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Quantitative membrane proteomics applying narrow range peptide isoelectric focusing for studies of small cell lung cancer resistance mechanisms
Karolinska University Hospital.
Karolinska University Hospital.
Linköping University, The Institute of Technology. Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics .
GE Healthcare Biosci AB.
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2008 (English)In: Proteomics, ISSN 1615-9853, Vol. 8, no 15, 3008-3018 p.Article in journal (Refereed) Published
Abstract [en]

Drug resistance is often associated with upregulation of membrane-associated drug-efflux systems, and thus global membrane proteomics methods are valuable tools in the search for novel components of drug resistance phenotypes. Herein we have compared the microsomal proteome from the lung cancer cell line H69 and its isogenic Doxorubicin-resistant subcell line H69AR. The method used includes microsome preparation, iTRAQ labeling followed by narrow range peptide IEF in an immobilized pH-gradient (IPG-IEF) and LC-MS/MS analysis. We demonstrate that the microsomal preparation and iTRAQ labeling is reproducible regarding protein content and composition. The rationale using narrow range peptide IPG-IEF separation is demonstrated by its ability to: (i) lowering the complexity of the sample by two-thirds while keeping high proteome coverage (96%), (ii) providing high separation efficiency, and (iii) allowing for peptide validation and possibly identifications of post-transcriptional modifications. After analyzing one-fifth of the IEF fractions (effective pH range of 4.0-4.5), a total of 3704 proteins were identified, among which 527 were predicted to be membrane proteins. One of the proteins found to be differentially expressed was Serca 2, a calcium pump located in the ER membrane that potentially could result in changes of apoptotic response toward Doxorubicin.

Place, publisher, year, edition, pages
2008. Vol. 8, no 15, 3008-3018 p.
Keyword [en]
Drug resistance, Isoelectric focusing, Lung cancer, Membrane proteins, Quantitative proteomics
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-16263DOI: 10.1002/pmic.200800174OAI: diva2:133564
Available from: 2009-01-12 Created: 2009-01-09 Last updated: 2009-04-27

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