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Bioinformatics approach identifies a specific senescence gene signature in pediatric low-grade gliomas, suggesting new therapeutic opportunities.
Pediatric low-grade gliomas (pLGGs), the most common brain tumors in children, are driven by constitutive MAPK pathway activation leading to oncogene-induced senescence (OIS). While OIS is central to pLGG biology and represents a potential therapeutic vulnerability, its investigation is limited by the lack of robust molecular markers. We developed a bioinformatics-driven strategy to derive a refined, cell-type-independent OIS gene signature specific for pLGG. Published senescence gene sets (n = 20) from diverse biological contexts (e.g. cellular senescence, premalignant tumors, induced senescence) were systematically integrated and filtered using cell type-specific expression references and deconvolution-informed approaches to remove lineage-associated bias. Given the prevalent MAPK activation in pLGG, additional filtering steps were applied to exclude genes reflecting MAPK pathway activity rather than senescence-specific biology. The resulting OIS signature was validated across multiple transcriptomic datasets, including in vitro pLGG models and large, clinically annotated pediatric brain tumor cohort (OPBTA). The signature containing genes downregulated in senescent cells robustly distinguished senescent from proliferating pLGG models and showed strong and specific enrichment in primary pLGG samples compared to high-grade gliomas (HGG). Importantly, the derived OIS signatures showed no significant correlation with MAPK activity score, indicating specificity for senescence-associated transcriptional programs beyond oncogenic signaling. Benchmarking against senescence signatures (n = 31) demonstrated improved robustness and specificity in the pLGG context. Further validation steps will apply the refined signatures to large, clinically annotated bulk and single-cell pLGG datasets to evaluate clinical relevance, including associations with progression-free survival, and to distill a reduced set of candidate marker genes for translational validation. Together, these findings introduce refined oncogene-induced senescence-associated gene signatures in pLGG, derived using a systematic analytical approach. These signatures provide a foundation for ongoing single-cell-resolved analyses and future experimental and clinical studies addressing the biological and clinical relevance of senescent tumor cell populations.
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Schulz et al. (2026) studied this question.
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