Multi-omics Analysis Identifies Glioblastoma Dependency on H3K9me3 Methyltransferase Activity [ChIP-seq]

Purpose: Enzymes catalyzing histone H3 lysine 9 (H3K9) methylation, such as SUV39H1, SUV39H2, SETDB1, SETDB2, EHMT1, and EHMT2, are individually linked to cancer progression. However, a comprehensive comparison and understanding of their characteristics and mechanisms in cancers is lacking. This study aims to fill this knowledge gap and explore its translational implications. Experimental Design: We conducted multi-omics analyses, including gene expression, mutations, copy number variations, and DNA methylation, to assess the expression patterns, regulation, and prognostic relevance of H3K9 methyltransferases across tumor types. This led to the development of "H3K9me3 MtSig", incorporating SUV39H1, SUV39H2, and SETDB1, with a focus on GBM. Correlations with signaling pathways were explored using gene set enrichment analysis (GSEA) and single-cell expression analyses. ChIP-sequencing was employed to detect H3K9me3 genomic binding sites in GBM cells. We validated the dependency of H3K9me3 MtSig in GBM using patient-derived samples through western blot, immunohistochemistry, immunofluorescence, cell growth, and quantitative PCR. Clinical prediction modeling and drug susceptibility screening were utilized to identify potential therapeutic avenues. Results: H3K9 methyltransferases display diverse expression patterns across cancers, influenced by mutations, CNVs, and DNA methylation associated with the genes. The unique H3K9me3 MtSig signature shows prognostic implications and associations with signaling pathways, particularly in GBM. Elevated H3K9me3 MtSig levels in GBM cells correlate with the G2/M cell cycle positively and immune responses negatively. H3K9me3-mediated repetitive sequence silencing contributes to these phenotypes, with inhibiting it suppressing proliferation and enhancing immune responses. Clinically, H3K9me3 MtSig could act as an independent prognostic factor, and drug susceptibility screening identifies potential GBM biomarkers and therapeutics. Conclusions: H3K9me3 MtSig has the potential to elucidate novel prognostic markers, therapeutic targets, and predictors of treatment response in GBM and other cancer types for clinical intervention.