Abstract 6445: Atypical teratoid rhabdoid tumor development mirrors developmental programs
Bibliographic record
Abstract
Abstract Atypical Teratoid Rhabdoid Tumors (ATRTs) are pediatric malignancies that arise primarily in young children under the age of 3. While ATRTs are known to segregate into three epigenetically defined subgroups, termed SHH, TYR, and MYC, little is known about the cellular contexts of how these deadly tumors arise and gain tumorigenic properties. We hypothesized that this early onset of disease reflects tumorigenic events in utero. Indeed, previous research has demonstrated maintenance of embryogenesis programs in other pediatric brain tumors. To characterize the cellular contexts that give rise to ATRTs, we curated 12 single cell and single nuclei RNAseq datasets of human and mouse embryogenesis and developed an atlas and well as a pipeline to match tumors to their most similar embryogenic landmark and timepoint, based on the published cell type identification tool SingleR. We applied this pipeline to two ATRTs single cell datasets generated on the 10X genomics platform: one from primary human samples (N = 33), and one from a tamoxifen inducible ATRT mouse model (N = 8). To validate the accuracy of our pipeline, we first examined the signatures from our ATRT mouse model. Our pipeline accurately predicted cell types and timepoint within the induction window of E6.5-8.5, suggesting that indeed tumors transcriptionally resemble their cellular contexts. Results on both human and mouse ATRTs reveals that ATRTs resemble two distinct developmental trajectories: one resembling a gradient of neuronal differentiation from neuroepithelial (NES, SOX2, OTX2) to radial glial cell (TTYH1, ASCL1, FAPB7) types, and a second trajectory characterized by distinctly mesenchymal signatures (COL1A2, PDGFRB). Single cell GSEA showed enrichment of pathways involved in radial glial and mesenchymal signalling, such as WNT, SHH, and PDGFRB signalling. Findings were validated through marker gene immunohistochemistry and spatial transcriptomics. Taken together, our results demonstrate that ATRTs transcriptionally resemble the developmental contexts of which they arise from. By identifying cellular origins of tumorigenesis, we can exploit this novel information to discover potential therapeutic avenues. Citation Format: Fupan Yao, Dean Popovski, Andrew Bondoc, James Rutka, Trevor Pugh, Annie Huang. Atypical teratoid rhabdoid tumor development mirrors developmental programs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6445.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".