Increased Regulatory T-Cell Fraction Amidst a Diminished CD4 Compartment Explains Cellular Immune Defects in Patients with Malignant Glioma
Bibliographic record
Abstract
Immunosuppression is frequently associated with malignancy and is particularly severe in patients with malignant glioma. Anergy and counterproductive shifts toward T(H)2 cytokine production are long-recognized T-cell defects in these patients whose etiology has remained elusive for >30 years. We show here that absolute counts of both CD4(+) T cells and CD4(+)CD25(+)FOXP3(+)CD45RO(+) T cells (T(regs)) are greatly diminished in patients with malignant glioma, but T(regs) frequently represent an increased fraction of the remaining CD4 compartment. This increased T(reg) fraction, despite reduced counts, correlates with and is sufficient to elicit the characteristic manifestations of impaired patient T-cell responsiveness in vitro. Furthermore, T(reg) removal eradicates T-cell proliferative defects and reverses T(H)2 cytokine shifts, allowing T cells from patients with malignant glioma to function in vitro at levels equivalent to those of normal, healthy controls. Such restored immune function may give license to physiologic antiglioma activity, as in vivo, T(reg) depletion proves permissive for spontaneous tumor rejection in a murine model of established intracranial glioma. These findings dramatically alter our understanding of depressed cellular immune function in patients with malignant glioma and advance a role for T(regs) in facilitating tumor immune evasion in the central nervous system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".