Real-time and label free determination of ligand binding-kinetics to primary cancer tissue specimens; a novel tool for the assessment of biomarker targeting
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- Real-time and label free determination of ligand binding-kinetics to primary cancer tissue specimens; a novel tool for the assessment of biomarker targeting
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In clinical oncology, diagnosis and evaluation of optimal treatment strategies are mostly based on histopathological examination combined with immunohistochemical (IHC) expression analysis of cancer-associated antigens in formalin fixed paraffin-embedded (FFPE) tissue biopsies. However, informative IHC analysis depends on both the specificity and affinity of the binding reagent, which are inherently difficult to quantify in situ. Here we describe a label-free method that allows for the direct and real-time assessment of molecular binding kinetics in situ on FFPE tissue specimens using quartz crystal microbalance (QCM) enabled biosensor technology. We analysed the interaction between the rVAR2 protein and its placental-like chondroitin sulfate (pl-CS) receptor in primary human placenta tissue and in breast and prostate tumour specimens in situ. rVAR2 interacted with FFPE human placenta and cancer tissue with an affinity in the nanomolar range, and showed no detectable interaction with pl-CS negative normal tissue. We further validated the method by including analysis with the androgen receptor N-20 antibody (anti-AR). As the KD value produced by this method is independent of the number of epitopes available, this readout offers a quantitative and unbiased readout for in situ binding-avidity and amount of binding epitopes. In summary, this method adds a new and important dimension to classical IHC-based molecular pathology by adding information about the binding characteristics in biologically relevant conditions. This can potentially be used to select optimal biologics for diagnostic and for therapeutic applications as well as guide the development of novel high affinity binding drugs.
|Sensing and Bio-Sensing Research
|Udgivet - jul. 2016
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