Publication: Osteosarcoma enters a post genomic era with in silico opportunities: Generation of the High Dimensional Database for facilitating sarcoma biology research: A report from the Children's Oncology Group and the QuadW Foundation
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Date
2017
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Public Library of Science
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Citation
Glover, J., T. Man, D. A. Barkauskas, D. Hall, T. Tello, M. B. Sullivan, R. Gorlick, et al. 2017. “Osteosarcoma enters a post genomic era with in silico opportunities: Generation of the High Dimensional Database for facilitating sarcoma biology research: A report from the Children's Oncology Group and the QuadW Foundation.” PLoS ONE 12 (7): e0181204. doi:10.1371/journal.pone.0181204. http://dx.doi.org/10.1371/journal.pone.0181204.
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Abstract
The prospective banking of osteosarcoma tissue samples to promote research endeavors has been realized through the establishment of a nationally centralized biospecimen repository, the Children’s Oncology Group (COG) biospecimen bank located at the Biopathology Center (BPC)/Nationwide Children’s Hospital in Columbus, Ohio. Although the physical inventory of osteosarcoma biospecimens is substantive (>15,000 sample specimens), the nature of these resources remains exhaustible. Despite judicious allocation of these high-value biospecimens for conducting sarcoma-related research, a deeper understanding of osteosarcoma biology, in particular metastases, remains unrealized. In addition the identification and development of novel diagnostics and effective therapeutics remain elusive. The QuadW-COG Childhood Sarcoma Biostatistics and Annotation Office (CSBAO) has developed the High Dimensional Data (HDD) platform to complement the existing physical inventory and to promote in silico hypothesis testing in sarcoma biology. The HDD is a relational biologic database derived from matched osteosarcoma biospecimens in which diverse experimental readouts have been generated and digitally deposited. As proof-of-concept, we demonstrate that the HDD platform can be utilized to address previously unrealized biologic questions though the systematic juxtaposition of diverse datasets derived from shared biospecimens. The continued population of the HDD platform with high-value, high-throughput and mineable datasets allows a shared and reusable resource for researchers, both experimentalists and bioinformatics investigators, to propose and answer questions in silico that advance our understanding of osteosarcoma biology.
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Keywords
Medicine and Health Sciences, Oncology, Cancers and Neoplasms, Sarcomas, Osteosarcoma, Biology and Life Sciences, Genetics, Gene Expression, Bioassays and Physiological Analysis, Microarrays, Database and Informatics Methods, Biological Databases, Genomic Databases, Computational Biology, Genome Analysis, Genomics, Computer and Information Sciences, Information Technology, Databases, Relational Databases, Bioinformatics
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