OncoTree: A Cancer Classification System for Precision Oncology

Ritika Kundra, Hongxin Zhang, Robert Sheridan, Sahussapont Joseph Sirintrapun, Avery Wang, Angelica Ochoa, Manda Wilson, Benjamin Gross, Yichao Sun, Ramyasree Madupuri, Baby A. Satravada, Dalicia Reales, Efsevia Vakiani, Hikmat A. Al-Ahmadie, Ahmet Dogan, Maria Arcila, Ahmet Zehir, Steven Maron, Michael F. Berger, Cristina ViaplanaKatherine Janeway, Matthew Ducar, Lynette Sholl, Snjezana Dogan, Philippe Bedard, Lea F. Surrey, Iker Huerga Sanchez, Aijaz Syed, Anoop Balakrishnan Rema, Debyani Chakravarty, Sarah Suehnholz, Moriah Nissan, Gopakumar V. Iyer, Rajmohan Murali, Nancy Bouvier, Robert A. Soslow, David Hyman, Anas Younes, Andrew Intlekofer, James J. Harding, Richard D. Carvajal, Paul J. Sabbatini, Ghassan K. Abou-Alfa, Luc Morris, Yelena Y. Janjigian, Meighan M. Gallagher, Tara A. Soumerai, Ingo K. Mellinghoff, Abraham A. Hakimi, Matthew Fury, Jason T. Huse, Aditya Bagrodia, Meera Hameed, Stacy Thomas, Stuart Gardos, Ethan Cerami, Tali Mazor, Priti Kumari, Pichai Raman, Priyanka Shivdasani, Suzanne MacFarland, Scott Newman, Angela Waanders, Jianjiong Gao, David Solit, Nikolaus Schultz

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)221-230
Number of pages10
JournalJCO Clinical Cancer Informatics
Volume5
DOIs
StatePublished - Feb 1 2021
Externally publishedYes

ASJC Scopus subject areas

  • Oncology
  • Health Informatics
  • Cancer Research

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