A proteomic approach to investigate potential biomarkers directed against membrane-associated breast cancer proteins.

The identification of specific protein markers for breast cancer would provide the basis for early diagnosis. Particularly, membrane and membrane-associated proteins are rich in targets for antibodies that may constitute suitable biomarkers of carcinogenesis. However, membrane proteins separation using 2-DE remains difficult. In this work, the breast cancer cell line MCF7 was used as source of proteins for the screening of potential cell membrane-associated antigens recognized by autoantibodies in patients with breast cancer and healthy volunteers. The protein extract obtained using trifluoroethanol (TFE) as cosolvent was compared to a total cell lysate protein extract prepared by a current technique. After 2-DE separation of the two extracts, their protein patterns clearly differed. About 63% of the proteins identified in the TFE-extract were predicted to possess at least one transmembrane domain. 2-D blots probed with sera from cancer patients or from healthy volunteers showed that, as expected, additional antigens were provided in the TFE-extract. Thus, the method described here appeared well suited for proteomic investigation of potential biomarkers undetected by current techniques.

An efficient proteomics-based approach for the screening of autoantibodies.

This study presents an improved method for the complete transfer of proteins separated by two-dimensional gel electrophoresis to a membrane, specifically designed for the screening and identification of antigens recognized by autoantibodies in patients with breast cancer (BCP) and healthy volunteers. This paper reports the evaluation of this technique using proteins from MCF7 as a source of antigens following 2-DE separation. The appropriate quantity of protein to be loaded on gels (150 microg) has been determined, the aim being a complete and reproducible recovery of all separated proteins onto the polyvinylidene fluoride membrane (2D-blot) after a semi-dry electrotransfer. Several different transfer methods were tested in parallel, resulting in the selection and optimisation of one using a discontinuous buffer system, based on the isotachophoresis theory. To facilitate the comparative analysis of the different sets of 2D-blots probed with individual sera from BCP and healthy volunteers, the 2D-blots were stained with colloidal gold following the immunodetection step. The gels and 2D-blots were scanned and analysed by imaging software. The matching permitted exact localisation of particular relevant protein spots hybridised by antibodies on the 2D-blots. These spots were subsequently located on preparative gels for identification by mass spectrometry. A set of 40 2D-blots was probed with 20 sera from patients with breast cancer and 20 sera from healthy volunteers. In the protein profiles submitted to immunodetection, 15 proteins were repeatedly immunodetected by both BCP and sera from healthy people. Those proteins were identified by mass spectrometry. Conversely, some protein isoforms were preferentially immunodetected by BCP sera and may reflect the presence of this cancer. The improved isotachophoretic method described in this study is suitable for comparing the overall profile of autoimmunity between different populations and for subsequent identification of relevant antigens.

Automating proteome analysis: improvements in throughput, quality and accuracy of protein identification by peptide mass fingerprinting.

The use of robots has major effects on maximizing the proteomic workflow required in an increasing number of high-throughput projects and on increasing the quality of the data. In peptide mass finger printing (PMF), automation of steps downstream of two-dimensional gel electrophoresis is essential. To achieve this goal, the workflow must be fluid. We have developed tools using macros written in Microsoft Excel and Word to complete the automation of our platform. Additionally, because sample preparation is crucial for identification of proteins by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, we optimized a sandwich method usable by any robot for spotting digests on a MALDI target. This procedure enables further efficient automated washing steps directly on the MALDI target. The success rate of PMF identification was evaluated for the automated sandwich method, and for the dried-droplet method implemented on the robot as recommended by the manufacturer. Of the two methods, the sandwich method achieved the highest identification success rate and sequence coverage of proteins.