Biallelic <i>Dicer1</i> Mutations in the Gynecologic Tract of Mice Drive Lineage-Specific Development of <i>DICER1</i> Syndrome–Associated Cancer
Bibliographic record
Abstract
DICER1 is an RNase III enzyme essential for miRNA biogenesis through cleaving precursor-miRNA hairpins. Germline loss-of-function DICER1 mutations underline the development of DICER1 syndrome, a rare genetic disorder that predisposes children to cancer development in organs such as lung, gynecologic tract, kidney, and brain. Unlike classical tumor suppressors, the somatic "second hit" in DICER1 syndrome-associated cancers does not fully inactivate DICER1 but impairs its RNase IIIb activity only, suggesting a noncanonical two-hit hypothesis. Here, we developed a genetically engineered conditional compound heterozygous Dicer1 mutant mouse strain that fully recapitulates the biallelic DICER1 mutations in DICER1 syndrome-associated human cancers. Crossing this tool strain with tissue-specific Cre strains that activate Dicer1 mutations in gynecologic tract cells at two distinct developmental stages revealed that embryonic biallelic Dicer1 mutations caused infertility in females by disrupting oviduct and endometrium development and ultimately drove cancer development. These multicystic tubal and intrauterine tumors histologically resembled a subset of DICER1 syndrome-associated human cancers. Molecular analysis uncovered accumulation of additional oncogenic events (e.g., aberrant p53 expression, Kras mutation, and Myc activation) in murine Dicer1 mutant tumors and validated miRNA biogenesis defects in 5P miRNA strand production, of which, loss of let-7 family miRNAs was identified as a putative key player in transcriptomic rewiring and tumor development. Thus, this DICER1 syndrome-associated cancer model recapitulates the biology of human cancer and provides a unique tool for future investigation and therapeutic development. SIGNIFICANCE: Generation of a Dicer1 mutant mouse model establishes the oncogenicity of missense mutations in the DICER1 RNase IIIb domain and provides a faithful model of DICER1 syndrome-associated cancer for further investigation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".