  With the rapid advancements in cancer research, the information that is
useful for characterizing disease, staging tumors, and creating treatment and
survivorship plans has been changing at a pace that creates challenges when
physicians try to remain current. One example involves increasing usage of
biomarkers when characterizing the pathologic prognostic stage of a breast
tumor. We present our semantic technology approach to support cancer
characterization and demonstrate it in our end-to-end prototype system that
collects the newest breast cancer staging criteria from authoritative oncology
manuals to construct an ontology for breast cancer. Using a tool we developed
that utilizes this ontology, physician-facing applications can be used to
quickly stage a new patient to support identifying risks, treatment options,
and monitoring plans based on authoritative and best practice guidelines.
Physicians can also re-stage existing patients or patient populations, allowing
them to find patients whose stage has changed in a given patient cohort. As new
guidelines emerge, using our proposed mechanism, which is grounded by semantic
technologies for ingesting new data from staging manuals, we have created an
enriched cancer staging ontology that integrates relevant data from several
sources with very little human intervention.
