RBIO-06. CLINICAL AND MOLECULAR PREDICTORS OF RADIATION RESPONSIVENESS IN MENINGIOMAS: A MULTICENTER RETROSPECTIVE COHORT STUDY
Bibliographic record
Abstract
Abstract BACKGROUND Aside from surgery, radiotherapy (RT) remains the only standard of care treatment for meningiomas. However, few studies have identified clinical/molecular biomarkers associated with responsiveness to RT and the optimal timing of RT after surgery remains controversial. We aimed to assess outcomes in a large multi-institutional cohort of RT-treated meningiomas to identify clinical factors and DNA methylation and RNA expression markers associated with progression-free survival (PFS) post-RT. METHODS Patients with intracranial meningiomas who underwent treatment with fractionated RT between 1997-2018 were included. DNA-methylation using the Illumina 850K EPICArray and RNA-sequencing were performed on tumours with sufficient tissue. Primary endpoints were radiographic recurrence of progression and time to progression from the time of RT completion. RESULTS 404 meningiomas were included for analysis. Of these, 167 (41.3%) recurred post-RT, usually within 5-years of RT. Previous RT to the meningioma, having a WHO grade 3 meningioma, and older age at diagnosis were independently associated with poorer PFS post-RT. Following propensity score matching, patients that received adjuvant RT had significantly better PFS post-RT compared to those that received salvage RT after recurrence (p=0.04). DNA methylation on 220 of these meningiomas segregated tumours into two distinct methylation groups (RT-resistant and RT-sensitive) based on unsupervised consensus clustering. DNA methylation were able to independently predict PFS post-RT better than all clinical factors. Differential RNA-expression analysis of these groups showed up-regulation of pathways involved in chromosome segregation and mitotic cell cycle and down-regulation of fatty acid metabolism pathways in RT-resistant meningiomas. CONCLUSION While there are a paucity of clinical factors that can reliably predict a meningioma’s response to RT, DNA methylation and RNA expression biomarkers may aid in differentiating RT-resistant meningiomas from RT-sensitive tumours. Patients that receive adjuvant RT may have prolonged PFS post-RT compared to those that receive salvage RT only after recurrence has already occurred.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".