ETMR-21. META-ANALYSIS OF PINEAL REGION TUMOURS DEMONSTRATES MOLECULAR SUBGROUPS WITH DISTINCT CLINICO-PATHOLOGICAL FEATURES: A CONSENSUS STUDY
Bibliographic record
Abstract
Abstract Pineoblastomas (PB) are rare, aggressive pineal gland tumours with poor global OS of 50–70% and only 15–49% OS for patients <4 years, despite intensive treatments. Recently, three independent groups (German Cancer Research Centre, Rare Brain Tumour Consortium/SickKids, St. Jude Children’s Research Hospital) collectively analyzed large tumour cohorts and revealed molecular sub-groups of PB. To harmonize and better characterize clinico-pathologic associations of these sub-groups, we undertook a meta-analysis of molecular and clinical data of the combined cohorts. Unsupervised consensus cluster analyses of global methylation data from 227 unique cases identified five robust molecular sub-groups of pineal region tumours: PB_miRNA_1, PB_miRNA_2, PB_MYC/FOXR2, and PB_RB, mainly comprised of pediatric WHO grade 4 PBs and PNETs; and a fifth group: named PPTID, comprised of mainly pineal parenchymal tumours of intermediate differentiation, a WHO grade 2–3 tumour common in adults. PB_miRNA_1 and PB_miRNA_2 tumours, primarily arising in children (median ages 7.7, 11.4y, respectively), were characterized by alterations of miRNA biogenesis genes DICER1, DROSHA, and DGCR8. PB_MYC/FOXR2 and PB_RB groups, arising in infants/toddlers (median ages 1.4, 2.0y, respectively), were distinguished by recurrent MYC gain/amplification and RB1 loss, respectively. The PPTID group affected mainly adults (median age 33y) and exhibited limited CNAs. Higher rates of metastasis were observed with PB_miRNA_1 (42%), PB_MYC/FOXR2 (38%), and PB_RB (75%) tumours, compared to PB_miRNA_2 (20%) and PPTID (25%). Results from ongoing integrative survival analyses of this large cohort will provide critical data for design of future clinical trials.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.021 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".