Proteomic analysis of proteins associated with the paclitaxel-induced drug-resistant human breast cancer cells

  • Si Ying Chen
  • , Jiang Xia Cai
  • , Wei Peng Zhang
  • , Jin Yao Sun
  • , Tao Tao Wang
  • , Jun Lu
  • , Ya Lin Dong

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

OBJECTIVE: To investigate multidrug resistance (MDR) in the paclitaxel-induced drug-resistant breast cancer MCF-7 cells (MCF-7/Tax) using proteomic analysis. METHODS: MCF-7/Tax cell line was established by escalating the concentrations of paclitaxel to drug-sensitive MCF-7 cells (MCF-7/S). The biological characteristics of MCF-7/Tax cells were analyzed using MTT test and flow cytometry. The global protein profiles of MCF-7/Tax and MCF-7/S were compared using two-dimensional gel electrophoresis (2-DF) and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS). We confirmed the protein and mRNA levels of five differential patterns of expression by Western blot and Real-time PCR, respectively. RESULTS: The resistance factor of MCF-7/Tax was 115. Significant differential expressions of 17 proteins between MCF-7/Tax and MCF-7/S were identified with 11 proteins upregulated and six proteins downregulated in MCF-7/Tax cells. With western blot and real-time PCR, we confirmed that heterogeneous nuclear ribonucleoprotein (hnRNP C1/C2), SET nuclear oncogene (SET), aspartate aminotransferase (AAT), transgelin-2 were upregulated, and nucleoside-diphosphate kinase A (NDKA) was downregulated in MCF-7/Tax cells. CONCLUSION: The identification of differential proteins, particularly transgelin-2 provides new insights into the mechanism of MDR to paclitaxel and novel biological targets for breast cancer treatment.

Original languageEnglish
Pages (from-to)825-832
Number of pages8
JournalChinese Pharmaceutical Journal
Volume49
Issue number10
DOIs
StatePublished - 22 May 2014
Externally publishedYes

Keywords

  • Breast cancer
  • Multidrug resistance
  • Paclitaxel
  • Proteomics

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