Breast cancer is the most commonly diagnosed malignancy in women in the Western world, with 13,000 new patients each year in the Netherlands alone. Extensive research on gene expression profiling has shown that breast cancer is a mixture of biologically different disease entities, referred to as molecular subtypes. Of all molecular subtypes, particularly the triple negative phenotype associates with poor prognosis and poor patient survival. Intriguingly, only a small subgroup of triple negative tumors (25%), which metastasize to distant organs within 3 years, accounts for this poor prognosis. Currently, no clinical markers are available to identify triple negative tumors based on positive expression, to predict disease prognosis, and to target therapy against. The aim of our project was to identify prognostic protein markers for triple negative breast cancer using a comparative tissue proteomics approach. We have subjected frozen breast cancer tissue sections to LCM and prepared tryptic digests for nLC-MS analysis. Peptide abundance levels from poor prognosis samples were compared to good prognosis samples to identify differentially abundant peptides and their corresponding proteins. A selection of 34 differentially abundant proteins appeared to significantly differentiate between the two groups. Careful validation of these proteins may lead to better prediction of disease prognosis of triple negative breast cancer patients. Furthermore, functional analysis of key proteins may help unravel the biology of triple negative breast cancer and may lead to the development of new therapies against target proteins.

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Keywords high resolution LC-MS, laser vapture microdissection, putative protein profile, tissue proteomics, triple negative breast cancer
Publisher Netherlands Proteomics Center
Persistent URL hdl.handle.net/1765/22126