TY - JOUR
T1 - Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment
AU - The NCI PDXNet Consortium
AU - Sun, Hua
AU - Cao, Song
AU - Mashl, R. Jay
AU - Mo, Chia Kuei
AU - Zaccaria, Simone
AU - Wendl, Michael C.
AU - Davies, Sherri R.
AU - Bailey, Matthew H.
AU - Primeau, Tina M.
AU - Hoog, Jeremy
AU - Mudd, Jacqueline L.
AU - Dean, Dennis A.
AU - Patidar, Rajesh
AU - Chen, Li
AU - Wyczalkowski, Matthew A.
AU - Jayasinghe, Reyka G.
AU - Rodrigues, Fernanda Martins
AU - Terekhanova, Nadezhda V.
AU - Li, Yize
AU - Lim, Kian Huat
AU - Wang-Gillam, Andrea
AU - Van Tine, Brian A.
AU - Ma, Cynthia X.
AU - Aft, Rebecca
AU - Fuh, Katherine C.
AU - Schwarz, Julie K.
AU - Zevallos, Jose P.
AU - Puram, Sidharth V.
AU - Dipersio, John F.
AU - Belmar, Julie
AU - Held, Jason
AU - Luo, Jingqin
AU - Van Tine, Brian A.
AU - Tipton, Rose
AU - Wu, Yige
AU - Yao, Lijun
AU - Zhou, Daniel Cui
AU - Butterfield, Andrew
AU - Chu, Zhengtao
AU - Fujita, Maihi
AU - Yang, Chieh Hsiang
AU - Cortes-Sanchez, Emilio
AU - Scherer, Sandra
AU - Zhao, Ling
AU - Borovski, Tijana
AU - Chin, Vicki
AU - DiGiovanna, John
AU - Minna, John D.
AU - Boning, Gao
AU - Girard, Luc
N1 - Funding Information:
This project has been funded by the National Cancer Institute under award U54-CA224083 to L.D, S.L., and R.G. Additional support was provided by The Foundation for Barnes-Jewish Hospital’s Cancer Frontier Fund through the Siteman Cancer Center Investment Program. The breast cancer PDX models from Washington University in St. Louis were developed in part through support from The Breast Cancer Research Foundation and Fashion Footwear Charitable Foundation of New York, Inc. PDMR data were generated with funding from the National Cancer Institute (Contract Number HHSN261200800001E). PDX generation and whole exome sequencing at the University of Texas MD Anderson Cancer Center were supported by the University of Texas MD Anderson Cancer Center Moon Shots Program, Specialized Program of Research Excellence (SPORE) grant CA070907. The development of PDX models and generation of data from Wistar Institute were supported by National Cancer Institute, National Institutes of Health (NCI R50-CA211199). Sample procurement and next-generation sequencing at Huntsman Cancer Institute was performed at the Genomics and Bioin-formatics Analysis and Biorepository and Molecular Pathology Shared Resources, respectively, supported by NCI P30CA042014. M.T.L. is supported by a P30 Cancer Center Support Grant CA125123 and a Core Facility Support Grant from the Cancer Research and Prevention Initiative of Texas RP170691. Support for the PDXNET consortium included funding provided by the NIH to the PDXNet Data Commons and Coordination Center (NCI U24-CA224067), to the PDX Development and Trial Centers (NCI U54-CA224083, NCI U54-CA224070, NCI U54-CA224065, NCI U54-CA224076, NCI U54-CA233223, and NCI U54-CA233306). The Seven Bridges Cancer Research Data Commons Cloud Resource has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, Contract No. HHSN261201400008C and ID/IQ Agreement No. 17 × 146 under Contract No. HHSN261201500003I and 75N91019D00024. The Jackson Laboratory (JAX) PDX resource data were supported by the National Cancer Institute under the JAX Cancer Center NCI Grant (Award Number P30CA034196). The genomic data for JAX PDX tumors used in this work were generated by JAX Genome Technologies and Single Cell Biology Scientific Service. Finally, this project would not have been possible without the generous donation of tissues by our patients.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12/1
Y1 - 2021/12/1
N2 - 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.
AB - 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.
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U2 - 10.1038/s41467-021-25177-3
DO - 10.1038/s41467-021-25177-3
M3 - Article
C2 - 34429404
AN - SCOPUS:85114981330
SN - 2041-1723
VL - 12
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 5086
ER -