Targeted proteomic analysis of 14-3-3 sigma, a p53 effector commonly silenced in cancer.

Mol Cell Proteomics

Molecular Oncology, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried/Munich, Germany.

Published: June 2005

To comprehensively identify proteins interacting with 14-3-3 sigma in vivo, tandem affinity purification and the multidimensional protein identification technology were combined to characterize 117 proteins associated with 14-3-3 sigma in human cells. The majority of identified proteins contained one or several phosphorylatable 14-3-3-binding sites indicating a potential direct interaction with 14-3-3 sigma. 25 proteins were not previously assigned to any function and were named SIP2-26 (for 14-3-3 sigma-interacting protein). Among the 92 interactors with known function were a number of proteins previously implicated in oncogenic signaling (APC, A-RAF, B-RAF, and c-RAF) and cell cycle regulation (AJUBA, c-TAK, PTOV-1, and WEE1). The largest functional classes comprised proteins involved in the regulation of cytoskeletal dynamics, polarity, adhesion, mitogenic signaling, and motility. Accordingly ectopic 14-3-3 sigma expression prevented cellular migration in a wounding assay and enhanced mitogen-activated protein kinase signaling. The functional diversity of the identified proteins indicates that induction of 14-3-3 sigma could allow p53 to affect numerous processes in addition to the previously characterized inhibitory effect on G2/M progression. The data suggest that the cancer-specific loss of 14-3-3 sigma expression by epigenetic silencing or p53 mutations contributes to cancer formation by multiple routes.

Download full-text PDF

Source
http://dx.doi.org/10.1074/mcp.M500021-MCP200DOI Listing

Publication Analysis

Top Keywords

14-3-3 sigma
28
14-3-3
8
identified proteins
8
sigma expression
8
sigma
7
proteins
7
targeted proteomic
4
proteomic analysis
4
analysis 14-3-3
4
sigma p53
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!