Abstract B74: Investigating the role of tumor:bone microenvironment crosstalk in Ewing sarcoma progression
Bibliographic record
Abstract
Abstract Background: Ewing sarcoma is the second most common pediatric bone cancer. Metastatic disease is almost always fatal, and there is currently no method to predict which patients are at risk for metastasis. Better therapies are needed to prevent and treat metastatic disease, which means the mechanisms that drive Ewing sarcoma metastasis must be better elucidated. It is becoming increasingly clear that interactions between tumor cells and the tumor microenvironment (TME) play an essential role in metastasis, but the specific mechanisms through which the TME contributes to Ewing sarcoma progression remain largely unknown. Our previous work has demonstrated that activation of canonical Wnt and TGF-β pathways in a subset of Ewing sarcoma cells induces changes in gene expression and protein secretion that are associated with enhanced metastatic engraftment, changes in the extracellular matrix (ECM), and increased angiogenesis. As bone, the primary site for Ewing sarcoma, is an excellent source of ligands for both pathways, we hypothesize that crosstalk between Wnt/TGF-β-activated tumor cells and the local bone microenvironment contributes to osteolysis and metastatic progression. Methods: Ewing sarcoma cells were treated with control or Wnt3a media +/- recombinant TGF-β1, and then the mRNA levels of target genes were measured by Q-RT-PCR. ELISA and Luminex assays were also performed to determine the levels of secreted proteins. Conditioned media collected from stimulated cells were used to treat osteoblast precursor cells, which were then assayed for effects on differentiation and function. Subcutaneous, femur, and vossicle transplant xenograft models were established in mice and are being validated. Results: We have demonstrated that in response to Wnt3a and TGF-β1, Ewing sarcoma cells upregulate expression of canonical Wnt targets (e.g., LEF1), ECM-associated genes (e.g., TNC, COL1A1, and MMP2), and the pro-osteolytic factor PTHrP. We have also shown that osteoblast precursor cells can be induced to differentiate in the presence of conditioned media from Ewing sarcoma cell lines. Immunohistochemical staining is being used to evaluate Wnt and TGF-β pathway activation, angiogenesis, osteolysis, and the ECM in our bone tumor xenograft models. Conclusions: Wnt3a/TGF-β1-stimulated Ewing sarcoma cells upregulate expression of genes associated with the ECM and osteolysis. We are in the process of demonstrating the functional consequences of those changes using in vitro conditioned media experiments and in vivo transplant models. Understanding the mechanisms by which these pathways contribute to Ewing sarcoma phenotypes is important for the development of new therapeutics for patients with metastatic disease. Citation Format: Kelsey Temprine, Sydney Treichel, Allegra Hawkins, Tahra Suhan, Wei Jiang, Parker Acevedo, Amy Koh, Kurt Hankenson, Laurie K. McCauley, Elizabeth R. Lawlor. Investigating the role of tumor:bone microenvironment crosstalk in Ewing sarcoma progression [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B74.
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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) | 0.006 | 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".