Assessment of Exhaled Breath Condensate for ALK, RET, ROS1, and NTRK1 Fusion Transcript Detection in NSCLC: Comparison With Tissue and Liquid Biopsy Samples.

Background: Lung cancer continues to be the primary cause of cancer-related deaths globally, with the majority of cases identified at advanced stages. Genetic alterations, including mutations and gene fusions, are central to its molecular pathogenesis. The discovery of therapeutically targetable gene fusions, such as ALK, RET, ROS1, and NTRK1, has significantly advanced lung cancer management. Conventional methods, such as tissue biopsies, are invasive and unsuitable for continuous molecular monitoring. Consequently, noninvasive approaches, such as liquid biopsies and exhaled breath condensate (EBC), offer promising options for real-time molecular surveillance.

Methods: This study evaluates the feasibility of identifying fusion transcripts in 30 patients with lung adenocarcinoma by using next-generation sequencing (NGS) on formalin-fixed paraffin-embedded (FFPE) tissue, plasma, and EBC samples.

Results: Clinically significant fusion transcripts, including KIF5B-ALK, KIF5B-RET, and SQSTM1-ALK, were detected across different sample types. EBC samples showed strong concordance with tissue biopsy results, particularly in detecting ALK, ROS1, and RET fusions, and demonstrated greater sensitivity than plasma in detecting NTRK1 fusions. Additionally, 30 fusion transcripts of uncertain clinical significance were identified, highlighting the need for further research into their role in lung cancer pathogenesis.

Conclusion: In conclusion, EBC samples provide a valuable, noninvasive medium for detecting clinically relevant and previously uncharacterized fusion transcripts in non-small cell lung cancer (NSCLC). The high concordance between EBC and tissue biopsies suggests that EBC could complement tissue biopsy for effective diagnosis and monitoring of NSCLC. These findings underscore the importance of comprehensive molecular profiling using multiple sample types to enhance diagnostic precision and optimize therapeutic outcomes in lung cancer management.