MétaCan
Menu
Back to cohort

Abstract A003: ASAP1 regulates myogenic differentiation in rhabdomyosarcoma by modulating YAP localization

2022· article· en· W4296132037 on OpenAlexaboutno aff
Katie E. Hebron, Olivia Feehan-Nelson, Angela Kim, Xiaoying Jian, Sofia A Girald, Paul A. Randazzo, Marielle E. Yohe

Bibliographic record

VenueClinical Cancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsnot available
Fundersnot available
KeywordsRhabdomyosarcomaGene knockdownCancer researchBiologyDifferentiation therapyCellular differentiationC2C12Transcription factorCell biologyMyocyteMyogenesisMedicineCell cultureSarcomaPathologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Despite aggressive, multimodal therapies, the prognosis of patients with refractory or recurrent rhabdomyosarcoma (RMS) has not improved in four decades. RMS is thought to arise due to defective differentiation in skeletal muscle precursor cells. Differentiation-inducing therapy may improve outcomes for RMS patients with advanced disease. In RAS-mutant PAX fusion-negative RMS (FN-FMS), targeting ERK1/2 activation through MEK1/2 inhibition (MEKi) induces differentiation, slows tumor growth, and extends survival in preclinical studies. However, the duration of therapeutic response is short lived. Identifying additional targets for differentiation therapy is necessary. We propose that ASAP1, an Arf GTPase-activating protein (Arf GAP) highly expressed in FN-RMS and implicated in breast and colorectal cancer progression as well as osteogenic and retinal endothelium differentiation, contributes to FN-RMS differentiation. We find that knockdown (KD) of ASAP1 inhibits differentiation in myoblasts and FN-RMS cells, and its overexpression enhances differentiation. Moreover, myogenic differentiation-associated genes are not enriched upon loss of ASAP1. We discover that KD of ASAP1 homologs, ASAP2 and ASAP3, also blocks differentiation. However, loss of a paralogous Arf GAP, ARAP1, does not, indicating that ASAP regulates differentiation through a mechanism not explained by GAP activity alone. Interestingly, KD of Arf1 or Arf5, small GTPases inactivated by ASAP, also blocks differentiation of FN-RMS, suggesting a novel relationship between Arf and ASAP. Using RNAseq, qPCR, and immunoblotting techniques, we show that loss of ASAP blocks myogenic transcription factor expression. To determine the mechanism by which ASAP1 regulates myogenic transcription factor expression, we investigate the PI3K/AKT, MAPK, and Hippo pathways, which are known to be regulated by ASAP1. While the PI3K/AKT and MAPK pathways are unaffected, downstream components of the Hippo pathway are modulated by ASAP1 KD in FN-RMS cells treated with MEKi. YAP and TAZ are transcriptional coactivators that promote proliferation. Upon Hippo pathway activation, YAP/TAZ activity is blocked by phosphorylation at a nuclear exclusion site. Using cell fractionation and immunoblotting techniques, we find that induction of differentiation by MEKi increases TAZ phosphorylation, excluding it from the nucleus and blocking pro-proliferative transcription. Further, upon ASAP1 KD, TAZ phosphorylation is blocked, restoring nuclear localization, and inhibiting MEKi-induced differentiation. In conclusion, we discover that ASAP1 regulates MEKi-induced differentiation of FN-RMS cells by modulating TAZ localization and supports targeting the YAP pathway as a strategy for FN-RMS differentiation therapy. Our work also identifies ASAP1 as a potential effector of Arf1 activity, a novel interaction of these two proteins. The results described herein provide a deeper understanding of differentiation in FN-RMS and establish the groundwork for advancing differentiation therapy in FN-RMS. Citation Format: Katie E. Hebron, Olivia Feehan-Nelson, Angela Kim, Xiaoying Jian, Sofia A Girald, Paul Randazzo, Marielle E. Yohe. ASAP1 regulates myogenic differentiation in rhabdomyosarcoma by modulating YAP localization [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A003.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.071
GPT teacher head0.432
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueClinical Cancer ResearchSame topicCancer-related gene regulationFrench-language works237,207