Title |
Identification of Novel Protein Expression Changes Following Cisplatin Treatment and Application to Combination Therapy
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Published in |
Journal of Proteome Research, September 2017
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DOI | 10.1021/acs.jproteome.7b00576 |
Pubmed ID | |
Authors |
Amy L. Stark, Ashraf G. Madian, Sawyer W. Williams, Vincent Chen, Claudia Wing, Ronald J. Hause, Lida Anita To, Amy L. Gill, Jamie L. Myers, Lidija K. Gorsic, Mark F. Ciaccio, Kevin P. White, Richard B. Jones, M. Eileen Dolan |
Abstract |
Determining the effect of chemotherapeutic treatment on changes in protein expression can provide important targets for overcoming resistance. Due to challenges in simultaneously measuring large numbers of proteins, a paucity of data exists on global changes. To overcome these challenges, we utilized microwestern arrays that allowed us to measure the abundance and modification state of hundreds of cell signaling and transcription factor proteins in cells following drug exposure. HapMap lymphoblastoid cell lines (LCLs) were exposed to cisplatin, a chemotherapeutic agent commonly used to treat testicular, head and neck, non-small cell lung, and gynecological cancers. We evaluated the expression of 259 proteins following 2, 6, and 12 hours of cisplatin treatment in two LCLs with discordant sensitivity to cisplatin. Of these 259 proteins, 66 displayed significantly different protein expression changes (p<0.05). Fifteen of these proteins were evaluated in a second pair of LCLs with discordant sensitivities to cisplatin; six demonstrated significant differences in expression. We then evaluated a subset of 63 proteins in a second set of LCLs with discordant sensitivity and 40% of those that were significant in the first pair were also significant in the second part with concordant directionality (p<0.05). We functionally validated one of the top proteins identified, PDK1, and demonstrated a synergistic relationship between cisplatin and a PDK1 inhibitor in multiple lung cancer lines. This study highlights the potential for identifying novel targets through an understanding of cellular changes in protein expression and modification following drug treatments. |
X Demographics
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 11 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 4 | 36% |
Student > Bachelor | 3 | 27% |
Other | 1 | 9% |
Student > Master | 1 | 9% |
Student > Postgraduate | 1 | 9% |
Other | 0 | 0% |
Unknown | 1 | 9% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 6 | 55% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 9% |
Immunology and Microbiology | 1 | 9% |
Neuroscience | 1 | 9% |
Chemistry | 1 | 9% |
Other | 0 | 0% |
Unknown | 1 | 9% |