Quantitative proteomic analysis of radioresistant breast cancer cell lines.

Abstract

Abstract Abstract #5074 Background: Resistance to radiotherapy may be a significant factor in the development of local recurrence following surgical resection and radiotherapy. We aimed to develop a novel in vitro model of radioresistance using a breast cancer cell line and to subsequently identify molecular biomarkers which may be associated with the radioresistant phenotype. We utilised a quantitative proteomics technique (iTRAQ) based on MALDI-TOF/TOF mass spectrometry (MS) to identify differentially expressed proteins.
 Material and Methods: We established 3 novel breast cancer cell sublines which were significantly resistant to radiotherapy when compared with the parental cells. The radioresistant sublines were created by irradiating cells in fractionated doses of 2Gy up to a total dose of 40Gy. Sufficient time was allowed for the cells to recover between subsequent irradiations. A dose response curve was assessed at the end of treatment to demonstrate a statistically significant increase in radioresistance for each novel cell subline when compared with parental cells. One radioresistant/parental cell pair was first analysed using in-solution digestion and liquid chromatographic separation with protein identification by MALDI-TOF/TOF (LC-MALDI analysis) on an Applied Biosystems 4800 Plus instrument. Quantitative iTRAQ (Applied Biosystems) was then performed on the same instrument for all 3 radioresistant/parental cell pairs.
 Results: A total of 586 and 652 proteins were identified in T47D and T47DRR cells respectively by LC-MALDI. Those proteins identified in both cell lines and any redundant entries were removed to reveal those proteins which were unique to each cell line. In total 244 unique proteins were identified in T47D cells and 311 unique proteins were identified in T47DRR cells.
 Comparison of the 3 pairs of radioresistant/parental cell samples by iTRAQ revealed a number of differentially expressed proteins. Using a standard ≥2-fold change in expression, these iTRAQ analyses revealed significant changes in the expression of 51 proteins in one or more of the radio-resistant derivatives.
 Further confirmation by immunoblotting is underway. Currently the decrease in expression of 26S proteasome associated subunits has been confirmed by this method.
 Conclusion: LC-MALDI and iTRAQ analysis has revealed a large number of candidate proteins which may be associated with a radioresistant phenotype. These now require further confirmatory studies. These MS-based techniques offer a powerful proteomic approach to identify candidate biomarkers which may be involved in radioresistance. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 5074.