TY - JOUR
T1 - Systematic establishment of robustness and standards in patient-derived xenograft experiments and analysis
AU - NCI PDXNet Consortium
AU - Evrard, Yvonne A.
AU - Srivastava, Anuj
AU - Randjelovic, Jelena
AU - Doroshow, James H.
AU - Dean, Dennis A.
AU - Morris, Jeffrey S.
AU - Chuang, Jeffrey H.
AU - Kaochar, Salma
AU - Lewis, Michael T.
AU - Mitsiades, Nicolas
AU - Chen, Li
AU - Patidar, Rajesh
AU - Robinson, Peter N.
AU - Zhao, Zi Ming
AU - Bult, Carol J.
AU - Lloyd, Michael
AU - Neuhauser, Steven
AU - Woo, Xing Yi
AU - Moscow, Jeffrey A.
AU - Davis-Dusenbery, Brandi
AU - DiGiovanna, Jack
AU - Frech, Christian
AU - Jeon, Ryan
AU - Miletic, Nevena
AU - Rosains, Jacqueline
AU - Seth, Isheeta
AU - Stankovic, Tamara
AU - Stanojevic, Adam
AU - Carvajal-Carmona, Luis
AU - Chen, Moon
AU - Pan, Chong Xian
AU - Chen, Huiqin
AU - Davies, Michael
AU - Fang, Bingliang
AU - Ha, Min Jin
AU - Meric-Bernstam, Funda
AU - Roth, Jack
AU - Arunachalam, Sasi
AU - Nix, David
AU - Welm, Alana L.
AU - Welm, Bryan E.
AU - Davies, Sherri
AU - Ding, Li
AU - Govindan, Ramaswamy
AU - Li, Shunqiang
AU - Ma, Cynthia
AU - van Tine, Brian A.
AU - Herlyn, Meenhard
AU - Kossenkov, Andrew
AU - Rebecca, Vito
N1 - Funding Information:
F. Meric-Bernstam reports receiving commercial research grants from Novartis, AstraZeneca, Calithera, Aileron, Bayer, Jounce, CytoMx, eFFECTOR, Zymeworks, PUMA Biotechnology, Curis, Millennium, Daiichi Sankyo, Abbvie, Guardant Health,
Funding Information:
This work was supported 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, NCI U54-CA233306), and to the Cancer Genomics Cloud (HHSN261201400008C and HHSN261201500003I). All authors in this publication are part of the NCI PDXNet Consortium. Additional contributing members are: Baylor College of Medicine, Houston, TX (Salma Kaochar, Michael T. Lewis, Nicolas Mitsiades); Frederick National Laboratory for Cancer Research, Frederick, MD (Li Chen, Rajesh Patidar); The Jackson Laboratory for Genomic Medicine, Farmington, CT (Peter N. Robinson, Zi-Ming Zhao); The Jackson Laboratory, Bar Harbor, ME (Carol J. Bult, Michael Lloyd, Steven Neuhauser, Xing Yi Woo); National Cancer Institute, Investigational Drug Branch, Bethesda, MD (Jeffrey A. Moscow); Seven Bridges Genomics, Inc., Cambridge, Charlestown, MA (Brandi Davis-Dusenb-ery, Jack DiGiovanna, Christian Frech, Ryan Jeon, Nevena Miletic, Jacqueline Rosains, Isheeta Seth, Tamara Stankovic, Adam Stanojevic); University of California School of Medicine, Davis, CA (Luis Carvajal-Carmona, Moon Chen, Chong-Xian Pan); The University of Texas M.D. Anderson Cancer Center, Houston, TX (Huiqin Chen, Michael Davies, Bingliang Fang, Min Jin Ha, Funda Meric-Bernstam, Jack Roth); University of Utah Huntsman Cancer Institute, Salt Lake City, UT (Sasi Arunachalam, David Nix, Alana L. Welm, Bryan E. Welm); Washington University School of Medicine in St. Louis, St. Louis, MO (Sherri Davies, Li Ding, Ramaswamy Govindan, Shunqiang Li, Cynthia Ma, Brian A. Van Tine); The Wistar Institute, Philadelphia, PA (Meenhard Herlyn, Andrew Kossenkov, Vito Rebecca, Jayamanna Wickramasinghe, Min Xiao).
Publisher Copyright:
© 2020 American Association for Cancer Research.
PY - 2020/6
Y1 - 2020/6
N2 - Patient-derived xenografts (PDX) are tumor-in-mouse models for cancer. PDX collections, such as the NCI PDXNet, are powerful resources for preclinical therapeutic testing. However, variations in experimental and analysis procedures have limited interpretability. To determine the robustness of PDX studies, the PDXNet tested temozolomide drug response for three prevalidated PDX models (sensitive, resistant, and intermediate) across four blinded PDX Development and Trial Centers using independently selected standard operating procedures. Each PDTC was able to correctly identify the sensitive, resistant, and intermediate models, and statistical evaluations were concordant across all groups. We also developed and benchmarked optimized PDX informatics pipelines, and these yielded robust assessments across xenograft biological replicates. These studies show that PDX drug responses and sequence results are reproducible across diverse experimental protocols. In addition, we share the range of experimental procedures that maintained robustness, as well as standardized cloud-based workflows for PDX exome-sequencing and RNA-sequencing analyses and for evaluating growth.
AB - Patient-derived xenografts (PDX) are tumor-in-mouse models for cancer. PDX collections, such as the NCI PDXNet, are powerful resources for preclinical therapeutic testing. However, variations in experimental and analysis procedures have limited interpretability. To determine the robustness of PDX studies, the PDXNet tested temozolomide drug response for three prevalidated PDX models (sensitive, resistant, and intermediate) across four blinded PDX Development and Trial Centers using independently selected standard operating procedures. Each PDTC was able to correctly identify the sensitive, resistant, and intermediate models, and statistical evaluations were concordant across all groups. We also developed and benchmarked optimized PDX informatics pipelines, and these yielded robust assessments across xenograft biological replicates. These studies show that PDX drug responses and sequence results are reproducible across diverse experimental protocols. In addition, we share the range of experimental procedures that maintained robustness, as well as standardized cloud-based workflows for PDX exome-sequencing and RNA-sequencing analyses and for evaluating growth.
UR - http://www.scopus.com/inward/record.url?scp=85085905384&partnerID=8YFLogxK
U2 - 10.1158/0008-5472.CAN-19-3101
DO - 10.1158/0008-5472.CAN-19-3101
M3 - Article
C2 - 32152150
AN - SCOPUS:85085905384
SN - 0008-5472
VL - 80
SP - 2286
EP - 2297
JO - Cancer research
JF - Cancer research
IS - 11
ER -