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Record W4379983451 · doi:10.1158/1538-7445.am2023-23

Abstract 23: Development of a biallelic<i>Dicer1</i>mutant mouse strain for studying the pathogenesis of DICER1 syndrome-associated cancer

2023· article· en· W4379983451 on OpenAlexaff
Yemin Wang, Shary Chen, Janine Senz, Maxwell Douglas, Shelby Thornton, Yana Moscovitz, C. Blake Gilks, David G. Huntsman, Gregg B. Morin

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyDicerMissense mutationCancer researchGeneticsRibonuclease IIIAlleleMutationNull alleleCarcinogenesisPathogenesisCancerGeneImmunologyTransfectionRNA interference

Abstract

fetched live from OpenAlex

Abstract DICER1 encodes a RNase III enzyme that post-transcriptionally controls gene expression through governing microRNA (miRNA) biogenesis. We and others have demonstrated that somatic mutations of DICER1 at its RNase IIIb domain metal binding sites, impairing its capability to produce mature miRNAs from the 5P strand of miRNA precursors, occur recurrently in a broad spectrum of cancers associated with the DICER1 syndrome that affects children and youths predominantly. The biallelic DICER1 mutations in these cancers challenge the two-hit hypothesis theory of traditional tumour suppressors, but it remains unproven whether these mutations are sufficient to drive tumorigenesis. The lack of biology relevant preclinical models has also hindered the understanding the pathogenesis. Here, we developed a genetically engineered mouse strain that expresses an inducible knockin Dicer1 missense mutation (Dicer1+/fl-D1693N), equivalent to the DICER1 RNase IIIb hotspot mutation D1709N in human cancers. This conditional strain behaves as a null allele due to an aberrant splicing event without Cre-mediated recombination. When crossed with a well-characterized conditional null Dicer1 strain (Dicer1fl/fl), the resulting compound heterozygous strain (Dicer1fl/fl-D1693N), acts as a hemizygous wildtype allele that is converted to a hemizygous missense mutation allele upon Cre-mediated recombination, reflecting the genetic status of DICER1 in DICER1 syndrome-associated cancer. When crossing with the anti-Mullerian hormone receptor 2 (Amhr2) driven cre strain (Amhr2+/cre), the biallelic Dicer1 mutation resulted in infertility in females by impairing the development of oviduct and endometrium and ultimately drove the development of multicystic tubal and intra-uterine tumours. Histologically, these murine tumors resemble human Müllerian adenosarcoma and other DICER1 syndrome-associated sarcomas. Molecular analysis of these murine tumours validated the miRNA biogenesis defects in 5P-miRNA production, uncovered the activation of the myc signaling and identified that loss of let-7 family miRNAs may drive the transcriptomic rewiring and malignant transformation. Thus, this first DICER1 syndrome-associated murine cancer model faithfully recapitulates the biology of human cancer and provides a unique tool for future investigation and therapeutic development. Citation Format: Yemin Wang, Shary Chen, Janine Senz, Maxwell Douglas, Shelby Thornton, Yana Moscovitz, C. Blake Gilks, David Huntsman, Gregg Morin. Development of a biallelicDicer1mutant mouse strain for studying the pathogenesis of DICER1 syndrome-associated cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 23.

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)0.001
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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.006

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 head0.196
GPT teacher head0.431
Teacher spread0.235 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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