Immune Cell Infiltrates in Atypical Teratoid/Rhabdoid Tumors
Bibliographic record
Abstract
OBJECTIVE: Atypical teratoid/rhabdoid tumor (AT/RT) is a highly malignant tumor of the central nervous system. Its pathogenesis remains unknown. Like glioblastomas, AT/RTs contain brain cancer stem cells (CSCs) that suppress the immunity of patients and are resistant to conventional chemotherapy and radiation therapy. Considerable infiltration of immune cells, including macrophages/microglia, dendritic cells and T-cells, has been noted in glioblastomas, which correlates with poor prognosis. The present study examines the significance of infiltrating immune cells in four cases of AT/RT; including one associated with an autoimmune disease, Henoch-Schonlein purpura. METHODS: Tumor tissues from four patients with AT/RT were analyzed and compared with those from four patients with glioblastomas. The frequency of immune cells, including CD68+, CD4+, and CD8+ cells, was assessed by scoring for statistical analysis. RESULTS: The infiltration of immune cells was identified in the case of AT/RT associated with HSP and three other cases of infratentorial AT/RTs. Moderate infiltration of CD68+ macrophages/microglia and CD4+ cells was noted in AT/RTs with no significant difference from that in glioblastomas (p > 0.05). However, the infiltration of CD8+ T-cells was significantly higher in AT/RTs than that in glioblastomas (p < 0.05); CD4+/CD8+ ratio was significantly lower in AT/RTs than that in glioblastomas (p < 0.05). In addition, eosinophils were found in all AT/RTs, but not in glioblastomas. CONCLUSIONS: These findings suggest an immune microenvironment of AT/RTs with more immune effectors than glioblastomas. Our observation contributes to understanding the growth environment of AT/RTs for which adjuvant immunotherapy may be potentially beneficial.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".