Routine RNA sequencing of formalin-fixed paraffin-embedded specimens in neuropathology diagnostics identifies diagnostically and therapeutically relevant gene fusions - Stichel, Damian; Schrimpf, Daniel; Casalini, Belén; Wefers, Annika K.; Sievers, Philipp; Kölsche, Christian; Reuss, David; Reinhardt, Annekathrin; Fernández Klett, Francisco; Keßler, Tobias; Sturm, Dominik; Ecker, Jonas; et al. (Acta neuropathologica, 2019)
Molecular markers have become pivotal in brain tumor diagnostics. Mutational analyses by targeted next-generation sequencing of DNA and array-based DNA methylation assessment with copy number analyses are increasingly being used in routine diagnostics. However, the broad variety of gene fusions occurring in brain tumors is marginally covered by these technologies and often only assessed by targeted assays. Here, we assessed the feasibility and clinical value of investigating gene fusions in formalin-fixed paraffin-embedded (FFPE) tumor tissues by next-generation mRNA sequencing in a routine diagnostic setting. After establishment and optimization of a workflow applicable in a routine setting, prospective diagnostic application in a neuropathology department for 26 months yielded relevant fusions in 66 out of 101 (65%) analyzed cases. In 43 (43%) cases, the fusions were of decisive diagnostic relevance and in 40 (40%) cases the fusion genes rendered a druggable target. A major strength of this approach was its ability to detect fusions beyond the canonical alterations for a given entity, and the unbiased search for any fusion event in cases with uncertain diagnosis and, thus, uncertain spectrum of expected fusions. This included both rare variants of established fusions which had evaded prior targeted analyses as well as the detection of previously unreported fusion events. While the impact of fusion detection on diagnostics is highly relevant, it is especially the detection of “druggable” fusions which will most likely provide direct benefit to the patients. The wider application of this approach for unbiased fusion identification therefore promises to be a major advance in identifying alterations with immediate impact on patient care.