Malignant glioma cells use MHC class II transactivator (CIITA) promoters III and IV to direct IFN‐γ‐inducible CIITA expression and can function as nonprofessional antigen presenting cells in endocytic processing and CD4<sup>+</sup> T‐cell activation
Bibliographic record
Abstract
Malignant gliomas (MGs), lethal human central nervous system (CNS) neoplasms, contain tumor infiltrating lymphocytes (TIL). Although MHC class II molecules are frequently detected on MG cells, suggesting that they may be capable of antigen (Ag) presentation to CD4(+) T cells, deficiencies in CD4(+) T-cell activation are associated with these nonimmunogenic tumors. We evaluated regulation of the MHC class II transactivator (CIITA), the key intermediate that controls class II expression, in MG cells and tested whether MG cells could process native Ag. After interferon-gamma (IFN-gamma) stimulation, MG cells upregulated CIITA and class II molecules. IFN-gamma-inducible CIITA expression in MG cells, as well as primary human astrocytes, was directed by two CIITA promoters, pIV, the promoter for IFN-gamma-inducible CIITA expression in nonprofessional antigen-presenting cells (APC), and pIII, the promoter that directs constitutive CIITA expression in B cells. Both pIII and pIV directed CIITA transcription in vivo in MGs and ex vivo in IFN-gamma-activated primary MG cultures. We also demonstrate for the first time that MG cells can process native Ag for presentation to CD4(+) MHC class II-restricted Th1 cells, indicating that MG cells can serve as nonprofessional APC. CIITA may be a key target to modulate MHC class II expression, which could augment immunogenicity, Ag presentation, and CD4(+) T-cell activation in MG therapy.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".