A Comprehensive Germ Cell Tumor Data Commons and Its Application in Risk Classification Model Validation

• Activity Number: 303 - Patient-Centered Outcomes, Patient Preferences, and Patient Reports
• Type: Contributed
• Date/Time: Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
• Sponsor: Health Policy Statistics Section
• Author(s): Bo Ci* and Yang Xie and Lindsay Frazier and Matthew Murray and James Amatruda and Mark Krailo and Samuel Volchenboum and Bo Yao and Caihong Xia and Lin Xu and Danni Luo and Shin-Yi Lin
• Companies: and University of Texas Southwestern Medical Center and Dana-Farber Cancer Institute and Cambridge University Hospitals and University of Texas Southwestern Medical Center and University of Southern California and University of Chicago and University of Texas Southwestern Medical Center and Children's Oncology Group and University of Texas Southwestern Medical Center and University of Texas Southwestern Medical Center and University of Texas Southwestern Medical Center
• Keywords: germ cell tumor; data commons; data standard; risk classification; personal therapy ; big data

Abstract

Germ cell tumors (GCTs) are a generally rare disease, but they account for 15% of all malignancies diagnosed during adolescence. Therapy-related toxicity is significant in GCT patients, rendering an urgent need to identify biomarkers to tailor the therapy for each patient. However, progress toward better treatments is severely hamstrung by the rarity of the disease. To overcome this difficulty, we collaborated with the Malignant Germ Cell International Consortium (MaGIC) to build a comprehensive germ cell tumor data commons harboring clinical, biospecimen and genomics data (https://qbrc.swmed.edu/projects/gct/). The commons currently includes data from 14 clinical trials, 1434 patients and 367 biospecimens. Using this data, we validated a risk classification model for GCTs developed by MaGIC. Tumor site, metastasis stage and age at diagnosis were significantly associated with the clinical outcome of the patients. In this work, we developed the first comprehensive GCT data commons to enable efficient and safe data sharing across institutes. The validated risk model will also assist in clinical practice to help tailor the treatment for individual patients.