Glioblastoma Patients Exhibit Circulating Tumor-Specific CD8+ T Cells
Bibliographic record
Abstract
PURPOSE: There is growing interest in developing cellular immune therapies for glioblastoma multiforme, but little is known about tumor-specific T-cell responses. A glioblastoma multiforme-specific T-cell assay was developed using monocyte-derived dendritic cells to present tumor antigens from the established glioblastoma multiforme cell line U118. EXPERIMENTAL DESIGN: Peripheral blood mononuclear cells (PBMC) and tumor cells were obtained from nine patients with newly diagnosed brain tumors: five glioblastoma multiforme, two oligodendroglioma, one ependymoma, and one astrocytoma. PBMCs were incubated overnight with autologous tumor cells or autologous dendritic cells loaded with a U118 cell lysate, and responses were detected by IFN-gamma ELISPOT and cytokine flow cytometry assays. RESULTS: PBMCs from all glioblastoma multiforme patients exhibited IFN-gamma responses to autologous tumor but not to HLA-mismatched U118 cells. Glioblastoma multiforme-specific IFN-gamma responses were primarily mediated by CD8+ T cells and represented approximately 2% of total CD8+ T cells. Additionally, all glioblastoma multiforme patients responded to autologous dendritic cells loaded with U118 lysate but not with low-grade astrocytoma cell lysates. PBMCs from four patients with other brain tumor types and one normal donor failed to respond to U118 lysate-loaded autologous dendritic cells. These data indicate that the IFN-gamma responses to U118 lysate-loaded autologous dendritic cells are glioblastoma multiforme specific. Moreover, PBMCs stimulated 1 to 2 weeks with U118 lysate-loaded dendritic cells exhibited MHC class I-restricted cytotoxicity against autologous tumor cells. CONCLUSIONS: Glioblastoma multiforme patients exhibit circulating tumor-specific CD8+ T cells that recognize shared tumor antigens from the glioblastoma multiforme cell line U118. These data show that glioblastoma multiformes are immunogenic and support the development of immunotherapy trials.
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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) | 0.003 | 0.001 |
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".