55 INSIGHTS INTO MENINGIOMA BIOLOGY AND RADIOTHERAPY RESPONSE THROUGH MOLECULAR CHARACTERIZATION OF RTOG-0539 CLINICAL TRIAL
Bibliographic record
Abstract
Abstract Brain Tumour Foundation of Canada Travel Award Recipient BACKGROUND Meningiomas are the most common primary intracranial tumors. Radiotherapy (RT) is an adjunct treatment following surgical resection, but response varies. RTOG-0539 is the first prospective phase 2 clinical trial to stratify patients into risk groups for adjuvant RT, establishing key benchmarks for RT outcomes. This study provides the first molecular characterization of an RT clinical trial in meningiomas to identify biological insights into RT response and tumor behavior. METHODS Tumor tissue from 100meningioma patients enrolled in the RTOG-0539 trial was analyzed using DNA methylation profiling, RNA sequencing, and whole-exome sequencing. Copy number variations, mutational landscapes, and gene expression patterns were examined to identify molecular correlates of tumor aggressiveness and RT response. Consensus pathway analysis was performed to determine biological processes associated with differential RT sensitivity. RESULTS High-risk meningiomas demonstrated significant cell cycle dysregulation and upregulation of hypermetabolic pathways. Specific genomic alterations, including 1p loss and 1q gain, were associated with aggressive tumor behavior. Co-occurrence of NF2 and non-NF2 mutations was identified in select high-risk cases, suggesting distinct molecular subgroups. Notably, molecular profiling led to reclassification of several tumors, revealing discrepancies between histopathologic grading and underlying biology. CONCLUSION This is the first study to comprehensively define the molecular landscape of meningiomas treated with RT in a prospective clinical trial. Multi-omic integration refined risk stratification beyond histopathologic grading, with implications for genomically guided treatment strategies. These findings align with ongoing precision medicine trials and emphasize the importance of prospective tumor banking to facilitate biomarker-driven approaches in meningioma management.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".