NKG2D- and T-cell receptor-dependent lysis of malignant glioma cell lines by human γδ T cells: Modulation by temozolomide and A disintegrin and metalloproteases 10 and 17 inhibitors
Bibliographic record
Abstract
The interaction of the MHC class I-related chain molecules A and B (MICA and MICB) and UL-16 binding protein (ULBP) family members expressed on tumor cells with the corresponding NKG2D receptor triggers cytotoxic effector functions in NK cells and γδ T cells. However, as a mechanism of tumor immune escape, NKG2D ligands (NKG2DLs) can be released from the cell surface. In this study, we investigated the NKG2DL system in different human glioblastoma (GBM) cell lines, the most lethal brain tumor in adults. Flow cytometric analysis and ELISA revealed that despite the expression of various NKG2DLs only ULBP2 is released as a soluble protein via the proteolytic activity of “a disintegrin and metalloproteases” (ADAM) 10 and 17. Moreover, we report that temozolomide (TMZ), a chemotherapeutic agent in clinical use for the treatment of GBM, increases the cell surface expression of NKG2DLs and sensitizes GBM cells to γδ T cell-mediated lysis. Both NKG2D and the T-cell receptor (TCR) are involved. The cytotoxic activity of γδ T cells toward GBM cells is strongly enhanced in a TCR-dependent manner by stimulation with pyrophosphate antigens. These data clearly demonstrate the complexity of mechanisms regulating NKG2DL expression in GBM cells and further show that treatment with TMZ can increase the immunogenicity of GBM. Thus, TMZ might enhance the potential of the adoptive transfer of ex vivo expanded γδ T cells for the treatment of malignant glioblastoma.
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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 | 0.000 |
| 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".