ArticleMolecular diagnosis & therapy2026
Clinical Utility of an RNA-based Gene Fusion Assay in Sarcoma for Diagnosis and Management: Experience in an Australian Laboratory.
Article in Molecular diagnosis & therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSarcoma represents a diverse group of over 70 subtypes with overlapping morphological and immunophenotypic features, often leading to diagnostic uncertainty. Gene fusions are commonly associated with specific sarcoma subtypes and can aid in diagnosis and management. RNA-based next-generation sequencing (NGS) enables sensitive detection of gene fusions, particularly in cases with limited tissue or ambiguous histopathology.
methodsWe conducted a retrospective review of 124 patients with suspected sarcoma who underwent RNA-based NGS using the Illumina TruSight RNA Fusion Panel (TRFP) at a dedicated sarcoma centre between June 2020 and June 2023. The impact of fusion testing on diagnostic classification and treatment decisions was evaluated by expert pathologists and oncologists.
resultsGene fusions were detected in 75 of 124 cases (60%). Fusion results confirmed the initial diagnosis in 58 cases (47%) and altered the diagnosis in 17 cases (14%). In 14 cases (11%), findings directly influenced clinical management, including treatment de-escalation (nine cases) and initiation of targeted or alternative therapies (five cases). A definitive diagnosis was achieved in 59% of cases with limited tissue (41 of 70), 48% with uncertain tumour differentiation (25 of 52), and 43% with inconclusive or failed prior molecular testing (ten of 23), underscoring the utility of RNA-based NGS in diagnostically complex scenarios.
conclusionsRNA-based NGS fusion panels provide diagnostic and clinical utility in the evaluation of mesenchymal tumours. Their integration into routine diagnostic workflows improves diagnostic accuracy and informs personalised treatment decisions, especially in diagnostically complex or resource-limited settings.
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