CpG hypermethylation and WNT/AP-1 cooperativity define the epigenetic landscape and a clinical subgroup of high-risk pediatric adrenocortical carcinoma

Figures

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  Fig. 1. DNA methylation–based stratification of pediatric adrenocortical tumors identifies four clinically distinct subgroups. A Overview of the project presented in this paper. Created in BioRender. Fincke, V. (2026) https://BioRender.com/5ujxlr5. B Unsupervised clustering of DNA methylation data using Consnsus Clustering identifies four molecular subgroups (Low Risk 1, Low Risk 2, Low Risk 3, and High Risk) in 214 pediatric ACTs. Red indicated samples always cluster together; blue color indicates samples never cluster together (total n = 214; HR, n = 36; LR1, n = 104; LR2, n = 34; LR3, n = 40). C UMAP projection of DNA methylation profiles colored by molecular subgroup (total n = 214; HR, n = 36; LR1, n = 104; LR2, n = 34; LR3, n = 40). D Kaplan–Meier analysis of overall survival across histopathological diagnoses (pACA, n = 82; pACC, n = 92; pUMP, n = 40; log-rank test). E Kaplan–Meier analysis of overall survival across methylation-based subgroups (HR, n = 36; LR1, n = 104; LR2, n = 34; LR3, n = 40; log-rank test). F COG/IPACTR stage at diagnosis across methylation-based subgroups (stage 1, n = 75; stage 2, n = 67; stage 3, n = 27; stage 4, n = 36; stage not available, n = 9;…

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  Fig. 2. High-risk pACTs exhibit enhanced CpG island methylation, genomic instability, and enriched TP53 mutations. A CpG island methylation levels (top 1% most variable probes) across pACT methylation subgroups (LR1, n = 104; LR2, n = 34; LR3, n = 40; HR, n = 36), adult adrenocortical carcinoma (ACC) CpG island methylator phenotype (CIMP) categories from the TCGA cohort (CIMP-high, n = 20; CIMP-intermediate, n = 27; CIMP-low, n = 32) and healthy adrenal cortex controls (n = 12); total n = 305. Violin plots show the kernel density distribution of the data; embedded box plots indicate the median (center line), the 25th and 75th percentiles (box bounds) and whiskers extending to the most extreme value within 1.5 × the interquartile range of the box, which define the plotted minima and maxima. Groups were compared by two-sided Kruskal–Wallis test, followed by two-sided Dunn’s post hoc tests with Benjamini–Hochberg correction across all 28 pairwise comparisons. Source data are provided with this paper. Adjusted p values: LR1 vs. LR2, p.adj = 1.5 × 10⁻⁸; LR1 vs. LR3, p.adj = 4.9 × 10⁻⁶; LR1 vs. HR, p.adj = 6.7 × 10⁻²⁵; LR1 vs. CIMP-high, p.adj = 5.0 × 10⁻²³; LR1 vs. CIMP-intermediate, p.adj =…

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  Fig. 3. Single-Nucleus RNA sequencing reveals adrenal zonation and cell type diversity across pACT zubgroups. A Clinical annotation of each sample, including risk group, gender, age category, clinical presentation, and survival status. B UMAP projection of snRNA-seq data from 18 pACT samples ((HR: 4 pACC; LR1: 4 pACC, 4 pACA; LR2: 1 pACC, 2 pACA, 1 pACx; LR3: 2 pACC)), colored by patient ID for n = 75,515 nuclei. C UMAP embedding of all cells (n = 75,515 cells, n = 18 samples) colored by inferred cell type identity, including glomerulosa-like, zF/zR-like Cluster I and II, macrophages, lymphoid cells, endothelial cells, fibroblasts, and cycling cells. D Expression of key adrenal steroidogenic genes across the UMAP space. Genes shown include DAB2, SYTL2, CYP11A1, CYP21A2, STAR, CYP17A1, CYP11B1, and HSD3B2. Diagram (center) summarizes the biosynthetic zonation of the adrenal cortex and corresponding gene functions. Created in BioRender. Fincke, V. (2026) https://BioRender.com/34flu07. E Pseudotime projection of tumor cells (n = 53,943 tumor cells, n = 18 samples), indicating a potential differentiation trajectory from glomerulosa-like cells toward zF/zR-like clusters. F Proportional…

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  Fig. 4. Transcriptional metasignatures reveal functional heterogeneity and differential WNT pathway engagement across pACT Subgroups. A Heatmap of pairwise correlations among seven transcriptional metasignatures derived from non-cycling tumor cells using non-negative matrix factorization (NMF) across 18 pACT samples. B Bar plots showing sample-level proportions of metasignature expression. Each bar represents one tumor sample, colored by metasignature contribution. C GO term enrichment analysis for Metasignature 4 (n = 30 genes), annotated as “Proliferative and Cell Cycle Activation,” showing top enriched pathways and gene counts. Enrichment was tested against the default genome-wide background of clusterProfiler using a one-sided hypergeometric test (clusterProfiler enrichGO), with p values adjusted for multiple comparisons by the Benjamini-Hochberg method. D Enrichment heatmap showing the prevalence of metasignatures in the tumor cell clusters in the molecular risk groups(HR: 4 pACC; LR1: 4 pACC, 4 pACA; LR2: 1 pACC, 2 pACA, 1 pACx; LR3: 2 pACC). E Dot plot showing ligand–receptor interactions inferred by LIANA across tumor clusters (zF/zR-like Cluster I n = 17,970 cells, zF/zR-like…

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  Fig. 5. Chromatin accessibility and transcription factor motif enrichment define subgroup-specific regulatory programs in pediatric ACT. A UMAP embedding of snRNA-Seq data from the validation cohort (n = 10 pACT samples, n = 50,988 nuclei), confirming cell type annotations observed in the primary cohort. Transitional cluster exhibiting features of both zG- and zF/zR-like tumor cells is highlighted. B Proportional distribution of metasignatures across DNA methylation–based risk groups in the original and validation cohort (VC). C Chromatin accessibility tracks from snATAC-Seq data showing elevated accessibility at the WNT5A locus (n = 7). D Pseudotime trajectory of tumor cell differentiation inferred from snRNA-Seq and snATAC-Seq integration, showing dynamic expression (right) and activity (left) of selected transcription factors, including TCF7L2 and members of the AP-1 complex (FOS, JUN, JUND) (n = 7). Created in BioRender. Fincke, V. (2026) https://BioRender.com/5kt1mj1. E Motif enrichment analysis based on Tn5 insertion frequency around TCF7L2 binding motifs. High Risk tumors exhibit the strongest enrichment at this CTNNB1-binding motif (n = 7). Equivalent figure for AP-1 is displayed…

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  Fig. 6. Spatial and epigenetic reprogramming define high-risk architecture and therapeutic vulnerabilities in pACT and ACC models. Spatial transcriptomic analysis of one representative tumor per DNA methylation-based subgroup using the Visium HD platform: A Low Risk 1, B Low Risk 2, C Low Risk 3, D High Risk. Cells were reconstructed from 2 µm bins with bin2cell and annotated by transferring the single-nucleus RNA-seq cluster labels with CellTypist. Cells analysed: Low Risk 1, n = 289,651 (tumor compartment 243,148, 83.9%); Low Risk 2, n = 140,105 (108,281, 77.3%); Low Risk 3, n = 99,273 (89,028, 89.7%); High Risk, n = 146,167 (67,396, 46.1%). The stacked bars show the cell type composition across all reconstructed cells (“all”) and across the tumor compartment only (“tumor only”). The Low Risk tumors (A–C) display a compartmentalised architecture, whereas the High Risk tumor (D) shows a disordered structure with an expanded stromal compartment. Insets show PROGENy-inferred WNT signaling activity for the boxed region on an identical color scale across all panels (−2 to 3), comprising 26,579 (A), 30,432 (B), 17,483 (C) and 19,975 (D) cells, respectively; the highest WNT activity was…

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  Fig. 7. Integrative summary of molecular and clinical features across pediatric ACT subgroups. Schematic overview of Low Risk 1, Low Risk 2, Low Risk 3, and High Risk DNA methylation-based subgroups, illustrating key differences in clinical outcomes and molecular phenotypes. From top to bottom: Kaplan-Meier survival curves highlighting subgroup-specific prognosis; age at diagnosis in years; frequency of germline TP53 mutations; degree of CpG island methylation; relative tumor cell heterogeneity derived from single-cell transcriptomics; AP-1 motif enrichment based on snATAC-Seq; WNT pathway activity and CTNNB1 localization. High Risk tumors are defined by poor survival, high CpG island methylation, TP53 alterations, increased transcriptional heterogeneity, elevated WNT signaling with nuclear CTNNB1, and strong AP-1 motif enrichment—features absent or attenuated in low-risk subgroups. Created in BioRender. Fincke, V. (2026) https://BioRender.com/h5ljapn.