Characterization of Kinase Expression Related to Increased Migration of PC-3M Cells Using Global Comparative Phosphoproteome Analysis

Yan Gao, Yun Sok Ha, Tae Gyun Kwon, Young Chang Cho, Sangkyu Lee, Jun Nyung Lee

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Background/Aim: Prostate cancer (PCa) is the second-most commonly occurring cancer among men, worldwide. Although the mechanisms associated with the progression of castration-resistant prostate cancer (CRPC) have been widely studied, the mechanism associated with more distant metastases from the bone remains unknown. This study aimed to characterize potential pathogenic kinases associated with highly metastatic PCa, that may regulate phosphorylation in extensively involved and diverse signaling pathways that are associated with the development of various cancers. Materials and Methods: A mass spectrometry (MS)based comparative phosphoproteome strategy was utilized to identify differentially expressed kinases between the highly aggressive PCa cell-lines PC-3 and PC-3M. Results: Among 2,968 phosphorylation sites in PCa cells, 151 differently expressed phosphoproteins were identified. Seven motifs: -SP-, -SxxE-, -PxS-, -PxSP-, -SxxK-, -SPxK-, and -SxxxxxP- were found to be highly expressed in PC-3M cells. Based on these motifs, the kinases p21-activated kinase (PAK)2, Ste20-like kinase (SLK), mammalian Ste20-like kinase (MST)4, mitogen-activated kinase kinase (MAP2K)2, and A-Raf proto-oncogene serine/threonine kinase (ARAF) were up-regulated in PC-3M cells. Conclusion: PAK2, SLK, MST4, MAP2K2, and ARAF are kinases that are potentially associated with the progression of increased migration in PC-3M cells and may represent molecule regulators or drug targets for highly metastatic PCa therapy.

Original languageEnglish
Pages (from-to)543-553
Number of pages11
JournalCancer Genomics and Proteomics
Volume17
Issue number5
DOIs
StatePublished - 2020

Keywords

  • Kinases
  • Metastatic prostate cancer
  • Phosphorylation
  • Proteomics

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