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Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling
Published on: July 1, 2014
Differential protein expression analysis using stable isotope labeling and PQD linear ion trap MS technology
Jenny M Armenta1, Ina Hoeschele, Iulia M Lazar
1Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA.
Journal of the American Society for Mass Spectrometry
|April 7, 2009
Summary
A new mass spectrometry method accurately quantifies protein expression changes in MCF-7 cells treated with estrogen and tamoxifen, identifying 16 potential cancer biomarkers involved in key cellular processes.
Area of Science:
- Proteomics
- Cancer Biology
- Biochemistry
Background:
- Differential protein expression analysis is crucial for understanding cellular responses to stimuli.
- Estrogen and tamoxifen are key regulators in estrogen-positive breast cancer, like the MCF-7 cell line.
- Accurate and reproducible protein quantitation methods are needed for biomarker discovery.
Purpose of the Study:
- To develop and optimize an isotope tags for relative and absolute quantitation (iTRAQ)-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for differential protein expression profiling.
- To identify protein expression changes in MCF-7 cells treated with 17beta-estradiol (E2) and tamoxifen (Tam).
- To establish criteria for selecting potential protein biomarkers based on quantitative data.
Main Methods:
- Utilized an iTRAQ-based RPLC-MS/MS approach with a linear trap quadrupole (LTQ) instrument and pulsed Q dissociation (PQD) detection.
- Optimized iTRAQ labeling efficiency and protein identification numbers, applying stringent data filtering for a false positive rate below 4%.
- Employed a data processing strategy for selection, normalization, and statistical evaluation of quantified proteins, requiring at least a 2-fold change for biomarker candidacy.
Main Results:
- Achieved protein identification reproducibility of 50%-67% in LC-MS/MS runs and run-to-run quantitative reproducibility better than 10% RSD.
- Identified 530 proteins in E2/Tam treated MCF-7 cells, with 255 proteins quantified by at least two peptides for differential analysis.
- Detected approximately 16 differentially expressed proteins involved in apoptosis, RNA processing, DNA repair, proliferation, and metastasis.
Conclusions:
- The developed iTRAQ-RPLC-MS/MS method provides a reproducible and accurate approach for differential protein expression profiling in complex cellular systems.
- This study successfully identified potential protein biomarkers associated with estrogen and tamoxifen treatment in MCF-7 cells.
- The findings highlight proteins involved in critical cellular pathways that could serve as therapeutic targets or diagnostic markers in breast cancer.
