Dataset of DNA methylation profiles of 189 pediatric central nervous system, soft tissue, and bone tumors.

Alterations in DNA methylation profiles belong to important mechanisms in cancer development, and their assessment can be utilized for rapid and precise diagnostics. Therefore, establishing datasets of methylation profiles can improve and deepen our understanding of the role of epigenetic changes in cancer development as well as improve our diagnostic capabilities. In this dataset, we generated NGS data for 189 samples of pediatric CNS, soft tissue, and bone tumors. The sequencing libraries were prepared using methyl capture bisulfite sequencing, an effective compromise between whole-genome bisulfite sequencing and array-based methods with a more limited scope of target regions. The larger part of the cohort was processed with the Agilent SureSelectXT Human Methyl-Seq kit (149 samples) and the rest with the Illumina TruSeq Methyl Capture EPIC Library Prep Kit (40 samples). The data presented in this article may help other researchers further elucidate the importance of methylation in diagnosing pediatric CNS tumors, soft tissue, and bone tumors.

Assessment of Tumor Mutational Burden in Pediatric Tumors by Real-Life Whole-Exome Sequencing and In Silico Simulation of Targeted Gene Panels: How the Choice of Method Could Affect the Clinical Decision?

BACKGROUND: Tumor mutational burden (TMB) is an emerging genomic biomarker in cancer that has been associated with improved response to immune checkpoint inhibitors (ICIs) in adult cancers. It was described that variability in TMB assessment is introduced by different laboratory techniques and various settings of bioinformatic pipelines. In pediatric oncology, no study has been published describing this variability so far. METHODS: In our study, we performed whole exome sequencing (WES, both germline and somatic) and calculated TMB in 106 patients with high-risk/recurrent pediatric solid tumors of 28 distinct cancer types. Subsequently, we used WES data for TMB calculation using an in silico approach simulating two The Food and Drug Administration (FDA)-approved/authorized comprehensive genomic panels for cancer. RESULTS: We describe a strong correlation between WES-based and panel-based TMBs; however, we show that this high correlation is significantly affected by inclusion of only a few hypermutated cases. In the series of nine cases, we determined TMB in two sequentially collected tumor tissue specimens and observed an increase in TMB along with tumor progression. Furthermore, we evaluated the extent to which potential ICI indication could be affected by variability in techniques and bioinformatic pipelines used for TMB assessment. We confirmed that this technological variability could significantly affect ICI indication in pediatric cancer patients; however, this significance decreases with the increasing cut-off values. CONCLUSIONS: For the first time in pediatric oncology, we assessed the reliability of TMB estimation across multiple pediatric cancer types using real-life WES and in silico analysis of two major targeted gene panels and confirmed a significant technological variability to be introduced by different laboratory techniques and various settings of bioinformatic pipelines.