Dicer-to-Argonaute switch controls biogenesis of oncogenic miRNA
Bibliographic record
Abstract
Abstract miRNAs are post-transcriptional regulators of gene expression, controlling biological processes from development to pathogenesis. We asked whether the reshaped functional miRNA landscape in cancers is driven by altered transcription of its precursors, or altered biogenesis and maturation of miRNAs. Integrated analysis of genomic and transcriptomic data in 9,111 samples across 10 cancer types and healthy tissues revealed a recurrent genomic switch from DICER-dependent to non-canonical Argonaute-mediated, DICER-independent, miRNA biogenesis. Experimental validation in AGO2-amplified clinical samples and cancer cell lines confirmed that canonical miRNAs can undergo maturation in a DICER-independent manner, and that elevated Argonaute levels promote selective maturation of the oncogenic miR-106b/25 cluster as shown by the altered ratio of mature miRNA to immature pri-miRNA levels. The preferential maturation of these oncogenic miRNAs, whose processing bypasses DICER1, promotes cancer progression and predicts poor prognosis. This highlights the evolution of non-canonical AGO2-dependent oncomiR processing as a novel driver pathway in cancer.
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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) | 0.000 | 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) | 0.001 | 0.000 |
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".