Reconstructing targetable pathways in lung cancer by integrating diverse omics data.
| Autor: | Balbin OA; 1] Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, Michigan 8109, USA [2] Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, USA [3] Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA., Prensner JR, Sahu A, Yocum A, Shankar S, Malik R, Fermin D, Dhanasekaran SM, Chandler B, Thomas D, Beer DG, Cao X, Nesvizhskii AI, Chinnaiyan AM |
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| Jazyk: | angličtina |
| Zdroj: | Nature communications [Nat Commun] 2013; Vol. 4, pp. 2617. |
| DOI: | 10.1038/ncomms3617 |
| Abstrakt: | Global 'multi-omics' profiling of cancer cells harbours the potential for characterizing the signalling networks associated with specific oncogenes. Here we profile the transcriptome, proteome and phosphoproteome in a panel of non-small cell lung cancer (NSCLC) cell lines in order to reconstruct targetable networks associated with KRAS dependency. We develop a two-step bioinformatics strategy addressing the challenge of integrating these disparate data sets. We first define an 'abundance-score' combining transcript, protein and phospho-protein abundances to nominate differentially abundant proteins and then use the Prize Collecting Steiner Tree algorithm to identify functional sub-networks. We identify three modules centred on KRAS and MET, LCK and PAK1 and β-Catenin. We validate activation of these proteins in KRAS-dependent (KRAS-Dep) cells and perform functional studies defining LCK as a critical gene for cell proliferation in KRAS-Dep but not KRAS-independent NSCLCs. These results suggest that LCK is a potential druggable target protein in KRAS-Dep lung cancers. |
| Databáze: | MEDLINE |
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