EORTC 2017-Patient-derived xenograft (PDX) models of NSCLC reflect clinical drug responses and predict effective treatments for patients


Patient-derived xenograft (PDX) models of NSCLC reflect clinical drug responses and predict effective treatments for patients


Daniel Ciznadija1, Igor Astaturov2, Haiying Cheng3, Nir Peled4, Jennifer Jaskowiak1, Angela Davies1, and David Sidransky1 Champions Oncology, Baltimore, USA. 2 Fox Chase Cancer Center, Philadelphia, USA. 3 Albert Einstein College of Medicine (Montefiore), New York, USA. 4 Rabin Medical Center, Tel Aviv, Israel. 5 Johns Hopkins University School of Medicine, Baltimore, USA

Presented at

EORTC 2017


Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality and prognosis remains poor despite the availability of numerous therapies. Integration of drug screening and sequencing in PDX models may allow for improved understanding of mechanisms of resistance (de novo and acquired), identification of biomarkers, and optimization of therapeutic strategies for NSCLC patients. In this study, we evaluated the response of NSCLC PDX models to multiple therapies and correlated responses to known clinical outcomes and molecular characteristics.

PDX models were developed from 86 patients with NSCLC and evaluated by next-generation sequencing for genomic alterations (mutations, amplifications/deletions, fusions, and gene expression changes). Models were screened against different therapies including first line platinum and non-platinum doublets and triplets, second line single agent docetaxel and pemetrexed (second line therapies) and EGFR-targeted inhibitors. Tumor regression (TR) values and RECIST criteria were determined and correlated with known literature-based response rates (RR) as well as individual patient outcomes.
Our study demonstrated the strong alignment between PDX model response to standard of care therapies and patient clinical outcomes, which highlights the potential application of PDX models for translational modeling and utilizing cohorts of PDX models for clinical trial simulation. The responses of these models to different lines of therapy reflected corresponding patient outcomes both at an individual and population level. Comprehensive sequencing (WES and RNA) and standard of care drug testing of these PDX models is planned and could allow a deeper understanding of such mechanisms. In this context, application of PDX models to drug development and stratification of clinical trial patients for treatment will continue to evolve.