The tool, CancerVar, combines Python, a command line software, and deep learning to generate automated descriptive interpretations for cancer mutations to determine whether the mutation is relevant for diagnosis, prognosis or to an ongoing clinical trial, according to a May 6 press release.
“CancerVar will not replace human interpretation in a clinical setting, but it will significantly reduce the manual work of human reviewers in classifying variants identified through sequencing and drafting clinical reports in the practice of precision oncology,” said Kai Wang, PhD, professor of pathology and laboratory medicine at Children’s Hospital of Philadelphia. “CancerVar documents and harmonizes various types of clinical evidence including drug information, publications, and pathways for somatic mutations in detail. By providing standardized, reproducible, and precise output for interpreting somatic variants, CancerVar can help researchers and clinicians prioritize mutations of concern.”
Currently, the CancerVar web server includes clinical evidence for 13 million somatic cancer variants from 1,911 cancer census genes that were obtained through existing studies and databases.
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