Immune Infiltration of Spontaneous Mouse Astrocytomas Is Dominated by Immunosuppressive Cells from Early Stages of Tumor Development
Bibliographic record
Abstract
Immune infiltration of advanced human gliomas has been shown, but it is doubtful whether these immune cells affect tumor progression. It could be hypothesized that this infiltrate reflects recently recruited immune cells that are immediately overwhelmed by a high tumor burden. Alternatively, if there is earlier immune detection and infiltration of the tumor, the question arises as to when antitumor competency is lost. To address these issues, we analyzed a transgenic mouse model of spontaneous astrocytoma (GFAP-V(12)HA-ras mice), which allows the study of immune interactions with developing glioma, even at early asymptomatic stages. T cells, including a significant proportion of Tregs, are already present in the brain before symptoms develop, followed later by macrophages, natural killer cells, and dendritic cells. The effector potential of CD8 T-cells is defective, with the absence of granzyme B expression and low expression of IFN-gamma, tumor necrosis factor, and interleukin 2. Overall, our results show an early defective endogenous immune response to gliomas, and local accumulation of immunosuppressive cells at the tumor site. Thus, the antiglioma response is not simply overwhelmed at advanced stages of tumor growth, but is counterbalanced by an inhibitory microenvironment from the outset. Nevertheless, we determined that effector molecule expression (granzyme B, IFN-gamma) by brain-infiltrating CD8 T-cells could be enhanced, despite this unfavorable milieu, by strong immune stimuli. This potential to modulate the strong imbalance in local antiglioma immunity is encouraging for the development and optimization of future glioma immunotherapies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".