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Comparative proteome analysis across non-small cell lung cancer cell lines

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Schaab,  Christoph
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Grundner-Culemann, K., Dybowski, J. N., Klammer, M., Tebbe, A., Schaab, C., & Daub, H. (2016). Comparative proteome analysis across non-small cell lung cancer cell lines. Journal of Proteomics, 130, 1-10. doi:10.1016/j.jprot.2015.09.003.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0029-5966-E
Abstract
Non-small cell lung cancer (NSCLC) cell lines are widely used model systems to study molecular aspects of lung cancer. Comparative and in-depth proteome expression data across many NSCLC cell lines has not been generated yet, but would be of utility for the investigation of candidate targets and markers in oncogenesis. We employed a SILAC reference approach to perform replicate proteome quantifications across 23 distinct NSCLC cell lines. On average, close to 4000 distinct proteins were identified and quantified per cell line. These included many known targets and diagnostic markers, indicating that our proteome expression data represents a useful resource for NSCLC pre-clinical research. To assess proteome diversity within the NSCLC cell line panel, we performed hierarchical clustering and principal component analysis of proteome expression data. Our results indicate that general proteome diversity among NSCLC cell lines supersedes potential effects common to K-Ras or epidermal growth factor receptor (EGFR) oncoprotein expression. However, we observed partial segregation of EGFR or KRAS mutant cell lines for certain principal components, which reflected biological differences according to gene ontology enrichment analyses. Moreover, statistical analysis revealed several proteins that were significantly overexpressed in KRAS or EGFR mutant cell lines. (C) 2015 Elsevier B.V. All rights reserved.