INTRODUCTION

, , and gene fusions are rare oncogenic driver alterations found in diverse tumor types of adults and children. They are clinically important biomarkers as tumors harboring these genomic alterations have high response rates to targeted therapy. Routine testing for fusions and treatment with TRK inhibitors has been recommended in multiple tumor types; however, differences between testing technologies used for detecting fusions can result in variable likelihoods of identification.

METHODS

To assess the prevalence of fusions in a real-world standard-of-care setting, we analyzed data from 19,591 FFPE samples encompassing 35 solid tumor types submitted for comprehensive genomic profiling (CGP) as part of routine clinical care. CGP testing included DNA hybrid-capture sequencing to detect small variants, copy number alterations, microsatellite instability (MSI), and tumor mutational burden (TMB). RNA hybrid-capture sequencing was concurrently performed to detect fusions and splice variants. Detected fusions were categorized as oncogenic, likely oncogenic, or variant of unknown significance (VUS) based on the fusion partner, orientation, and breakpoint position.

RESULTS

73 oncogenic or likely oncogenic fusions were identified in 69 unique tumor specimens across 19 tumor types for a total cohort prevalence of 0.35%. Tumor types with the highest fusion prevalence included glioblastoma (1.91%), small intestine (1.32%), and head and neck (0.95%) tumors with other solid tumor types ranging from 0.19% (uterine) to 0.63% (breast). We identified diverse intra and inter-chromosomal partner genes for fusions across all tumor types. Most fusions were detected in only one tumor specimen, though some recurrent fusions were noted with , , , , , , , and fusion partners. Most fusions were mutually exclusive from other genomic driver alterations, however, almost a third of tumor specimens (29%) contained at least one co-occurring genomic driver, which may affect treatment decisions.

DISCUSSION

The high prevalence of oncogenic and likely oncogenic fusions detected in our analysis suggests that RNA hybrid-capture-based sequencing for fusion detection is a highly sensitive method for identifying clinically meaningful known and novel fusions, which may be missed with other detection methods, directly impacting therapeutic options and patient outcomes.