TMIC-16. THE IMMUNO-PROTECTIVE FUNCTION OF GLIOMA-ASSOCIATED BONE MARROW DERIVED CELLS DEPENDS ON THE STAGE OF TUMOR GROWTH AND IS INFLUENCED BY TREATMENT WITH MINOCYCLINE
Bibliographic record
Abstract
Glioblastoma (GBM) remains the most aggressive primary brain tumor due to its recurrent nature and inherent ability to evade the current treatment strategies. Non-malignant monocyte lineage cells including monocyte, macrophage, microglia, and dendritic cells, infiltrate the glioblastoma tumor mass and contribute to its growth and homeostasis. These cells can become activated towards an immuno-suppressive and pro-angiogenic state that promotes continued tumor growth. While it was once thought that glioma-associated macrophages and microglia play an anti-tumor role, more recent studies have suggested that tumors may co-opt these immune cells for their own tumor-promoting function. In this study, we assessed the tumor-suppressor and pro-tumor roles of glioma associated macrophages and microglia using the antibiotic minocycline. Minocycline is a non-cytotoxic antibiotic that could be re-purposed, as a single agent or in combination with other medications, to inhibit or reverse immuno-suppression, angiogenesis, and other tumor growth-enhancing roles of microglia and macrophages. We demonstrate that bone marrow-derived cells (BMDCs) that track to mouse gliomas and mature into glioma-associated microglia/macrophages function in either an anti- or pro-tumorigenic manner upon treatment with minocycline, depending on the stage of tumor growth at which this drug is administered. Survival analysis of glioma mouse models indicated that treatment with minocycline immediately after intracrainial injections reduced survival, while delayed treatment increased the survival of mice. In addition, our data indicate that minocycline affects the immune function of BMDCs by altering their ability to phagocytoze tumor cells. This observation was in agreement with changes observed in the expression of genes known to play a role in phagocytosis. These findings strengthen the hypothesis that tumor-resident BMDCs can play a dual anti-tumorigenic or pro-tumorigenic role depending on the stage of tumor growth. As such, targeting these cells with pharmaceutical agents for treatment of gliomas requires detailed understanding of their exact role in the tumors.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".