1. Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment
- Author
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Li Chen, Jacqueline Mudd, Michael Ittmann, Carol J. Bult, Amanda R. Kirane, Jelena Randjelovic, Stephen Scott, Yige Wu, Li Ding, Vashisht G. Yennu-Nanda, Jing Wang, Christopher D. Lanier, Maihi Fujita, Emilio Cortes-Sanchez, Sienna Rocha, Susan G. Hilsenbeck, Kian-Huat Lim, Fernanda Martins Rodrigues, Jill Rubinstein, Nicholas Mitsiades, Haiyin Lin, Jayamanna Wickramasinghe, Andrew Butterfield, Bryan E. Welm, Alana L. Welm, Jose P. Zevallos, Jason Held, Nicole B. Coggins, Song Cao, Yuanxin Xi, Brenda C. Timmons, Paul Lott, David Menter, Shunqiang Li, Tina Primeau, Fei Yang, Andrea Wang-Gillam, Ramaswamy Govindan, Dali Li, Brandi Davis-Dusenbery, Sara Seepo, Michael C. Wendl, Jeffrey Grover, Brian S. White, Clifford G. Tepper, Peter N. Robinson, Michael A. Davies, Zhengtao Chu, Michael W. Lloyd, Hua Sun, Xiaoshan Zhang, Tamara Stankovic, Dylan Fingerman, Anuj Srivastava, Luis G. Carvajal-Carmona, Don L. Gibbons, Lijun Yao, Rebecca Aft, Hongyong Zhang, Ismail Meraz, John DiGiovanna, Scott Kopetz, Ling Zhao, Guadalupe Polanco-Echeverry, Feng Chen, Jeremy Hoog, Matthew A. Wyczalkowski, George Xu, John D. Minna, Yi Xu, Julie Belmar, Xiaowei Xu, Luc Girard, Dennis A. Dean, Tijana Borovski, Chong-xian Pan, Cynthia X. Ma, Alexa Morales Arana, Yize Li, Turcin Saridogan, Steven B. Neuhauser, Sandra Scherer, Vicki Chin, Rose Tipton, David R. Gandara, Sherri R. Davies, Argun Akcakanat, Rajesh Patidar, Julie K. Schwarz, Soner Koc, Gao Boning, Michael Kim, Bryce P. Kirby, Yvonne A. Evrard, Hyunsil Park, Christian Frech, Chia-Kuei Mo, Ran Zhang, Brian A. Van Tine, Jonathan W. Reiss, Min Xiao, Xing Yi Woo, Tiffany Le, Ana Estrada, Xiaofeng Zheng, Jeffrey A. Moscow, Mourad Majidi, Nadezhda V. Terekhanova, Katherine Fuh, Erkan Yuca, Timothy A. Yap, Jianhua Zhang, Matthew J. Ellis, Shannon Westin, James H. Doroshow, Vito W. Rebecca, Moon S. Chen, Coya Tapia, Reyka G Jayasinghe, Jack A. Roth, Jithesh Augustine, Ryan C. Fields, Michae T. Tetzlaff, Michael T. Lewis, Kurt W. Evans, Ralph W. deVere White, Brian J. Sanderson, May Cho, Jeffrey H. Chuang, Tiffany Wallace, Ryan Jeon, Ted Toal, Matthew H. Bailey, Bert W. O'Malley, Katherine L. Nathanson, Qin Liu, Benjamin J. Raphael, Jingqin Luo, Salma Kaochar, Huiqin Chen, Rajasekharan Somasundaram, Daniel Cui Zhou, John F. DiPersio, Andrew V. Kossenkov, Bingliang Fang, Vanessa Jensen, Simone Zaccaria, Alexey Sorokin, Ai-Hong Ma, Sidharth V. Puram, Min Jin Ha, Meenhard Herlyn, R. Jay Mashl, Kelly Gale, Bingbing Dai, Lacey E. Dobrolecki, Chieh-Hsiang Yang, and Funda Meric-Bernstam
- Subjects
endocrine system ,Science ,Druggability ,General Physics and Astronomy ,Genomics ,Computational biology ,Biology ,Genome ,digestive system ,General Biochemistry, Genetics and Molecular Biology ,Article ,Research community ,Multiple time ,medicine ,Cancer genomics ,Cancer models ,Tumor xenograft ,Multidisciplinary ,Cancer ,General Chemistry ,medicine.disease ,Pharmacogenomics ,Data integration ,hormones, hormone substitutes, and hormone antagonists - Abstract
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 and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs’ recapitulation of human tumors., Patient-derived xenograft models (PDX) have been extensively used to study the molecular and clinical features of cancers. Here the authors present a cohort of 536 PDX models from 25 cancers, as well as their genomic and evolutionary profiles and their suitability for clinical trials.
- Published
- 2021