EACR 2016 – Patient-derived xenografts effectively capture patient clinical responses to oncology therapy


Patient-derived xenografts effectively capture patient clinical responses to oncology therapy


Angela Davies1, Justin Stebbing2, Stergios Zacharoulis3, Andrew Gaya4, William McGuire5, William Harris6, Robert Maki7, Manuel Hidalgo8, David Vasquez-Dunddel1, Daniel Ciznadija1, Amanda Katz1, and David Sidransky9.

Presented at

EACR 2016


The high proportion of experimental oncology agents failing to demonstrate sufficient clinical activity represents a continuing challenge and results in part from a failure to appropriately identify responsive patient cohorts. Technologies enabling multiple experimental regimens to be evaluated simultaneously to identify those most likely to be clinically beneficial in specific patient populations are needed. Drug sensitivity screening in patient-derived xenografts (PDXs) is a viable solution, but requires such models to accurately reflect patient clinical outcomes. In this study we examined the capacity of PDXs to replicate patient responses across a heterogeneous population of solid tumors and treatments and report performance metrics highlighting the clinical utility of this tool.

Tumor tissue resected from 611 cancer patients was engrafted into immunodeficient mice to generate PDX models. From these, 90 were screened against the treatments received by the corresponding patient. In some instances, drug selection was based on genomic data obtained through next-generation sequencing. Patient clinical outcomes and model drug responses were assessed and correlated in 126 instances using RECIST criteria, with parameters including sensitivity, specificity, and predictive values calculated to determine the capacity of PDX responses to capture patient responses.

Overall survival for cancer patients remains poor as does the percentage of investigational agents that ultimately demonstrate clinical benefit. Using a large cohort, we have shown PDX model responses correlate strongly with patient clinical outcomes to the same therapy. Application of PDX models to guide treatment decisions in oncology may improve the identification of drugs most likely to benefit individual patients, leading to better outcomes. Moreover, given the clinical relevance of these models, they could also be deployed as real-time patient surrogates during drug development. Establishment of PDX models may also allow real-time analysis of treatment responses during clinical trials and help identify biomarkers that predict different therapeutic outcomes.
Patient-derived xenograft; chemotherapy; clinical response