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.

Department of Biochemistry Faculty of Science Masaryk University Kamenice 753 5 625 00 Brno Czechia

Department of Biology Faculty of Medicine and Central European Institute of Technology Masaryk University Kamenice 753 5 625 00 Brno Czechia

Department of Oncological Pathology Masaryk Memorial Cancer Institute Žlutý kopec 543 7 656 53 Brno Czechia

Department of Pediatric Oncology University Hospital Brno and Faculty of Medicine Masaryk University Jihlavská 20 625 00 Brno Czechia

See more in PubMed

Panditharatna E., Filbin M.G. The growing role of epigenetics in childhood cancers. Curr. Opin. Pediatr. 2020;32(1):67–75. doi: 10.1097/MOP.0000000000000867. PubMed DOI

Louis D.N., et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro-Oncology. 2021;23(8):1231–1251. doi: 10.1093/neuonc/noab106. PubMed DOI PMC

Capper D., et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018;555(7697) doi: 10.1038/nature26000. Art. no. 7697. PubMed DOI PMC

Koelsche C., et al. Sarcoma classification by DNA methylation profiling. Nat. Commun. 2021;12(1):498. doi: 10.1038/s41467-020-20603-4. PubMed DOI PMC

Pidsley R., et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome Biol. 2016;17(1):208. doi: 10.1186/s13059-016-1066-1. PubMed DOI PMC

Yuan D., et al. crossNN: an explainable framework for cross-platform DNA methylation-based classification of cancer. medRxiv. 2024 doi: 10.1101/2024.01.22.24301523. DOI

“Dataset of DNA methylation profiles of 189 pediatric central nervous system, soft tissue, and bone tumors - EGA European Genome-Phenome Archive.” Accessed: January 26, 2024. [Online]. Available: https://ega-archive.org/studies/EGAS50000000051.

S. Andrews, “FastQC: a quality control tool for high throughput sequence data,” 2010, Accessed: December 28, 2022. [Online]. Available: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.

F. Krueger, “Trim Galore! A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files, with extra functionality for RRBS data.,” https://www.bioinformatics.babraham.ac.uk/projects/trim_galore. 2012. [Online]. Available: https://github.com/FelixKrueger/TrimGalore.

Krueger F., Andrews S.R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics. 2011;27(11):1571–1572. doi: 10.1093/bioinformatics/btr167. PubMed DOI PMC