Proteomics-driven approach for the detection of breast cancer biomarkers

Breast cancer (BC) is the most often diagnosed cancer entity of women worldwide. No molecular biomarkers are usable in the clinical routine for the early detection of BC. Proteomics is one of the dynamic tools for the successful examination of changes on the protein level. In this thesis different proteomics-based investigations were performed for the detection of protein and autoantibody biomarkers in serum samples of BC and healthy (CTRL) subjects. First, protein levels of candidates from previous profiling studies were investigated via antibody-microarray platform. Three proteins were found in distinct levels in both groups: secretoglobin family 1D member 1, alpha-2 macroglobulin and inter-alpha-trypsin inhibitor heavy chain family member 4. The second part was dedicated to the de novo exploration of potentially immunogenic tumor antigens (TA’s) with immunoprecipitation and Western immunoblotting followed by identification over mass spectrometry. Autoantibody levels were verified in individual serum profiling via the protein microarray platform. Two autoantibody’ cohorts (anti-Histone 2B and anti-Recoverin) were found in different levels in both groups. The findings of this PhD thesis underline deregulated serum protein and autoantibody levels in the presence of BC. Further investigations are needed to confirm the results in an independent study population.

Plasmonic nanoparticles as sensors : a novel approach to quantify adsorption and diffusion kinetics

Biosensors find wide application in clinical diagnostics, bioprocess control and environmental monitoring. They should not only show high specificity and reproducibility but also a high sensitivity and stability of the signal. Therefore, I introduce a novel sensor technology based on plasmonic nanoparticles which overcomes both of these limitations. Plasmonic nanoparticles exhibit strong absorption and scattering in the visible and near-infrared spectral range. The plasmon resonance, the collective coherent oscillation mode of the conduction band electrons against the positively charged ionic lattice, is sensitive to the local environment of the particle. I monitor these changes in the resonance wavelength by a new dark-field spectroscopy technique. Due to a strong light source and a highly sensitive detector a temporal resolution in the microsecond regime is possible in combination with a high spectral stability. This opens a window to investigate dynamics on the molecular level and to gain knowledge about fundamental biological processes.rnFirst, I investigate adsorption at the non-equilibrium as well as at the equilibrium state. I show the temporal evolution of single adsorption events of fibrinogen on the surface of the sensor on a millisecond timescale. Fibrinogen is a blood plasma protein with a unique shape that plays a central role in blood coagulation and is always involved in cell-biomaterial interactions. Further, I monitor equilibrium coverage fluctuations of sodium dodecyl sulfate and demonstrate a new approach to quantify the characteristic rate constants which is independent of mass transfer interference and long term drifts of the measured signal. This method has been investigated theoretically by Monte-Carlo simulations but so far there has been no sensor technology with a sufficient signal-to-noise ratio.rnSecond, I apply plasmonic nanoparticles as sensors for the determination of diffusion coefficients. Thereby, the sensing volume of a single, immobilized nanorod is used as detection volume. When a diffusing particle enters the detection volume a shift in the resonance wavelength is introduced. As no labeling of the analyte is necessary the hydrodynamic radius and thus the diffusion properties are not altered and can be studied in their natural form. In comparison to the conventional Fluorescence Correlation Spectroscopy technique a volume reduction by a factor of 5000-10000 is reached.