AI Article Synopsis

  • The development of OncoTree addresses the shortcomings of existing cancer classification systems, such as ICD-O and SNOMED-CT, by providing a modern platform suited for genomic sequencing results and oncology research.
  • OncoTree is an open-source system supported by a collaborative team of experts and is accessible through a web interface and API, making it user-friendly for various stakeholders in oncology.
  • With 868 tumor types across 32 organ sites, OncoTree is already being used by prominent institutions like AACR and Memorial Sloan Kettering, proving its utility in clinical and research settings.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240791PMC
http://dx.doi.org/10.1200/CCI.20.00108DOI Listing

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