Targeting NKG2D ligands in glioblastoma with a bispecific T-cell engager is augmented with conventional therapy and enhances oncolytic virotherapy of glioma stem-like cells
Bibliographic record
Abstract
BACKGROUND: Glioblastoma (GBM) almost invariably becomes resistant towards conventional treatment of radiotherapy and temozolomide (TMZ) chemotherapy, partly due to subpopulations of intrinsically resistant glioma stem-like cells (GSC). The oncolytic herpes simplex virus-1 G207 is a promising approach for GBM virotherapy although its efficacy in patients with GBM is often limited. Natural killer group 2 member D ligands (NKG2DLs) are minimally expressed by healthy cells but are upregulated by the DNA damage response (DDR) and in malignant cells with chronic DDR signaling, resulting in innate immune activation. METHODS: We have designed a bispecific T-cell engager (BiTE) capable of cross-linking CD3 on T cells with NKG2DL-expressing GBM cells. We then engineered the G207 virus to express the NKG2D BiTE and secrete it from infected cells. The efficacy of the free BiTE and BiTE delivered by G207 was evaluated in combination with conventional therapies in GBM cells and against patient-derived GSCs in the context of T-cell activation and target cell viability. RESULTS: NKG2D BiTE-mediated cross-linking of GBM cells and T cells causes antigen-independent T-cell activation, pro-inflammatory cytokine release, and tumor cell death, thereby combining direct viral oncolysis with BiTE-mediated cytotoxicity. Surface NKG2DL expression was further elevated on GBM cells following pretreatment with sublethal doses of TMZ and radiation to induce the DDR, increasing sensitivity towards G207-NKG2D BiTE and achieving synergistic cytotoxicity. We also demonstrate a novel strategy for targeting GSCs that are non-permissive to G207 infection but remain sensitive to NKG2D BiTE. CONCLUSIONS: We propose a potential model for targeting GSCs in heterogeneous tumors, whereby differentiated GBM cells infected with G207-NKG2D BiTE produce NKG2D BiTE locally, directing T-cell cytotoxicity towards the GSC subpopulations in the tumor microenvironment.
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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".