Abstract B009: Cancer-associated fibroblasts remodel the extracellular matrix in Adamantinomatous Craniopharyngioma
Bibliographic record
Abstract
Abstract Adamantinomatous craniopharyngiomas (ACPs) are benign but locally invasive pituitary tumors that cause significant neuroendocrine morbidity due to their proximity to critical brain structures. Standard of care is surgical resection and radiation, with no effective medical therapies available. Despite intervention, up to 25% of patients experience tumor recurrence. ACPs are driven by somatic mutations in exon 3 of CTNBB1, which result in degradation-resistant beta-catenin and aberrant activation of WNT target genes. Interestingly, only a small subset of tumor cells, known as cluster cells, display oncogenic nuclear accumulation of beta-catenin. In contrast, the majority of ACPs are composed of tumor cells with cytoplasmic accumulation of beta-catenin, along with immune cells, cancer-associated fibroblasts (CAFs), and cysts. This disparity raises key questions about the mechanisms driving ACPs development and growth.: Recent work from our group and collaborators has revealed extensive cell-cell communication between cluster cells, other tumor cell populations, and cells in the tumor microenvironment (TME), suggesting that cluster cells may promote ACP tumorigenesis via secreted factors. Supporting this, our collaborators have shown that in murine models, cluster cells induce the proliferation of nearby cells in a non-cell autonomous manner.: To further investigate the role of cell-extrinsic factors in human ACPs, we performed single-cell RNA sequencing (scRNA-seq) on seven patient ACP samples from our institution. Consistent with prior studies, we identified diverse cell populations, including cluster cells, other epithelial tumor cells, immune cells, and CAFs. Notably, we observed a significant population of CAFs enriched for extracellular matrix (ECM) remodeling pathways. Furthermore, we detected putative ligand-receptor interactions between CAFs and tumor cells, suggesting that CAFs contribute to ACP progression by modulating the TME through ECM remodeling and supporting tumor development via paracrine signaling.: This previously unrecognized role for CAFs in ACP tumorigenesis highlights a novel and potentially targetable mechanism. Our findings offer new therapeutic insights for treating ACPs, a devastating pediatric cancer for which effective medical therapies are direly needed. Citation Format: Timothy H Chang, Shriya M Rangaswamy, John Jeang, Scott Haston, Danny Jomaa, Prasidda Khadka, Eric Prince, John Apps, Todd Hankinson, Sher Bahadur, Dana Novikov, Jessica Tsai, Riley Choi, Marissa Coppola, Jared Collins, Lissa Baird, Keith Ligon, Juan Pedro Martinez-Barbera, Pratiti Bandopadhayay. Cancer-associated fibroblasts remodel the extracellular matrix in Adamantinomatous Craniopharyngioma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Discovery and Innovation in Pediatric Cancer— From Biology to Breakthrough Therapies; 2025 Sep 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_2):Abstract nr B009.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".