Abstract A052 Project HOPE: A spatiotemporal single-cell landscape of high-grade gliomas in children, adolescents and young adults
Bibliographic record
Abstract
Abstract Despite the growing insights into the cellular heterogeneity of pediatric brain tumors, the transcriptional changes and spatial reorganization during disease progression remain largely unexplored. Here, we present an in-depth single-cell and 10X Xenium spatial transcriptomic characterization of 24 matched pediatric high-grade gliomas (pHGGs) in children, adolescents and young adults (AYA) profiled at both diagnosis and recurrence - constituting a total of 55 tissue samples. By stratifying the transcriptional programs activated at recurrence, we identify two distinct global response sets. Hemispheric AYA tumors predominantly exhibit upregulation of extracellular matrix pathways at recurrence, whereas midline tumors preferentially activate generic stress response programs. On a cellular level, we find that heterogeneity within the malignant tumor compartment remains largely unchanged at recurrence. However, a subset of AYA patients with hemispheric pHGG shows enrichment of the neural-progenitor-like (NPC-like) tumor cell state, and compositional changes in the immune and normal cell landscape, characterized by a global decrease in myeloid cells and an increase in oligodendrocyte fractions. Those changes lead, in turn, to enhanced NPC-like tumor cell-to-oligodendrocyte interactions. Spatial analysis of our extensive cohort at unprecedented subcellular resolution further reveals distinct cellular and spatial features associated with tumor progression, particularly in the remodeling of cell-cell interactions and tumor cell neighborhoods. Overall, this study provides a comprehensive longitudinal single-cell and spatial atlas of pHGG, uncovering the extensive cellular heterogeneity associated with tumor progression. Our findings highlight the role of intrinsic and extrinsic tumor adaptations in shaping disease progression in pHGG, offering potential novel therapeutic targets. Citation Format: Sara G. Danielli, Sina Neyazi, Olivia A. Hack, Li Jiang, Costanza Lo Cascio, Andrezza Nascimento, Cuong Nguyen, Jacob Rozowsky, Ilon Liu, Owen Hoare, Karin Shamardani, Kennedy Cunliffe-Koehler, Johannes Gojo, Keith L. Ligon, Lissa Baird, Sanda Alexandrescu, Jennifer Cotter, Michael Prados, Adam Resnick, Lin Wang, Michelle Monje, Aaron Diaz, Mariella G. Filbin. Project HOPE: A spatiotemporal single-cell landscape of high-grade gliomas in children, adolescents and young adults [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A052.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".