Dr. Nietzer, who currently serves as the Chair of Tissue Engineering and Regenerative Medicine, will share about a combined in silico and in vitro lung cancer model on a decellularized matrix that enables individualized drug response predictions.
Though lung cancer (LC) therapy has diversified in the last decade, the formation of drug resistance is becoming increasingly burdensome and more reliable prediction of drug responses is necessary for the development of individualized treatment strategies. In order to obtain predictions in a pre-clinical model, Dr. Nietzer and her group generated a 3D LC model based on a decellularized biological matrix using different cell lines with specific driver mutations that represented different response groups of LC patients. Drug response was measured by the quantification of apoptosis and proliferation, and activation changes over 49 RTKs (receptor tyrosine kinase) and 43 phospho-kinases upon treatment were determined.
The Tyrosine Kinase Inhibitor (TKI) gefitinib showed a reduction in proliferation and an induction of apoptosis in cell lines with activating mutations of the Epidermal Growth Factor Receptor (EGFR) gene, but had no effect in cells with the EGFR wild type gene. No significant drug responses were seen in 2D culture. As LC is mostly diagnosed in a late stage of disease, Dr. Nietzerís group also induced an invasion of tumor cells accompanied by EMT (epithelial to mesenchymal transition) via TGFBeta1 stimulation, thus enabling drug testing in advanced states.