Abstract 5466: <i>In vivo</i> characterization of neuroblastoma intratumoral heterogeneity
Bibliographic record
Abstract
Abstract Background: Neuroblastoma is a pediatric solid tumor that arises from neural crest-derived progenitor cells of the peripheral sympathetic nervous system (PSNS). Neuroblastoma patients display a significant level of genetic and phenotypic heterogeneity, with amplification of the MYCN oncogene associated with poor clinical outcomes. To better understand underlying genetic mechanisms associated with aggressive neuroblastoma, our group incorporated patient-relevant loss-of-function mutations into the established MYCN-driven zebrafish model of neuroblastoma (Tg(dbh:EGFP-MYCN)), which resulted in increased tumor penetrance and a highly metastatic phenotype. Aims & Methods: We aimed to investigate metastases-associated intratumoral heterogeneity in vivo using our patient-relevant metastatic zebrafish models, with functional validations performed using human neuroblastoma cell lines. Results: Single-cell RNA sequencing of metastatic zebrafish neuroblastoma tumors revealed intra-tumor cell heterogeneity, with a subset of cells highly expressing markers of more differentiated adrenergic-like cell fates (th, dbh, phox2a) while others enriched for markers of less differentiated mesenchymal-like progenitor cells (prrx1a, vim, fn1a). Differential cell labeling in zebrafish neuroblastoma suggests distinct tumor cell populations for follow-up validation and characterization throughout metastatic progression. Conclusion: Single-cell RNA sequencing of zebrafish metastatic neuroblastoma showed evidence of intratumoral heterogeneity that warrants further investigation. We are characterizing neuroblastoma intratumoral heterogeneity in our in vivo metastatic zebrafish models to examine the association between neuroblastoma tumor composition and metastatic potential. Altogether, this work aims to improve our understanding of the evolution of tumor cell heterogeneity associated with neuroblastoma metastasis and uncover novel therapeutic opportunities to improve patient outcomes. Citation Format: Willow R. Squires, Alex Weiss, Sarah Cohen-Gogo, Adam Shlien, David Kaplan, Meredith S. Irwin, Madeline N. Hayes. In vivo characterization of neuroblastoma intratumoral heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5466.
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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) | 0.002 | 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".