Enrichment of SMARCA4 mutations in lung carcinomas presenting as cancer of unknown primary.
Summary
This study investigates a simplified approach to identify lung origin in cancers of unknown primary (CUP). Researchers found that the presence of SMARCA4 mutations, combined with a history of smoking, is strongly associated with lung-origin CUP (CUP-Lung). This combination offers a 76% probability of lung origin, even without detectable pulmonary involvement. This method could serve as a surrogate for whole-genome sequencing (WGS) to guide organ-directed treatments.
Analysis
Clinique: This retrospective study proposes a predictive biomarker for identifying the lung origin of cancers of unknown primary (CUP). The combination of a SMARCA4 mutation (OR 10.3, 95% CI 4.5-23.8, p < 0.001) and a smoking history (OR 4.9, 95% CI 2.2-10.9, p < 0.001) independently predicts a lung origin with a 76% probability. This could justify a change in practice by enabling organ-directed treatments even without WGS, with a potential clinical impact within 1-3 years for centers lacking WGS capabilities. Biomol: The key discovery is the significant enrichment of SMARCA4 mutations in lung-origin CUP (36.2%) compared to other CUPs (10.7%) and general lung cancers (6-8%). The study used WGS for tissue-of-origin prediction as a reference, then explored this low-complexity biomarker. CUP-Lung cases also exhibited higher tumor mutational burden (TMB) and enriched smoking-related mutational signatures. This finding could lead to the development of a clinical test based on targeted sequencing panels or SMARCA4 mutation detection methods, validating a biomarker for diagnostic guidance. Bioinfo: The study leverages WGS-based tissue-of-origin prediction as the reference method to identify CUP-Lung cases. It then proposes a "low-complexity surrogate" (SMARCA4 mutations + smoking history) for situations where WGS is unavailable. While not introducing a novel algorithm, the underlying bioinformatic approach for WGS-based TOO prediction is implied. The development of this surrogate aims to improve diagnostic workflows in centers without WGS access, providing an alternative based on more readily available clinical and molecular data.