Low incidence and molecular heterogeneity of pediatric T-cell lymphoblastic lymphoma (T-LBL) require an international, large-scale effort to identify novel clinical biomarkers. The ongoing international clinical trial LBL2018 (NCT04043494) represents an ideal opportunity to implement a common analytic approach. Targeted next-generation sequencing is well-suited for this purpose; however, selection of relevant target genes for T-LBL remains subject of ongoing debates. Our group has recently designed and evaluated a first target panel of 80 candidate genes for T-LBL. The present study aimed at developing a novel optimized gene panel for large-scale application and to promote an international agreement on a common core panel. Small sequence variants obtained from our former study were systematically analyzed and classified with regards to pathogenic relevance, to prioritize candidate genes. Additional genes were curated from literature and online databases for a more comprehensive analysis of relevant functions and signaling pathways. The new target panel TGP-T-LBL entails 84 candidate genes which are key actors in NOTCH, PI3K-AKT, JAK–STAT, RAS signaling, epigenetic regulation, transcription, DNA repair, cell cycle regulation, and ribosomal function. From our former gene panel, 35 out of 80 candidate genes were selected for the novel panel. Forty-six out of 84 genes are currently being analyzed in the ongoing international trial LBL2018. Exploratory analysis of prognostic relevance on mutation-level suggested a potential association of PIK3CA variants c.1624G>A(p.Glu542Lys) and c.1633G>A(p.Glu545Lys) to occurrence of relapse, emphasizing particular relevance of mutation analysis in PI3K-AKT signaling. Our approach promotes comprehensive and clinically relevant mutational profiling of pediatric T-LBL.
CITATION STYLE
Ruether, C., Wuensch, C., Randau, G., Michgehl, U., Trautmann, M., Hartmann, W., … Burkhardt, B. (2022). Design of a targeted next-generation DNA sequencing panel for pediatric T-cell lymphoblastic lymphoma to unravel biology and optimize treatment. Genes Chromosomes and Cancer, 61(8), 459–470. https://doi.org/10.1002/gcc.23037
Mendeley helps you to discover research relevant for your work.