OncoTree: A Cancer Classification System for Precision Oncology

Area of Science:

• Oncology
• Bioinformatics
• Genomics

Background:

• Existing cancer classification systems like ICD-O, SNOMED-CT, and NCIt lack dynamic modernization for genomic data.
• There is a need for a flexible platform to classify cancers, especially with evolving genomic sequencing results.

Purpose of the Study:

• To develop and introduce OncoTree, an open-source, dynamic cancer classification system.
• To address the limitations of current terminologies in handling modern oncology data.

Main Methods:

• Developed OncoTree as an open-source system with a web interface and API.
• Maintained by a cross-institutional committee of experts.

Main Results:

• OncoTree includes 868 tumor types across 32 organ sites.
• Adopted by AACR Project GENIE, Memorial Sloan Kettering, and Dana-Farber for clinical molecular testing.
• Integrated into precision oncology tools like OncoKB and cBioPortal.

Conclusions:

• OncoTree provides a dynamic, flexible, and community-driven cancer classification.
• It offers clinically relevant granularity for decision support and research.
• Encompasses rare and common cancers for broad applicability.