Optimized precision oncology through implementation of a comprehensive molecular analysis pipeline - relevance for additional therapeutic options.
Summary
This study investigated the impact of next-generation sequencing (NGS) panel size on therapeutic recommendations in precision oncology. Comparing a 430-gene panel to a smaller 185-gene panel in 281 patients, researchers found molecular alterations in nearly all tumors. While most stratified therapy recommendations were achievable with the smaller panel, the expanded panel enabled additional recommendations for 8.8% of patients and identified actionable variants in five extra genes. The study emphasizes the necessity of sufficient genomic coverage for reliable tumor mutational burden (TMB) calculation, thereby establishing a minimal standard for genomic cancer care.
Analysis
This retrospective study of 281 consecutive patients evaluates the clinical impact of different NGS panel sizes on therapeutic recommendations in molecular tumor boards (MTB). It shows that 60.5% of patients received a molecular-stratified therapy recommendation, with 8.8% of these recommendations depending on the expanded panel. High TMB, reliably calculated with sufficient genomic coverage, enabled 4.1% of MTB recommendations. These findings suggest that larger panels can refine therapeutic options for a minority of patients, potentially justifying their use for better stratification, although the impact on clinical trials or widespread practice changes remains to be fully assessed. Time to clinical impact could be 3-5 years for broader adoption. The study utilized DNA NGS panels (430 genes, 1.3 Mb vs 185 genes, 618 kb) combined with an RNA-fusion panel to detect oncogenic variants and gene fusions. It discovered that the expanded panel identified actionable variants in five additional genes not covered by the smaller panel. NGS technology is validated for detecting these alterations. The study highlights the importance of genomic coverage for the reliability of TMB calculation, a potential predictive biomarker. Tumor samples were analyzed, with implications for future clinical tests that may require larger panels for comprehensive molecular characterization.