Analytical Performance of the EasyPGX Ready NTRK Fusion Assay for Detecting Tumor-Agnostic NTRK Gene Fusions in Solid Tumors

Early detection and accurate characterization of pathogenic NTRK1, NTRK2, and NTRK3 gene rearrangements have become essential components of multimodal testing frameworks to select gene fusion-positive candidates for NTRK-directed molecularly targeted therapies. This retrospective study presents the first independent validation of the CE-IVD-compliant EasyPGX ready NTRK Fusion assay, a ready-to-use RT-PCR workflow for the qualitative detection of NTRK1,2,3 gene fusions in solid tumors. Based on the fusion frequency in our institutional pathology cohort, the potential diagnostic coverage of the streamlined fast-track assay was 93.8% (15/16) for NTRK1, 100% (1/1) for NTRK2, and 58.8% (10/17) for NTRK3 rearrangement, including TPM3, LMNA, TPR, STRN, and ETV6 as 5′ fusion partners. Twenty-nine archived FFPE tumor specimens with known NTRK1,2,3 gene rearrangement status, and two multiplexed FFPE NTRK fusion reference standards were tested. Targeted RNA-based next-generation sequencing served as the diagnostic benchmark reference method. Conclusive results were obtained for all 31 RNA samples, including FFPE tumor specimens archived for up to six years. The observed overall sensitivity was 96% (23/24; 95% CI, 78.9–99.9%) and no false-positive results were observed for any of the nine gene fusion targets (observed specificity 100%); the single discordant result occurred in a fusion-positive sample with borderline transcript abundance at the lower limit of the assay’s dynamic range. Dilution experiments indicated valid detection at 6.25 ng RNA input per reaction for all fusion transcripts tested, with robust inter-run repeatability and no false-positive results. In this single-center study, the CE-IVD-compliant EasyPGX ready NTRK Fusion assay demonstrated analytical performance within its predefined repertoire of NTRK1,2,3 rearrangements, consistent with guideline thresholds, supporting its potential as a first-level fast-track component of multimodal pan-cancer diagnostic workflows.