Inhibition of protein phosphorylation in MIA pancreatic cancer cells: Confluence of metabolic and signaling pathways

Hengwei Zhang, Rui Cao, Wai Nang Paul Lee, Caishu Deng, Yingchun Zhao, Joan Lappe, Robert Recker, Yun Yen, Qi Wang, Ming Ying Tsai, Vay Liang Go, Gary Guishan Xiao

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Oxythiamine (OT), a transketolase inhibitor, is known to inhibit pancreatic cancer cell proliferation. In this study, we investigated the effect of inhibition of the transketolase pathway on signaling pathways in MIA PaCa cancer cells using in-house proteomic techniques. We hypothesized that OT alter protein phosphorylation thus affecting cell cycle arrest and cell proliferation. MIA PaCa-2 cells were cultured in media containing an algal 15N amino acid mixture at 50% enrichment, with and without OT, to determine protein expression and synthesis. Analysis of cell lysates using two-dimensional gel electrophoresis matrix assisted laser desorption and ionization time-of-flight and time-of-flight mass spectrometry (2-DE-MALDI-TOF/TOF MS) identified 12 phosphor proteins that were significantly suppressed by OT treatment. Many of these proteins are involved in regulation of cycle activities and apoptosis. Among the proteins identified, expression of the phosphor heat shock protein 27 (Hsp27) was dramatically inhibited by OT treatment while the level of its total protein remained unchanged. Hsp27 expression and phoshporylation is known to be associated with drug resistance and cancer cell survival. The changes in phosphorylation of key proteins of cancer proliferation and survival suggest that protein phosphorylation is the confluence of the effects of OT on metabolic and signaling pathways.

Original languageEnglish (US)
Pages (from-to)980-989
Number of pages10
JournalJournal of Proteome Research
Volume9
Issue number2
DOIs
StatePublished - Feb 5 2010
Externally publishedYes

Keywords

  • N stable isotope
  • Oxythiamine
  • Pancreas cancer
  • Phosphorylation
  • Quantitative proteomics
  • Turnover rate

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