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Identification of genes and pathways associated with MDR in MCF-7/MDR breast cancer cells by RNA-seq analysis

  • Authors:
    • Minlan Yang
    • Hairi Li
    • Yanru Li
    • Yang Ruan
    • Chengshi Quan

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  • Published online on: March 7, 2018     https://doi.org/10.3892/mmr.2018.8704
  • Pages: 6211-6226

  • Copyright: © Yang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Multidrug resistance (MDR) is a major problem in the treatment of breast cancer. In the present study, next-generation sequencing technology was employed to identify differentially expressed genes in MCF‑7/MDR cells and MCF‑7 cells, and aimed to investigate the underlying molecular mechanisms of MDR in breast cancer. Differentially expressed genes between MCF‑7/MDR and MCF‑7 cells were selected using software; a total of 2085 genes were screened as differentially expressed in MCF‑7/MDR cells. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. Finally, a protein‑protein interaction network was constructed and the hub genes in the network were analyzed using the STRING database. GO annotation demonstrated that the differentially expressed genes were enriched in various biological processes, including ‘regulation of cell differentiation’, ‘cell development’, ‘neuron development’, ‘movement of cell or subcellular component’ and ‘cell morphogenesis involved in neuron differentiation’. Cellular component analysis by GO revealed that differentially expressed genes were enriched in ‘plasma membrane region’ and ‘extracellular matrix’ terms. Furthermore, KEGG analysis demonstrated that the target genes were enriched in various pathways, including ‘cell adhesion molecules (CAMs)’, ‘calcium signaling pathway’, ‘tight junction’, ‘Wnt signaling pathway’ and ‘pathways in cancer’ terms. A protein‑protein interaction network demonstrated that certain hub genes, including cyclin D1, nitric oxide synthase 3 (NOS3), NOTCH3, brain‑derived neurotrophic factor (BDNF), paired box 6, neuropeptide Y, phospholipase C β (PLCB) 4, PLCB2 and actin α cardiac muscle 1, may be associated with MDR in breast cancer. Subsequently, RT‑qPCR confirmed that the expression of these 9 hub genes was higher in MCF‑7/MDR cells compared with MCF‑7 cells, consistent with the RNA‑sequencing analysis. Additionally, a Cell Counting Kit‑8 assay demonstrated that specific inhibitors of NOS3 and BDNF/neurotrophic receptor tyrosine kinase, type 2 signaling reduced the IC50 of MCF‑7/MDR cells in response to various anticancer drugs, including adriamycin, cisplatin and 5‑fluorouracil. The results of the present study provide novel insights into the mechanism underlying MDR in MCF‑7 cells and may identify novel targets for the treatment of breast cancer.
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May-2018
Volume 17 Issue 5

Print ISSN: 1791-2997
Online ISSN:1791-3004

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  • Journal Metrics
  • Impact Factor: 3.4
  • Ranked Medicine Research and Experimental
    (total number of cites)
  • CiteScore: 7.6
  • CiteScore Rank: Q1: #82/347 Biochemistry, Genetics and Molecular Biology
  • Source Normalized Impact per Paper (SNIP): 0.647
  • SCImago Journal Rank (SJR): 0.781
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Spandidos Publications style
Yang M, Li H, Li Y, Ruan Y and Quan C: Identification of genes and pathways associated with MDR in MCF-7/MDR breast cancer cells by RNA-seq analysis. Mol Med Rep 17: 6211-6226, 2018.
APA
Yang, M., Li, H., Li, Y., Ruan, Y., & Quan, C. (2018). Identification of genes and pathways associated with MDR in MCF-7/MDR breast cancer cells by RNA-seq analysis. Molecular Medicine Reports, 17, 6211-6226. https://doi.org/10.3892/mmr.2018.8704
MLA
Yang, M., Li, H., Li, Y., Ruan, Y., Quan, C."Identification of genes and pathways associated with MDR in MCF-7/MDR breast cancer cells by RNA-seq analysis". Molecular Medicine Reports 17.5 (2018): 6211-6226.
Chicago
Yang, M., Li, H., Li, Y., Ruan, Y., Quan, C."Identification of genes and pathways associated with MDR in MCF-7/MDR breast cancer cells by RNA-seq analysis". Molecular Medicine Reports 17, no. 5 (2018): 6211-6226. https://doi.org/10.3892/mmr.2018.8704