1A-O1-1600 PDF
Identification of novel NF1-related molecular networks by integrated proteomics
MS-based quantitative proteomics is widely used for large scale identification and quantification of cellular proteins. However, there are no tools or strategies for the quick data mining and extraction of molecular networks with biologically-important functions. In this study, we developed a unique integrated proteomics strategy, comprising iTRAQ, 2D-DIGE, DNA microarrays, and a proprietary data mining tool [(an integrated protein/gene expression analysis chart (iPEACH)/Molecular Annotation by Gene Ontology (MANGO)] to study the molecular mechanism of NF1 pathogenesis. NF1 tumor suppressor gene product, neurofibromin, functions in part as a Ras-GAP, and though its loss is implicated in the neuronal abnormality of NF1 patients, its precise cellular function remains unclear. We prepared NF1 gene knockdown (KD) PC12 cells, as a NF1 disease model, and analyzed their molecular expression profiles with the integrated proteomics. In NF1-KD PC12 cells, of 3239 molecules quantitatively identified and listed in iPEACH/MANGO, continuously up- or down-regulated molecules over time were extracted. Pathway/network analysis of the differentially-expressed molecules revealed the novel NF1-related abnormal networks, such as “dynein IC2-GR-COX-1 signaling” and “TCTP-mediated oncogenic activation signaling”. Integrated proteomics strategy we developed is useful and effective for identification of disease-related molecular networks being studied.