CD155 regulates tumor growth and immune evasion in diffuse midline glioma
Bibliographic record
Abstract
Abstract Diffuse midline glioma (DMG) is a devastating pediatric brain tumor with an unmet need for novel therapies. Immune checkpoint inhibitors have failed to prolong survival for DMG patients. In this study, we analyzed the expression of immune checkpoint molecules in human and murine DMG cells, as well as primary brain tumor samples, and identified CD155 as the most highly expressed. When murine DMG cells were co-cultured with CD8+ T cells, silencing of CD155 led to a marked increase in T cell-mediated killing. Strikingly, CD155-deficient DMG cells failed to grow in immunocompetent mice, and depletion of CD8+ T cells allowed these tumors to grow. CD155 also exerted cell-autonomous effects on tumor cells: silencing of CD155 led to induction of apoptosis of DMG cells and to delayed tumor growth in immunodeficient mice. Transcriptomic analyses identified FOXM1 as a key target of CD155. Notably, FOXM1 silencing also led to reduced proliferation of DMG cells in vitro and in vivo . Finally, treatment of DMG-bearing mice with Thiostrepton, a FOXM1-targeting agent, delayed tumor growth and prolonged survival. These studies demonstrate that CD155 regulates immune evasion and tumor growth in DMG, and suggest that targeting CD155 could be a valuable two-pronged therapeutic strategy for this disease. Conflict-of-interest statement The authors have declared that no conflict of interest exists.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".