEG3 expression using the Serial Analysis of Gene Expression Genie suite and Oncomine analysis. The prognostic roles of MEG3 in breast cancer were investigated using the PrognoScan database. The heat map and methylation status of MEG3 were determined using the UCSC Genome Browser.

Results: We found that MEG3 was more frequently downregulated in breast cancer than in normal tissues and this correlated with prognosis. However, estrogen receptor and progesterone receptor status were found to be positively correlated with MEG3 expression. Conversely, basal-like status, triple-negative breast cancer status, and Scarff Bloom & Richardson grade criterion were negatively correlated with MEG3 expression. Following data mining in multiple big data databases, we confirmed a positive correlation between MEG3 and heparan sulfate proteoglycan 2 (HSPG2) expression in breast cancer tissues.

Conclusion: MEG3 could be adopted as a marker to predict the prognosis of breast cancer with HSPG2. However, large-scale and comprehensive research is needed to clarify our results.

Keywords: Breast carcinoma; Long non-coding RNAs; MEG3; Prognosis.