Page 68 - Molecular features of low-grade developmental brain tumours

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(TSS200, TSS1500, 5’UTR and Exon 1) with a benjamini-Hochberg adjusted p-value<0.01 and a β-value difference of >0.2 were considered differentially methylated. Gene ontology (GO) analysis was performed using the R package clusterProfiler 37. In order to identify mTOR pathway methylation changes the mTOR pathway or mTORC1 signaling pathway genelist from the Reactome database was extracted 38,39. CpGs mapping to these genes with a benjamini-Hochberg adjusted p-value<0.01 and a β-value difference of >0.2 were considered differentially methylated.
Immunohistochemistry
Immunohistochemical staining was performed on 42 SEGAs and 8 controls with a Ventana semiautomated staining machine (Benchmark ULTRA; Ventana, Illkirch, France) and the Ventana DAB staining system according to the manufacturer’s protocol. The following antibodies have been used: glial fibrillary acidic protein (GFAP; polyclonal rabbit, DAKO, Glostrup, Denmark; 1:4000; monoclonal mouse; DAKO; 1:50), microtubule-associated protein (MAP2; mouse clone HM2; Sigma 1:100), human leukocyte antigen class II (HLA- DP, DQ, DR; mouse clone CR3/43; DAKO; 1:100), cluster of differentiation 3 (CD3; mouse monoclonal, clone F7.2.38; DAKO; 1:200; T-lymphocytes), phospho-S6 ribosomal protein (pS6 Ser235/236; rabbit polyclonal, Cell Signaling Technology, Beverly, MA, USA; 1:50).
Statistical analysis
Statistical analysis was performed with GraphPad Prism software (Graphpad software Inc., La Jolla, CA) using the nonparametric Mann-Whitney U-test or, for multiple groups, the non- parametric Kruskal-Wallis test followed by Mann-Whitney U-test. Correlations were assessed with R using the Spearman’s rank correlation test. An adjusted P-value< 0.05 was considered statistically significant except for the differentially methylation analysis where an adjusted P-value< 0.01 was considered statistically significant.
Figure 1. The methylation profile of SEGAs. a. A principal component analysis (PCA) of the methylation data in SEGA (n=42) and periventricular control tissue (n=8) showing that the major source of variability in CpG methylation is the diagnosis. X-axis: the first principal component (PC); y-axis: the second PC. b. Spearman’s rank correlation matrix of the methylation data showing separate clustering of SEGAs from periventricular control tissue. The scale bar indicates the strength of the correlation with 1 indicating a strong positive correlation (dark blue) and -1 indicating a negative correlation (dark red) between samples. c. Pie charts showing the distribution of CpGs on the gene region (TSS200, TSS1500, 5’UTR and Exon 1, IGR, 3’UTR or gene body). The upper pie chart shows the distribution for 421,352 CpGs selected after filtering for probes with a detection p-values of more than 0.01, located on the sex chromosomes, or in SNPs were removed as well as cross-hybridization probes. The lower pie chart shows the gene distribution after selecting for an adjusted p-value<0.01 and a β-value difference of >0.2. d. Volcano plot showing the differentially methylated CpGs on the promoter region (adjusted p-value<0.01 and a β-value difference of >0.2) between SEGAs and control tissue. A total of 4616 CpGs were hypomethylated and 2526 were hypermethylated in SEGA compared to control tissue. e. Schematic overview using Cytoscape of GO terms enriched in SEGA compared to control tissue (adjusted p-value<0.02). Lines indicate genes in common between GO terms. f. Graphical representation of hypermethylated (red) and hypomethylated (blue) in the top 50 GO terms.