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Record W3047412501 · doi:10.1158/1538-7445.pedca19-b45

Abstract B45: Therapeutic potential of splicing in RMS: SRSF2 binding modulation controls MDM2 alternative splicing

2020· article· en· W3047412501 on OpenAlexaboutno aff
Matías Montes, Daniel F. Comiskey, Safiya Khurshid, Dawn S. Chandler

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
Fundersnot available
KeywordsMinigeneRNA splicingAlternative splicingSplicing factorBiologyExonExonic splicing enhancerGeneticsMdm2Cell biologyCancer researchGeneRNA

Abstract

fetched live from OpenAlex

Abstract MDM2 undergoes complex alternative splicing and one of its spliced isoforms, MDM2-ALT1, comprised of coding exons 3 and 12, is highly expressed in pediatric rhabdomyosarcoma, and its expression correlates with a poor disease prognosis. MDM2-ALT1 expression is also upregulated under conditions of cellular genotoxic stress, and this alternative splicing is conserved in the mouse Mdm2 gene. Furthermore, previous research from our lab has reported that the splicing factors SRSF1, FUBP1, and PTBP1 are involved in this regulation; nevertheless, the way that MDM2 splicing is controlled is not entirely understood. In this work, we explore the role of the splicing factor SRSF2/SC35 in the alternative splicing of MDM2, hypothesizing that this factor acts as a positive regulator, in both human and mouse, facilitating the production of the full-length MDM2 mature transcript. This splicing factor has been reported to be mutated in several cancers, including myelodysplastic syndromes and rhabdomyosarcoma. Moreover, using a minigene system that mimics the endogenous Mdm2 splicing in response to UV and cisplatinum-induced DNA damage and the CRISPR-Cas9 technology, we show that mutations in SRSF2 predicted binding sites alter Mdm2 alternative splicing. The CRISPR-engineered mutant cells that express this splice isoform show increased proliferation in an Arf/p19 null context. On the other hand, we show that by using antisense oligonucleotides working as splice-switching molecules that target the SRSF2 binding sites in the MDM2 pre-mRNA, we are able to shift the expression of the MDM2 splice isoforms to drive p53 target gene expression in p53 wild-type cells. Furthermore, in an effort to understand better the effect of the MDM2-ALT1 isoform in carcinogenesis, we performed the CRISPR-Cas9 technique to generate a mouse model expressing the cancer-associated spliced isoform. We expect the mouse to be a cancer-sensitized model that will give rise to RMS tumors and provide a preclinical model for testing splice-switching oligonucleotide therapies. Citation Format: Matias I. Montes, Daniel F. Comiskey, Safiya Khurshid, Dawn S. Chandler. Therapeutic potential of splicing in RMS: SRSF2 binding modulation controls MDM2 alternative splicing [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 B45.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 integrity0.0000.000
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 head0.069
GPT teacher head0.394
Teacher spread0.325 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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