Ritika Kundra1, Hongxin Zhang1, Robert Sheridan1, Sahussapont Joseph Sirintrapun2, Avery Wang1, Angelica Ochoa1, Manda Wilson1, Benjamin Gross1, Yichao Sun1, Ramyasree Madupuri1, Baby A Satravada1, Dalicia Reales3, Efsevia Vakiani1, Hikmat A Al-Ahmadie2, Ahmet Dogan2, Maria Arcila4, Ahmet Zehir2, Steven Maron5, Michael F Berger1,2,6, Cristina Viaplana7, Katherine Janeway8, Matthew Ducar9, Lynette Sholl10,11, Snjezana Dogan2, Philippe Bedard1,12, Lea F Surrey13,14, Iker Huerga Sanchez15, Aijaz Syed2, Anoop Balakrishnan Rema2, Debyani Chakravarty1, Sarah Suehnholz1, Moriah Nissan1, Gopakumar V Iyer5, Rajmohan Murali2, Nancy Bouvier16, Robert A Soslow2, David Hyman17, Anas Younes18, Andrew Intlekofer6, James J Harding5,19, Richard D Carvajal20, Paul J Sabbatini5,19, Ghassan K Abou-Alfa5, Luc Morris6,21,22, Yelena Y Janjigian5, Meighan M Gallagher23, Tara A Soumerai24, Ingo K Mellinghoff5,6, Abraham A Hakimi25, Matthew Fury26, Jason T Huse27, Aditya Bagrodia28, Meera Hameed2, Stacy Thomas29, Stuart Gardos29, Ethan Cerami30, Tali Mazor31, Priti Kumari31, Pichai Raman32, Priyanka Shivdasani10, Suzanne MacFarland33,34, Scott Newman35, Angela Waanders36, Jianjiong Gao1, David Solit1,5,6,20, Nikolaus Schultz1,6,37. 1. Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY. 2. Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY. 3. Clinical Research Administration, Memorial Sloan Kettering Cancer Center, New York, NY. 4. Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY. 5. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY. 6. Human Oncology and Pathogenesis Program, Memorial Sloan Kettering, New York, NY. 7. Oncology Data Science (ODysSey Group), Vall d'Hebron Institute of Oncology, Barcelona, Spain. 8. Pediatrics, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA. 9. Foundation Medicine, Boston, MA. 10. Department of Pathology, Brigham and Women's Hospital, Boston, MA. 11. Department of Pathology, Harvard Medical School, Boston, MA. 12. Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, ON, Canada. 13. Cancer Genomics Program, Princess Margaret Cancer Centre, Toronto, ON, Canada. 14. Department of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, PA. 15. Tempus Labs Inc, New York, NY. 16. Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY. 17. Loxo Oncology Inc, Stamford, CT. 18. AstraZeneca, US, Wilmington, DE. 19. Department of Medicine, Weill Cornell Medical College, New York, NY. 20. Department of Medicine, Columbia University Medical Center, New York, NY. 21. Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering, New York, NY. 22. Department of Surgery, Memorial Sloan Kettering, New York, NY. 23. ExecuPharm, King of Prussia, PA. 24. Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA. 25. Department of Urology, Memorial Sloan Kettering Cancer Center, New York, NY. 26. Regeneron Pharmaceuticals, Tarrytown, NY. 27. Departments of Pathology and Translational Molecular Pathology, University of Texas, MD Anderson Cancer Center, Houston, TX. 28. Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX. 29. Information Systems, Memorial Sloan Kettering Cancer Center, New York, NY. 30. Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA. 31. Knowledge Systems Group, Dana-Farber Cancer Institute, Boston, MA. 32. GlaxoSmithKline. 33. Division of Oncology, Children's Hospital of Philadelphia, Philadelphia, PA. 34. University of Pennsylvania School of Medicine, Philadelphia, PA. 35. Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN. 36. Children's Hospital of Chicago, Chicago, IL. 37. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering, New York, NY.
Abstract
PURPOSE: Cancer classification is foundational for patient care and oncology research. Systems such as International Classification of Diseases for Oncology (ICD-O), Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), and National Cancer Institute Thesaurus (NCIt) provide large sets of cancer classification terminologies but they lack a dynamic modernized cancer classification platform that addresses the fast-evolving needs in clinical reporting of genomic sequencing results and associated oncology research. METHODS: To meet these needs, we have developed OncoTree, an open-source cancer classification system. It is maintained by a cross-institutional committee of oncologists, pathologists, scientists, and engineers, accessible via an open-source Web user interface and an application programming interface. RESULTS: OncoTree currently includes 868 tumor types across 32 organ sites. OncoTree has been adopted as the tumor classification system for American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE), a large genomic and clinical data-sharing consortium, and for clinical molecular testing efforts at Memorial Sloan Kettering Cancer Center and Dana-Farber Cancer Institute. It is also used by precision oncology tools such as OncoKB and cBioPortal for Cancer Genomics. CONCLUSION: OncoTree is a dynamic and flexible community-driven cancer classification platform encompassing rare and common cancers that provides clinically relevant and appropriately granular cancer classification for clinical decision support systems and oncology research.
PURPOSE: Cancer classification is foundational for patient care and oncology research. Systems such as International Classification of Diseases for Oncology (ICD-O), Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), and National Cancer Institute Thesaurus (NCIt) provide large sets of cancer classification terminologies but they lack a dynamic modernized cancer classification platform that addresses the fast-evolving needs in clinical reporting of genomic sequencing results and associated oncology research. METHODS: To meet these needs, we have developed OncoTree, an open-source cancer classification system. It is maintained by a cross-institutional committee of oncologists, pathologists, scientists, and engineers, accessible via an open-source Web user interface and an application programming interface. RESULTS: OncoTree currently includes 868 tumor types across 32 organ sites. OncoTree has been adopted as the tumor classification system for American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE), a large genomic and clinical data-sharing consortium, and for clinical molecular testing efforts at Memorial Sloan Kettering Cancer Center and Dana-Farber Cancer Institute. It is also used by precision oncology tools such as OncoKB and cBioPortal for Cancer Genomics. CONCLUSION: OncoTree is a dynamic and flexible community-driven cancer classification platform encompassing rare and common cancers that provides clinically relevant and appropriately granular cancer classification for clinical decision support systems and oncology research.
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Authors: Brendan Reardon; Nathanael D Moore; Nicholas S Moore; Eric Kofman; Saud H AlDubayan; Alexander T M Cheung; Jake Conway; Haitham Elmarakeby; Alma Imamovic; Sophia C Kamran; Tanya Keenan; Daniel Keliher; David J Konieczkowski; David Liu; Kent W Mouw; Jihye Park; Natalie I Vokes; Felix Dietlein; Eliezer M Van Allen Journal: Nat Cancer Date: 2021-09-30
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