1277P - Optimising targeted therapy in NSCLC: A comprehensive analysis of oncogenic fusion mutations and co-mutation landscapes

Background

In non-small cell lung cancer (NSCLC), the presence of fusion mutations in driver genes was linked to heightened malignancy. However, the therapeutic outcomes of different oncogenic fusions vary considerably, likely influenced by distinct co-mutation profiles within the fusion mutations. Therefore, a thorough analysis of the genetic landscape associated with various oncogenic fusions yielded critical insights, potentially guiding more effective treatment approaches.

Methods

A total of 1565 NSCLC patient samples confirmed to have pathogenic fusion mutations through Next-Generation Sequencing (NGS) testing (on a 733-gene tissue/ liquid biopsy panel) were used in this study for analysis. This includes 1125 tumor tissue samples and their corresponding blood samples, in addition to 440 standalone blood samples. Tumor Mutational Burden (TMB) was defined as the total number of somatic non-synonymous mutations in the coding region.

Results

In a cohort of 1565 NSCLC patients with pathogenic fusions, the median age was 42, evenly split by gender. Lung adenocarcinoma (92%) was most common, followed by lung squamous cell carcinoma (7%) and adenosquamous carcinoma (1%). Key fusions included ALK (39.6%), RET (12.8%), ROS1 (9.2%,), FGFR1-3 (3.9%), NTRK1-3 (1.79%), NRG1 (1.3%), with EGFR and BRAF fusions at 2.56% and 1.79%, respectively. Significant TMB differences were observed across fusions, with FGFR1-3 showing the highest TMB (10.82 Muts/Mb) and NRG1 the lowest (3.72 Muts/Mb).TP53 co-mutation rates varied, being highest in EGFR, BRAF, and FGFR1-3 fusions (78-64%) and lower in ALK and ROS1 (28-9%).Co-mutation profiles varied among fusion types in NSCLC. ALK and ROS1 showed lower co-mutation rates, mainly with CDKN2A and CDKN2B. FGFR1-3, NTRK1-3, and BRAF fusions frequently co-mutated with EGFR and PIK3CA, suggesting similarities to EGFR secondary mutations. RET fusions had fewer co-mutations, primarily with MDM2, FRS2, and MYC. NRG1 presented a balanced co-mutation spectrum, notably with EGFR and CDKN2B.

Conclusions

This study highlights the diversity in fusion mutations, underscoring the importance of personalized treatments guided by genetic profiling to enhance therapy effectiveness and patient outcomes.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

D. Zhang: Financial Interests, Personal, Full or part-time Employment: 3D Medicines Inc. All other authors have declared no conflicts of interest.