Abstract
Breast cancer is the most common cancer in women with increasing insidance. Breast cancer occurs as a result of some molecular changes, such as aberrant or dysregulated expression of receptors, in breast epithelial cells. Therefore, breast cancer cells can be detected through their membrane receptors using specific antibodies. This study aims to form a quartz crystal microbalance (QCM) biosensor to detect breast cancer cells. Notch receptor signaling directs many pathways in developing breast tissue and its expression is found to be aberrant or disregulated in metastatic breast cancer cells. Its involvement in malignant transformation makes it a potential drug target. The human metastatic breast cancer cells, MDA MB 231 cells, are used here as a model due to the overexpression of notch-4 receptor on their membranes. First, to increase the surface area of the chip poly(2-hydroxyethyl methacrylate-PHEMA) nanoparticles were synthesized and were placed on QCM chip surface. Then, the surface was further modified and functionalized by binding notch-4 receptor antibody using carbodiimide. Nanoparticle coated and antibody attached QCM chips were characterized via FTIR-ATR, ellipsometry, contact angle measurements and by atomic force microscopy. MDA MB 231 cell samples ranging in numbers between 50-300 cells/ml were introduced to the functionalized QCM chip at a flow rate of 1.0 mL/min and the resonance frequency (f0) was recorded. Then, cell samples were applied to the QCM biosensor and the resonance frequency was monitored. The binding mode fitted best to Langmuir isotherm model. Sensitivity is found to be high and the selectivity as tested by competitive adsorption of L929 mouse fibroblast cells showed that QCM biosensor was 17.5 times more selective for MDA MB 231 cells than the fibroblast cells. The chip was reusable and was stable over 3 months. These results indicate that, the notch-4 receptor antibody PHEMA nanoparticle QCM biosensor is highly selective and efficient system that may be used for cancer cell detection.
Published Version
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