Table 5_Methylation and gene expression patterns in adamantinomatous craniopharyngioma highlight a panel of genes associated with disease progression-free survival.xlsx

IntroductionOver the past decade, advancements in next-generation sequencing have significantly enhanced our understanding of the molecular pathogenesis of adamantinomatous craniopharyngiomas (ACP).
ObjectiveThis study integrated methylome and transcriptome analyses in ACP samples to explore the potential interplay between DNA methylation and RNA expression signatures for diagnostic and prognostic applications in ACP patients.
MethodsThis cross-sectional study evaluated clinicopathological features, DNA methylation, and gene expression profiles in 15 patients with ACP (33% women, age range: 3–55 years, 53% diagnosed before 18 years) treated at Ribeirao Preto Medical School, University of São Paulo.
ResultsMultidimensional scaling and principal component analysis identified two distinct clusters (ACP-A: n=9, ACP-B: n=6) with consistent composition across DNA methylation and gene expression profiles. While most clinical and histopathological characteristics were similar between clusters, ACP-A exhibited a longer median progression-free survival. ACP-B showed a higher prevalence of hypomethylated probes in CGI sites, and 63% of differentially methylated positions (DMPs) located in gene body regions. Differential methylation patterns were categorized into Methyl-Set1 (hypomethylated in ACP-A and hypermethylated in ACP-B) and Methyl-Set2 (hypermethylated in ACP-A and hypomethylated in ACP-B). Clustering analyses based on the methylation levels of probes and expression levels of the stringently filtered 212- and 37-gene sets further confirmed these two distinct ACP subgroups. Functional enrichment analysis highlighted key roles in synaptic modulation, nervous system development, cell adhesion, as well as pathways linked to RAS signaling, GTPase activity, and membrane potential regulation.
ConclusionAlthough clinical characteristics were largely comparable between the clusters, ACP-B patients exhibited shorter median progression-free survival, suggesting a more aggressive phenotype. The higher prevalence of hypomethylation in ACP-B indicates increased transcriptional activation, potentially driving tumor aggressiveness. The strong concordance between methylation and transcriptomic data in the 212- and 37-gene sets underscores their potential as a clinically relevant molecular biomarker panel. These gene sets demonstrate robustness in distinguishing ACP clusters, making it a promising tool for clinical sample classification.