Bioinformatic identification of chemoresistance-associated microRNAs in breast cancer based on microarray data

Wang,Ya-Wen; Zhang,Weiguo; Ma,Rong

doi:10.3892/or.2018.6205

Bioinformatic identification of chemoresistance-associated microRNAs in breast cancer based on microarray data

Authors:
- Ya-Wen Wang
- Weiguo Zhang
- Rong Ma
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Affiliations: Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, Shandong 250012, P.R. China
Published online on: January 10, 2018 https://doi.org/10.3892/or.2018.6205
Pages: 1003-1010
Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Breast cancer is the most commonly diagnosed cancer among females, and chemoresistance constitutes a major clinical obstacle to the treatment of this disease. MicroRNAs (miRNAs) are related to human cancer development, progression and drug resistance. To identify breast cancer chemoresistance-associated miRNAs, miRNA microarray dataset GSE71142, including five chemoresistant breast cancer tissues and five chemosensitive tissues, was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DE-miRNAs) were obtained by t-test and the potential target genes were predicted by miRWalk2.0. Functional and pathway enrichment analysis by WebGestalt was performed for the potential target genes of DE-miRNAs. Protein-protein interaction (PPI) network was established by STRING database and visualized by Cytoscape software. Enriched transcription factors by the target genes were obtained from FunRich. Breast cancer-associated miRNA‑gene pairs were identified from miRWalk2.0. A total of 22 DE-miRNAs were screened out, including 10 upregulated miRNAs (e.g., miR-196a-5p) and 12 downregulated miRNAs (e.g., miR-4472) in the chemoresistant breast cancer tissues, compared with chemosensitive tissues. In total 1,278 target genes were screened out, and they were involved in breast cancer-related pathways such as pathways in cancer, signaling pathways regulating pluripotency of stem cells, endocrine resistance, breast cancer, mTOR signaling and Hippo signaling pathway. NOTCH1 and MAPK14 were identified as hub genes in the PPI network. EGR1 and SP1 were the most enriched transcription factors by the target genes. Several breast cancer-associated miRNA-gene pairs including miR-214-TP53 and miR-16-PPM1D were identified. The current bioinformatics study of miRNAs based on microarray may offer a new understanding into the mechanisms of breast cancer chemoresistance, and may identify novel miRNA therapeutic targets.

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