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Cancer Res. 2017 Nov 1;77(21):e62-e66. doi: 10.1158/0008-5472.CAN-17-0582.

PDX-MI: Minimal Information for Patient-Derived Tumor Xenograft Models.

Author information

1
European Molecular Biology Laboratory-European Bioinformatics Institute, Hinxton, United Kingdom. tmeehan@ebi.ac.uk.
2
European Molecular Biology Laboratory-European Bioinformatics Institute, Hinxton, United Kingdom.
3
Institute for Computational Health Sciences, University of California, San Francisco, California.
4
Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York.
5
Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts.
6
Hopp-Children's Cancer Center at the NCT Heidelberg (KiTZ), Heidelberg, Germany.
7
Division of Pediatric Neuro-oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.
8
Northrop Grumman Information Systems Health IT, Rockville, Maryland.
9
The Jackson Laboratory, Bar Harbor, Maine.
10
Candiolo Cancer Institute, FPO-IRCC, Department of Oncology, University of Torino, Torino, Italy.
11
Cancer Research UK Cambridge Institute, Cambridge Cancer Centre, University of Cambridge, Cambridge, United Kingdom.
12
Department of Medical Informatics and Clinical Epidemiology and OHSU Library, Oregon Health and Science University, Portland, Oregon.
13
Royal College of Surgeons in Ireland, Ireland.
14
Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas.
15
Oncology Innovative Medicines and Early Development, AstraZeneca R&D Boston, Waltham, Massachusetts.
16
Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
17
Oncodesign Biotechnology and IMODI Consortium, France.
18
Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, Maryland.
19
Oncology Disease Area, Novartis Institutes for Biomedical Research, Switzerland.
20
Cancer Research UK Manchester Institute, The University of Manchester, Manchester, United Kingdom.
21
Champions Oncology, Baltimore, Maryland.
22
Translational Bioinformatics Bristol-Myers Squibb, Pennington, New Jersey.
23
Katholieke Universiteit Leuven, Leuven, Belgium.
24
Greehey Children's Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas.
25
The Netherlands Cancer Institute, Amsterdam, the Netherlands.
26
Institute for Applied Cancer Science, Center for Co-Clinical Trial, The University of Texas MD Anderson Cancer Center, Houston, Texas.
27
The Lester and Sue Smith Breast Center, Departments of Molecular and Cellular Biology and Radiology, Baylor College of Medicine, Houston, Texas.
28
Department of Surgery, School of Medicine, and Mouse Biology Program, University of California Davis, Davis, California.
29
Fred Hutchinson Cancer Research Center, Seattle Children's Hospital, Seattle, Washington.
30
Research Institute for Veterinary Science and Korea Mouse Phenotyping Center, Seoul, Republic of Korea.
31
Seeding Science SAS, Paris, France.
32
Tumor Initiation and Maintenance Program, NCI-Designated Cancer Center, La Jolla, California.
33
Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah.
34
Department of Oncology, Mayo Clinic College of Medicine, Rochester, Minnesota.
35
University of Leuven, Leuven, Belgium.
36
Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany.

Abstract

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62-66. ©2017 AACR.

PMID:
29092942
PMCID:
PMC5738926
DOI:
10.1158/0008-5472.CAN-17-0582
[Indexed for MEDLINE]
Free PMC Article

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