Abstract 3171: Vangl2 regulates cancer stem cell self-renewal and growth in rhabdomyosarcoma
Bibliographic record
Abstract
Abstract Growth and relapse are driven by cancer stem cells (CSCs) in a subset of tumors, yet mechanisms driving cancer cell fate choices, maintenance and self-renewal are not fully understood. Here, we show that Van Gogh-like 2 (Vangl2), a core regulator of the non-canonical Wnt/planar cell polarity pathway (Wnt/PCP), regulates CSCs self-renewal in human rhabdomyosarcoma (RMS) – a common pediatric cancer of muscle. Wnt/PCP signaling is essential during development and recent work has linked this pathway to cancer growth, invasion and metastasis. However, roles for Vangl2 in regulating tumor self-renewal have not been previously described. Here, we show that VANGL2 is expressed in a majority of human RMS, specifically within early mononuclear progenitor-like cells. VANGL2 depletion inhibited proliferation, reduced self-renewal, and induced differentiation of human RMS. VANGL2 was also required for continued tumor growth and maintenance following engraftment of human RMS using mouse xenografts. Using a zebrafish model of embryonal rhabdomyosarcoma (ERMS) and limiting dilution cell transplantation approaches, we identified that Vangl2 expression enriches for CSCs in vivo and when transgenically expressed, at high levels elevates cancer stem cell number by 9-fold. Mechanistic studies revealed a role for RhoA downstream of Vangl2 in regulating maintenance of stem cell programs in human RMS. Our studies offer novel opportunities to isolate and characterize RMS cancer stem cells in vivo, and identify potential therapeutic targets for patient treatment. Citation Format: Madeline Hayes, Karin McCarthy, Alexander Jin, Sowmya Iyer, Sara Garcia, Mariana L. Oliveira, Sivasish Sindiri, Berkley Gryder, Zainab Motala, G Petur Nielsen, Jean-Paul Borg, Matt van de Rijn, David Malkin, Javed Khan, Myron Ignatius, David M. Langenau. Vangl2 regulates cancer stem cell self-renewal and growth in rhabdomyosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3171.
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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".