TMIC-17. IMMUNE MICROENVIRONMENT OF NF2-ALTERED RADIATION-INDUCED MENINGIOMAS
Bibliographic record
Abstract
Radiation-induced meningiomas (RIMS) are more clinically aggressive than their sporadic counterparts, with higher rates of tumor recurrence, multiplicity and neurological impairment. Our laboratory has previously demonstrated that RIMs have a distinct genomic profile with a subset of tumors harboring NF2 inactivation through genomic rearrangements. In this study we establish the clinical characteristics and immune microenvironment between RIMs with and without the NF2 alterations. A retrospective chart review was performed on 31 RIMs. Volumetric analysis was performed using ITK-SNAP on serial preoperative imaging to estimate tumor growth rate. Immunohistochemistry staining for PD-1, PD-L1, CD-3, CD-163, and FOX-P3 were performed. Results were correlated with whole exome sequencing and RNA sequencing data previously published. Pathway analysis was performed using Gene Set Enrichment Analysis (GSEA) on RNA sequencing data using the differentially expressed genes. Clinically, NF2-altered tumors and NF2-WT (wildtype) tumors did not differ based on age at diagnosis, indication for previous radiation, WHO grade, histopathological subtype, extent of resection and tumor location. NF2-altered tumors had a significantly faster growth rate compared to NF2-WT tumors (3.8X faster, p>0.05). The difference in growth rate was independent of tumor grade. PD-L1 staining was negative on tumor cells in NF2-altered tumors and patchy positivity in 60% of NF2-WT tumors (p < 0.05). In contrast, 100% and 60% of tumors had PD-L1 positive immune cells in NF2-altered and NF2-WT tumors, respectively (p<0.05). The degree of CD3+ lymphocyte infiltration was lower in NF2-altered tumors (t=2.73, p<0.05). Our findings suggest that there is a difference in the immune microenvironment between NF2-altered and NF2-WT RIMs. NF2-altered tumors have a lower degree of CD3+ lymphocyte infiltration and higher frequency of PD-L1 positive immune cells that are indicative of an immunosuppressed microenvironment. Further work is needed to elucidate pathways that may be targeted to manipulate the immune 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 | 0.001 | 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 | 0.000 |
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".