Increased Glioma Growth in Mice Depleted of Macrophages
Bibliographic record
Abstract
Macrophages can promote the growth of some tumors, such as those of the breast and lung, but it is unknown whether this is true for all tumors, including those of the nervous system. On the contrary, we have previously shown that macrophages can slow the progression of malignant gliomas through a tumor necrosis factor-dependent mechanism. Here, we provide evidence suggesting that this antitumor effect could be mediated by T lymphocytes, as their number was drastically reduced in tumor necrosis factor-deficient mice and inversely correlated with glioma volume. However, this correlation was only observed in allogeneic recipients, prompting a reevaluation of the role of macrophages in a nonimmunogenic context. Using syngeneic mice expressing the herpes simplex virus thymidine kinase under the control of the CD11b promoter, we show that macrophages can exert an antitumor effect without the help of T lymphocytes. Macrophage depletion achieved by ganciclovir treatment resulted in a 33% increase in glioma volume. The antitumor effect of macrophages was not likely due to a tumoricidal activity because phagocytosis or apoptosis of glioma cells, transduced ex vivo with a lentiviral vector expressing green fluorescent protein, was rarely observed. Their antitumor effect was also not due to a destructive action on the tumor vasculature because macrophage depletion resulted in a modest reduction in vascular density. Therefore, this study suggests that macrophages can attenuate glioma growth by an unconventional mechanism. This study also validates a new transgenic model to explore the role of macrophages in cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".