Abstract B32: ASAP1 regulates differentiation in myoblasts and PAX-FOXO1 fusion-negative rhabdomyosarcoma
Bibliographic record
Abstract
Abstract Rhabdomyosarcoma (RMS), the most frequently diagnosed soft-tissue sarcoma in children, is caused by a differentiation defect in skeletal muscle precursor cells. Despite aggressive, multimodal therapies, the prognosis for recurrent PAX-FOXO1 fusion-negative RMS (FN-RMS) remains poor. Inducing differentiation in diseases defined by defective differentiation programs has led to curative therapies in cancers such as acute promyelocytic leukemia. A recent study showed that inducing differentiation slowed tumor growth and extended survival in a xenograft model of FN-RMS, identifying differentiation as a promising therapeutic target in FN-RMS. However, genes associated with differentiation are frequently found to be hijacked by tumor cells and repurposed for proinvasive programs. Therefore, better understanding of differentiation signaling and its relation to invasion could reveal novel therapeutic opportunities for patients with advanced FN-RMS. We hypothesize that ASAP1, an Arf GTPase-activating protein implicated in differentiation in normal cells and invasion in carcinoma, promotes progression by controlling proinvasive elements of differentiation signaling through focal adhesion assembly. ASAP1, an Arf GTPase-activating protein (Arf GAP), regulates integrin adhesion complexes, critical regulators of biologic processes such as proliferation, migration, and differentiation that are commonly dysregulated in cancer. ASAP1 is overexpressed in several cancers and correlates with increased metastasis and poor patient prognosis but has also been shown to promote differentiation. The mechanisms by which ASAP1 affects cancer progression and differentiation and the relationship between these effects are not yet understood. We found that ASAP1 is overexpressed in FN-RMS. ASAP1 overexpression inhibits proliferation in myoblasts, but not in FN-RMS. Knockdown of ASAP1 inhibits differentiation in both myoblast and FN-RMS cell lines, while overexpression enhances differentiation. Moreover, gene set enrichment analysis shows that myoblast differentiation-associated genes fail to become enriched upon knockdown of ASAP1. Finally, knockdown of Arf1 and Arf5, established binding partners of ASAP1, also blocks differentiation of FN-RMS cell lines, indicating that ASAP1 may regulate differentiation through its interaction with Arf GTPases. These data support our hypothesis that ASAP1 regulates the continuum of differentiation and invasion in FN-RMS. As a continuing test of the hypothesis, future studies will investigate focal adhesion assembly, dynamics, and signaling, which are processes known to be affected by ASAP1, as a mechanism for ASAP1-mediated regulation of myoblast differentiation. Citation Format: Katie E. Hebron, Olivia Feehan-Nelson, Xiaoying Jian, Sofia A. Girald, Paul A. Randazzo, Marielle E. Yohe. ASAP1 regulates differentiation in myoblasts and PAX-FOXO1 fusion-negative rhabdomyosarcoma [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 B32.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".