Julia Schueler, Research Director Discovery Services, explains how her team used the tumor model database to select the most relevant models for the well-known target EGFR to showcase the feasibility of the selection in the different drug development platforms.
Julia Schuler (00:07): The Charles River compendium is an online tool which gives you access to more than 700 different tumor models, including PDX, cell-line derived models, as well as syngeneic lines. The PDX compendium was used by us, using the well-known target EGFR in oncology, and we then used the selected models to showcase the feasibility of the selection in the different drug development platforms. So we used EGFR based on RNA expression and selected the models in the online compendium. We selected high expressors as well as low expressors. And in a first attempt, we used 75 different lines in a 2D assay and screened more than 20 different EGFR targeting compounds. We saw there that we have around 25 high expressing models which were highly sensitive, and 23 resistant models. So we confirmed and even extended those data by using almost 300 different PDX models in our 3D assay, which is a soft agar based essay, where we tested 10 different EGFR targeting compounds in this 300 different PDX models. Julia Schuler (01:22): We saw high sensitive models, mainly in the gastric cancer, as well as in non-small cell lung cancer and renal cancers. But we as well identified highly resistant models. To show that our in vitro platforms are predictive for the more important in vivo part, we tested as well, three of these are targeting compounds. This was cetuximab, gefitinib, and erlotinib in 25 different PDX models in vivo. For the small molecules, gefitinib and erlotinib. The productivity of our in vitro 3D assay was a very high for in vivo testing. To give an additional layer to this drug development platform, we could also do bioinformatic as well as biomarker studies, which enabled us to identify predictive biomarkers within our PDX collection, which can then be tested in a clinical as well as in a translational space.