HGG-07. INVESTIGATING THE ROLE OF SENESCENCE IN PEDIATRIC HIGH-GRADE GLIOMAS
Bibliographic record
Abstract
Abstract Cellular senescence has expanded well past the original definition of just proliferative exhaustion and tumor suppression. Today, senescence is considered a “Hallmark of Cancer” and the senescence-associated secretory phenotype (SASP) secretes molecules that can promote oncogenesis, angiogenesis, and an immunosuppressive tumor microenvironment (TME). Pediatric high-grade gliomas (pHGGs) are aggressive brain tumors with dismal outcomes and limited therapeutic options. Accumulating evidence suggests potential therapeutic vulnerabilities in targeting senescence in adult solid and brain tumors. Furthermore, senescent immune cells in the TME appear to play an important role in the initiation and progression in adult solid tumors. The role of senescence in pHGGs, however, has not been well described. Here, we show evidence of senescent glial and immune cells in pHGG tumors. Using patient-derived cell lines, we also investigate triggers of senescence and further characterize SASP in pHGGs. By understanding the role of senescence in gliomagenesis, we hope to open new approaches in treating pHGGs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".