Background: Genomic fusions are potent oncogenic drivers across cancer types and many are targetable. We demonstrate the clinical performance of DNA-based comprehensive genomic profiling (CGP) for detecting targetable fusions.
Materials and methods: We analyzed targetable fusion genes in >450 000 tissue specimens profiled using DNA CGP (FoundationOne CDx, FoundationOne). Using a de-identified nationwide (US-based) non-small cell lung cancer (NSCLC) clinico-genomic database, we assessed outcomes in patients with nonsquamous NSCLC (NonSqNSCLC) who received matched therapy based on a fusion identified using DNA CGP. Lastly, we modeled the added value of RNA CGP for fusion detection in NonSqNSCLC.
Results: We observed a broad diversity of fusion partners detected with DNA CGP in conjunction with targetable fusion genes (ALK, BRAF, FGFR2, FGFR3, NTRK1/2/3, RET, and ROS1). In NonSqNSCLC with oncogenic ALK, NTRK, RET, and ROS1 fusions detected by DNA CGP, patients treated with a matched tyrosine kinase inhibitor had better real-world progression-free survival than those receiving alternative treatment regimens and benefit was observed regardless of the results of orthogonal fusion testing. An estimated 1.3% of patients with NonSqNSCLC were predicted to have an oncogenic driver fusion identified by RNA, but not DNA CGP, according to a model that accounts for multiple real-world factors.
Conclusion: A well-designed DNA CGP assay is capable of robust fusion detection and these fusion calls are reliable for informing clinical decision-making. While DNA CGP detects most driver fusions, the clinical impact of fusion detection is substantial for individual patients and exhaustive efforts, inclusive of additional RNA-based testing, should be considered when an oncogenic driver is not clearly identified.
Keywords: DNA sequencing; RNA sequencing; gene fusion; lung cancer; next-generation sequencing.
© The Author(s) 2024. Published by Oxford University Press.