Medicine and Health Sciences Commons^™

Comprehensive Characterization Of 536 Patient-Derived Xenograft Models Prioritizes Candidatesfor Targeted Treatment., Hua Sun, Song Cao, R Jay Mashl, Chia-Kuei Mo, Simone Zaccaria, Michael C Wendl, Sherri R Davies, Matthew H Bailey, Tina M Primeau, Jeremy Hoog, Jacqueline L Mudd, Dennis A Dean, Rajesh Patidar, Li Chen, Matthew A Wyczalkowski, Reyka G Jayasinghe, Fernanda Martins Rodrigues, Nadezhda V Terekhanova, Yize Li, Kian-Huat Lim, Andrea Wang-Gillam, Brian A Van Tine, Cynthia X Ma, Rebecca Aft, Katherine C Fuh, Julie K Schwarz, Jose P Zevallos, Sidharth V Puram, John F Dipersio, Nci Pdxnet Consortium, Brandi Davis-Dusenbery, Matthew J Ellis, Michael T Lewis, Michael A Davies, Meenhard Herlyn, Bingliang Fang, Jack A Roth, Alana L Welm, Bryan E Welm, Funda Meric-Bernstam, Feng Chen, Ryan C Fields, Shunqiang Li, Ramaswamy Govindan, James H Doroshow, Jeffrey A Moscow, Yvonne A Evrard, Jeffrey Chuang, Benjamin J Raphael, Li Ding, Carol J Bult, Peter N Robinson

Faculty Research 2021

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications …