Development of a Data Model and Data Commons for Germ Cell Tumors

Author:

Ci Bo1,Yang Donghan M.1,Krailo Mark23,Xia Caihong3,Yao Bo1,Luo Danni1,Zhou Qinbo1,Xiao Guanghua14,Xu Lin1,Skapek Stephen X.56,Murray Matthew J.7,Amatruda James F.28,Klosterkemper Lindsay9,Shaikh Furqan10,Faure-Conter Cecile11,Fresneau Brice12,Volchenboum Samuel L.13,Stoneham Sara14,Lopes Luiz Fernando15,Nicholson James16,Frazier A. Lindsay9,Xie Yang146

Affiliation:

1. Quantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX

2. Keck School of Medicine, University of Southern California, Los Angeles, CA

3. Children’s Oncology Group, Monrovia, CA

4. Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX

5. Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX

6. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX

7. Department of Pathology, University of Cambridge, Cambridge, United Kingdom

8. Cancer and Blood Disease Institute, Children’s Hospital Los Angeles, Los Angeles, CA

9. Dana-Farber/Boston Children’s Blood and Cancer Disorders Center, Boston, MA

10. Hospital for Sick Children, University of Toronto, Toronto, ON, Canada

11. Institute of Hematology and Pediatric Oncology, Lyon, France

12. Department of Pediatric Oncology, Gustave Roussy, University of Paris-Saclay, Villejuif, France

13. Center for Research Informatics, Division of Medicine and Biological Sciences, University of Chicago, Chicago, IL

14. Department of Paediatrics, University College London Hospitals, London, United Kingdom

15. Children’s Cancer Hospital, Barretos Cancer Center, Barretos, Brazil

16. Department of Paediatric Haematology and Oncology, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, United Kingdom

Abstract

Germ cell tumors (GCTs) are considered a rare disease but are the most common solid tumors in adolescents and young adults, accounting for 15% of all malignancies in this age group. The rarity of GCTs in some groups, particularly children, has impeded progress in treatment and biologic understanding. The most effective GCT research will result from the interrogation of data sets from historical and prospective trials across institutions. However, inconsistent use of terminology among groups, different sample-labeling rules, and lack of data standards have hampered researchers’ efforts in data sharing and across-study validation. To overcome the low interoperability of data and facilitate future clinical trials, we worked with the Malignant Germ Cell International Consortium (MaGIC) and developed a GCT clinical data model as a uniform standard to curate and harmonize GCT data sets. This data model will also be the standard for prospective data collection in future trials. Using the GCT data model, we developed a GCT data commons with data sets from both MaGIC and public domains as an integrated research platform. The commons supports functions, such as data query, management, sharing, visualization, and analysis of the harmonized data, as well as patient cohort discovery. This GCT data commons will facilitate future collaborative research to advance the biologic understanding and treatment of GCTs. Moreover, the framework of the GCT data model and data commons will provide insights for other rare disease research communities into developing similar collaborative research platforms.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

General Medicine

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