Abstract 998: OPeN: the oncology precision network data sharing consortium
| Autor: | Lincoln Nadauld, Mariko Tameishi, Derrick S. Haslem, James M. Ford, Thomas J. Brown, Paul D. Tittel |
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| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Cancer Research. 77:998-998 |
| ISSN: | 1538-7445 0008-5472 |
| DOI: | 10.1158/1538-7445.am2017-998 |
| Popis: | Background: The advent of Next-Generation Sequencing (NGS), and other molecular diagnostic technologies, has enabled the use of genomic information to guide targeted treatment in cancer patients. While this precision oncology approach can yield exciting clinical outcomes, the innumerable genomic variants identified in individual tumors effectively establishes each case as a unique N=1 clinical presentation. This scenario is contrary to a basic dogma of medical practice where historical cases and treatment outcomes guide future management and therapeutic decisions. Aggregation of large data sets, on a multi-institutional basis, has the potential to overcome the N=1 paradox and yield management insights in the implementation of precision oncology. Methods: We have formed the Oncology Precision Network (OPeN), an oncology data sharing consortium, to aggregate big data sets consisting of clinical, genomic, pharmacological, and treatment response data from diverse patient cases. Data from Intermountain Healthcare, Stanford University, and Swedish Cancer Institute-Providence St. Joseph Health, as well as other institutions, comprises the database and is derived from 79 hospitals, over 800 physician clinics and more than 50,000 annual cases. Results: The OPeN database can be interrogated by variant type, specific therapeutics, clinical outcomes, and by grouped variables, in a structured data format. The overarching IT platform is a cloud based, open source, triple store precision oncology solution, Syapse. These data are yielding valuable insights, including tumor mutational burden (TMB) scores and their correlation to immunotherapy response, clinical response in various drug-gene combinations, and therapy-specific adverse events. Conclusions: We anticipate this resource will be used by the Molecular Tumor Boards of contributing institutions for clinical interpretation, and by treating providers to overcome the N=1 challenge associated with precision oncology. Citation Format: Lincoln Nadauld, Derrick Haslem, Paul D. Tittel, Mariko Tameishi, Thomas Brown, James Ford. OPeN: the oncology precision network data sharing consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 998. doi:10.1158/1538-7445.AM2017-998 |
| Databáze: | OpenAIRE |
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