Abstract
e21022 Background: Breast cancer is the most common cancer type in women worldwide. Its early detection is a crucial step for the successful treatment. Although many serum biomarkers were described for breast cancer, all of them still lack of clinical specificity and sensitivity for the early detection. Therefore, we developed and evaluated a proteomics-approach for detection of biomarkers in serum of breast cancer patients and tried to identify differently regulated proteins. Methods: Blood samples of 50 women with breast cancer (CA) and 50 age-matched healthy women (CTRL) were drawn prior to surgery and respective sera were obtained. We used surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS) for protein profiling with three active surfaces of the protein chips with different binding properties. Data was analyzed by multivariate statistical techniques and artificial neural networks. Results: We obtained a protein profile with 15 differently regulated proteins. Ten of them were upregulated in sera of breast cancer patients. The diagnostic pattern could discriminate CA from CRTL with specificity of 77% and sensitivity of 85%, the area under curve (AUC) of 0.85 was achieved. Two of upregulated proteins in breast cancer sera are Inter-a (globulin) inhibitor H4 (ITIH4) and Apolipoprotein C-I (ApoC-1). Conclusions: SELDI-TOF-MS is a promising, non-invasive tool for detection of breast cancer biomarkers with low sample amounts and high sensitivity and specificity. The next step of this project is the identification of all obtained biomarkers from our protein profiles and a validation serum study in a larger study population. The knowledge of different regulated proteins can help to understand the development of cancer, possibly leading to its early detection. No significant financial relationships to disclose.
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