PATH-12. A new powerful tool to simultaneously deliver DNA methylation profile and driver fusions detection based on Nanopore Sequencing

Nom de la revue
Mathilde Filser, Abderaouf Hamza, Elodie Girard, Nicolas Servant, Victor Renault, Kevin Merchadou, Christine Bourneix, Pascale Varlet, Emmanuelle Uro-Coste, Arnault Tauziède-Espariat, Francois Doz, Franck Bourdeaut, Olivier Delattre, Julien Masliah-Planchon

The fast advances in molecular biology have led to the discovery of new genetic and epigenetic driver events that play a key role in the pathogenesis of central nervous system (CNS) tumors. These data showed the importance of molecular biology, and in particular methylation profiling and fusion detection, to complete the histological examination. Exploring all these complex genomic and epigenomic alterations with the technologies implemented in the routine diagnosis requires massive laboratory equipment. In addition, it could take weeks before getting data that could be important to adapt the diagnosis, prognosis, and to ultimately guide the treatment’s choice. We describe the innovative potential of a nanopore sequencing device to obtain fast and multiple information to characterize CNS tumors. Adaptive-sampling is a software-controlled enrichment unique method that allows simultaneous methylation profiling, copy number landscape assessment, and fusion gene detection. Thereby, this technology brings comprehensive molecular information that could be very important for CNS tumor classification in a very short delay (below one week) and with a relative low cost compared to the combined other molecular analysis needed to get the same information. We report ten cases of diverse CNS tumors with already known oncogenic structural variants such as YAP1-MAMLD1 fused ependymoma, CNS neuroblastoma with FOXR2 activation, CNS high-grade neuroepithelial tumor with BCOR and MEN1 alteration, and atypical teratoid rhabdoid tumors (ATRT). For these tumors, using adaptive sampling with the nanopore sequencing, we were able to detect fusion genes as driver events, while obtaining at the same time the methylation profile to corroborate the tumor classification. Our results with this combined approach, never described before, demonstrate its feasibility as a new extremely powerful tool and show remarkable perspectives for this technology to bring a fast and comprehensive tumor molecular characterization.