Normal human monocytes exposed to glioma cells acquire myeloid-derived suppressor cell-like properties
Bibliographic record
Abstract
Glioblastoma patients are immunosuppressed, yet glioblastomas are highly infiltrated by monocytes/macrophages. Myeloid-derived suppressor cells (MDSC; immunosuppressive myeloid cells including monocytes) have been identified in other cancers and correlate with tumor burden. We hypothesized that glioblastoma exposure causes normal monocytes to assume an MDSC-like phenotype and that MDSC are increased in glioblastoma patients. Healthy donor human CD14(+) monocytes were cultured with human glioblastoma cell lines. Controls were cultured alone or with normal human astrocytes. After 48 hours, glioblastoma-conditioned monocytes (GCM) were purified using magnetic beads. GCM cytokine and costimulatory molecular expression, phagocytic ability, and ability to induce apoptosis in activated lymphocytes were assessed. The frequency of MDSC was assessed by flow cytometry in glioma patients' blood and in GCM in vitro. As predicted, GCM have immunosuppressive, MDSC-like features, including reduced CD14 (but not CD11b) expression, increased immunosuppressive interleukin-10, transforming growth factor-beta, and B7-H1 expression, decreased phagocytic ability, and increased ability to induce apoptosis in activated lymphocytes. Direct contact between monocytes and glioblastoma cells is necessary for complete induction of these effects. In keeping with our hypothesis, glioblastoma patients have increased circulating MDSC compared with normal donors and MDSC are increased in glioma-conditioned monocytes in vitro. To our knowledge, this has not been reported previously. Although further study is needed to directly characterize their origin and function in glioblastoma patients, these results suggest that MDSC may be an important contributor to systemic immunosuppression and can be modeled in vitro by GCM.
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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) | 0.002 | 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".