オーラルセッション
- 第4日 5月18日（金） 15:05～15:25 A会場（オービットホール）
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4A-O2-P-1505 PDF
統合翻訳後修飾プロテオミクス法による癌バイオマーカーの体系的探索
Protein post-translational modification-dependent cellular signaling is known to play a critical role in regulating multiple cellular processes such as proliferation, differentiation and apoptosis. Previous functional analyses of cancer cell signaling under a variety of experimental conditions revealed many of the key molecules and their related protein modifications regarding each type of cancer. Recent technological advances in mass spectrometry-based proteomics have also enabled us to measure post-translational modification-dependent signaling dynamics in a comprehensive manner. In order to systematically discover clinically important biomarker candidates from cancer-specific protein modifications on signaling molecules, we have developed a high-resolution mass spectrometry-based proteomics methodology for integrative identification of post-translational modifications from various types of cancer cells. The bioinformatical approaches using IPA, NetworKIN and a newly developed platform named PTMapper allowed us to perform network‐wide prediction of upstream interactors/kinases with the related information on the diseases and functions, leading to systematic finding of novel drug candidates to regulate aberrant cell signaling. In this presentation, we would like to introduce our recent works on statistical network analyses of cancer cell signaling dynamics based on the large‐scale phosphoproteome data and discuss the future diagnostic potential of protein modification-oriented medical big data.