LOGGIC Core BioClinical Data Bank: Added clinical value of RNA-Seq in an international molecular diagnostic registry for pediatric low-grade glioma patients
Emily C. Hardin, Simone Schmid, Alexander C. Sommerkamp, Carina Bodden, Anna-Elisa Heipertz, Philipp Sievers, Andrea Wittmann, Till Milde, Stefan M. Pfister, Andreas von Deimling, Svea Horn, Nina A. Herz, Michèle Simon, Ashwyn A Perera, Amedeo A. Azizi, Ofelia Cruz, Sarah Curry, An Van Damme, Miklós Garami, Darren Hargrave, Antonis Kattamis, Barbara Faganel Kotnik, Päivi M. Lähteenmäki, Katrin Scheinemann, Antoinette Y. N. Schouten‐van Meeteren, Astrid Sehested, Elisabetta Viscardi, Ole Mikal Wormdal, Michal Zápotocký, David S. Ziegler, Arend Koch, Pablo Hernáiz Driever, Olaf Witt, David Capper, Felix Sahm, David Jones, Cornelis M. van Tilburg
Abstract
BACKGROUND: The international, multicenter registry LOGGIC Core BioClinical Data Bank aims to enhance the understanding of tumor biology in pediatric low-grade glioma (pLGG) and provide clinical and molecular data to support treatment decisions and interventional trial participation. Hence, the question arises whether implementation of RNA sequencing (RNA-Seq) using fresh frozen (FrFr) tumor tissue in addition to gene panel and DNA methylation analysis improves diagnostic accuracy and provides additional clinical benefit. METHODS: Analysis of patients aged 0 to 21 years, enrolled in Germany between April 2019 and February 2021, and for whom FrFr tissue was available. Central reference histopathology, immunohistochemistry, 850k DNA methylation analysis, gene panel sequencing, and RNA-Seq were performed. RESULTS: FrFr tissue was available in 178/379 enrolled cases. RNA-Seq was performed on 125 of these samples. We confirmed KIAA1549::BRAF-fusion (n = 71), BRAF V600E-mutation (n = 12), and alterations in FGFR1 (n = 14) as the most frequent alterations, among other common molecular drivers (n = 12). N = 16 cases (13%) presented rare gene fusions (eg, TPM3::NTRK1, EWSR1::VGLL1, SH3PXD2A::HTRA1, PDGFB::LRP1, GOPC::ROS1). In n = 27 cases (22%), RNA-Seq detected a driver alteration not otherwise identified (22/27 actionable). The rate of driver alteration detection was hereby increased from 75% to 97%. Furthermore, FGFR1 internal tandem duplications (n = 6) were only detected by RNA-Seq using current bioinformatics pipelines, leading to a change in analysis protocols. CONCLUSIONS: The addition of RNA-Seq to current diagnostic methods improves diagnostic accuracy, making precision oncology treatments (MEKi/RAFi/ERKi/NTRKi/FGFRi/ROSi) more accessible. We propose to include RNA-Seq as part of routine diagnostics for all pLGG patients, especially when no common pLGG alteration was identified.