This study employs systems medicine approaches, including complex networks and machine learning-driven discovery, to identify key biomarkers governing phenotypic plasticity in pediatric high-grade gliomas (pHGGs), namely, IDH-WT glioblastoma and H3K27M diffuse intrinsic pontine glioma (DIPG). By integrating single-cell transcriptomics and histone mass cytometry data, we conceptualize these aggressive tumors as complex adaptive ecosystems driven by hijacked oncofetal developmental programs and pathological attractor dynamics. Our analysis predicts lineage-plasticity markers, including KDM5B (JARID1B), ARID5B, GATA2/6, WNT, TGFβ, NOTCH, CAMK2D, ATF3, DOCK7, FOXO1/3, FOXA2, ASCL4, PRDM9, METTL5/8, RAP1B, CD99, RLIM, TERF1, and LAPTM5, as drivers of cell fate cybernetics. Further, we identified endogenous bioelectric signatures, including voltage-gated and ligand-gated ion channels like GRIK, GRIN, SLC5A9, NKAIN4, and KCNJ4/6, as potential reprogramming targets. Additionally, we validate previously discovered plasticity genes such as PDGFRA, EGFR targets, OLIG1/2, FXYD5/6, MTSS1, SEZ6L, MTRN2L1, and SOX11, confirming the robustness of our complex systems approaches. This systems oncology framework offers promising avenues for precision medicine, optimizing patient outcomes by guiding combination therapies informed by single-cell multi-omics and targeting pHGG phenotypic plasticity as therapeutic vulnerabilities. Further, our findings suggest the epigenetic reprogrammability of tumor phenotypic plasticity (i.e., transition therapy) and maladaptive behaviors in pHGG ecosystems toward stable, transdifferentiated states.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://github.com/Abicumaran/Glioblastoma_III...

H3K4-H3K9 Histone Methylation Patterns and Oncofetal Developmental Networks as Drivers of Cell Fate Decisions in Pediatric High-Grade Gliomas

10.1101/2024.12.29.630486