Abstract B010: Revealing the Influence of the Infantile Immune System on the Developmental Origins of Childhood Ependymoma: An Integrative Multi-Omic Investigation of Supratentorial Ependymoma Tumorigenesis Driven by ZFTA-RELA Fusion
Bibliographic record
Abstract
Abstract Despite advances in treatment, the recurrence rate of childhood supratentorial ependymomas remains distressingly high, with approximately 60% of patients experiencing relapse. Moreover, the rigorous treatment regimen poses significant challenges to the quality of life of affected children. Among supratentorial ependymomas, those driven by the ZFTA-RELA fusion represent over 70% of cases. Here, we present the pioneering development of a spontaneous genetically engineered mouse model (GEMM) for ZFTA-RELA fusion-driven ependymoma. By targeting the Nestin-Flx-STOP-Flx-ZFTA-RELA open reading frame with luciferase to the Rosa-26 locus of C57B/L6 mice, and subsequently crossing them with the Nestin-CreERT2 line, we successfully induced recombination in neural progenitor cells. Consequently, resulting in the development of forebrain tumors that could be monitored through non-invasive bioluminescence imaging from postnatal day 20. Recognizing the neonatal origins of ZFTA-RELA ependymoma, our study employed an integrated multi-omic approach to investigate the complete developmental trajectory of this tumor, spanning from embryonic stages to postnatal tumor formation. Notably, we uncovered a reservoir of immature immune populations in the developing brain, which we implicate in the central tolerance of ependymoma tumorigenesis. The coordinated interaction between these immature immune populations in the developing brain and immune cell progenitors in the skull bone marrow niche establishes a unique environment that fosters tumor formation. In light of these findings, we propose that immunotherapeutic strategies aimed at augmenting these immature immune populations hold promise as potential therapeutic interventions. By exploiting the intricate interplay between these populations, we may unlock new avenues for targeted immunotherapies in ZFTA-RELA ependymoma. Our research sheds vital light on the critical role played by the pediatric immune system in the developmental origins of this devastating malignancy, opening up exciting possibilities for improved treatments and outcomes in the future. Citation Format: Elizabeth Cooper, Sigourney Bonner, Amir Jassim, Gunjan Katyal, Alisha Kardian, Stephen C. Mack, Katherine Masih, Jessica T. Taylor, Claire King, Katherine Wickham Rahrmann, Linda Hu, Richard J. Gilbertson. Revealing the Influence of the Infantile Immune System on the Developmental Origins of Childhood Ependymoma: An Integrative Multi-Omic Investigation of Supratentorial Ependymoma Tumorigenesis Driven by ZFTA-RELA Fusion [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B010.
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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 | 0.000 | 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 | 0.001 |
| 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".