Comparison of somatic variant oncogenicity classification using ClinGen/CGC/VICC guidelines and QIAGEN Clinical...

Area of Science:

• Genomic medicine
• Cancer genomics
• Clinical informatics

Background:

• Accurate clinical interpretation of somatic cancer variants is essential for diagnosis and precision oncology treatment.
• Increasing genomic sequencing depth and breadth led to independent laboratory standards for somatic variant classification.
• A collaborative set of standards was published by the Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC).

Purpose of the Study:

• To evaluate the ClinGen/CGC/VICC standards for somatic variant classification.
• To compare these standards against classifications from a clinical decision support software system (QIAGEN Clinical Insight - QCI Interpret One).
• To assess the concordance between automated and consensus-based somatic variant classifications.

Main Methods:

• Utilized a published variant set for validation.
• Expanded the dataset with real-world cancer variants from Mayo Clinic retrospective oncology cases.
• Compared classifications generated by the ClinGen/CGC/VICC system with those from the QCI Interpret One system.

Main Results:

• Automated classifications by the QCI system showed 97.2% concordance with ClinGen/CGC/VICC assessed classifications for "oncogenic" and "likely oncogenic" variants.
• The ClinGen/CGC/VICC standards resulted in more conservative classifications, with a higher proportion of variants designated as "variant of unknown significance" or "likely benign."
• Demonstrated effective combined use of guidelines and decision support tools.

Conclusions:

• The ClinGen/CGC/VICC guidelines provide a robust framework for somatic variant classification.
• Clinical decision support tools, like QCI Interpret One, can be effectively integrated with these guidelines.
• The combined approach facilitates accurate somatic variant classification and interpretation in clinical oncology settings.