EPCO-05. AN ONCOGENIC PHOTORECEPTOR PROGRAM UNIFIES DISTINCT CENTRAL NERVOUS SYSTEM TUMORS
Bibliographic record
Abstract
Abstract Pineoblastoma (PB) is a clinically aggressive embryonal central nervous system (CNS) tumor composed of distinct molecular subgroups. The cellular and biological basis of PB remains poorly defined, limiting the development of more effective therapeutic strategies. To identify the cellular composition, origins, and drivers of PB, we derived single-cell transcriptomes from patient-derived pineal tumors (n=38) and integrated malignant cells with a novel transcriptional atlas of mouse pineal gland development (E13-P21). Application of a series of computational strategies pinpointed transient, cycling pinealocyte progenitors as the likely cellular origin of PB, irrespective of molecular subgroup. To functionally validate these findings, we generated lineage-specific genetically engineered mouse (GEM) models representing distinct PB subgroups with high temporal, anatomic, and phenotypic fidelity. Transcriptomic analysis further substantiated the accuracy of novel GEM models which converged on cell-cycle dysregulation, highlighting a core pathogenic mechanism across PB subgroups. Relative to the developing pineal gland, photoreceptor transcription factors were aberrantly activated in PB GEM models, suggesting photoreceptor involvement in tumor initiation and/or maintenance. Multi-omic analysis across a large range of diverse CNS cancers revealed an oncogenic photoreceptor program specific to PB, retinoblastoma (RETB), and Group 3 medulloblastoma (G3-MB). This shared transcriptional program was active within respective cellular origins, establishing a unified mechanistic basis across these anatomically distinct CNS tumors. CRISPR-based functional studies confirmed selective dependencies of photoreceptor transcription factors (NRL, CRX, OTX2) in PB, RETB and G3-MB, demonstrating the essentiality of this photoreceptor program. These discoveries not only resolve longstanding uncertainties regarding PB pathogenesis but also highlight conserved molecular signatures and therapeutic vulnerabilities spanning different pediatric CNS malignancies. Our results underscore the potential of targeting developmentally regulated programs and master transcription factors as novel therapeutic strategies for PB, RETB, and G3-MB, offering critical insights and preclinical models for future translational research.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".