Genetic testing is now a central part of the oncology workflow, with germline and somatic results contributing to both risk assessment and treatment selection.1 In diseases such as breast, colorectal, prostate, and pancreatic cancer, paired tumor-germline analysis improves the accuracy of inherited risk evaluation and may identify additional therapeutic targets.1
However, the clinical utility of multigene testing panels depends on the validity of gene-disease associations. Larger panels may include genes with limited or uncertain clinical validity, increasing the likelihood of variants of uncertain significance (VUS), which can lead to misinterpretation and overtreatment. As a result, some providers prefer smaller, more focused panels to minimize these risks.1,2 Longitudinal data show that genes with definitive evidence contribute the most to diagnostic yield, while those with limited evidence add little and may increase the burden of VUS findings.1,2 Clinical teams must weigh these factors when interpreting reports or selecting panels.
Recent studies also underscore the importance of pharmacogenomic data, often underutilized in oncology.3 Variants that affect drug metabolism and toxicity are identifiable in routine exome sequencing and can be extracted using validated informatics pipelines with high accuracy.3 When incorporated into clinical decision-making, these variants may help reduce treatment-related toxicity and optimize supportive care. Although the cost of analyzing and confirming actionable pharmacogenomic findings is relatively modest, confirmatory testing introduces further expense for the patient. Providers must weight these financial considerations when discussing the utility of such testing, particularly in the context of shared decision-making.3
As professional guidelines evolve and molecular testing becomes more embedded in clinical workflows, oncology teams must stay informed about the interpretive limitations of emerging biomarkers and the downstream implications of genomic findings.
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