Novel small RNA expression libraries uncover hsa-miR-30b and hsa-miR-30c as important factors in anoikis resistance
Bibliographic record
Abstract
MicroRNAs (miRNAs) have been widely studied in order to elucidate their biological functions. MicroRNA microarrays or miRNA overexpression libraries generated by synthesis and cloning of individual miRNAs have been used to study their different roles. In this work, we have developed a novel methodology to express mature miRNAs and other small RNAs from a double convergent RNA polymerase III promoter. We show that the generated miRNAs function similarly to those processed from primary transcripts or pri-miRNAs. This system allowed us to produce a lentiviral library expressing the whole population of small RNAs present in a metastatic cell line. A functional screening using this library led to the identification of hsa-miR-30b and hsa-miR-30c as negative regulators of cell death induced by loss of attachment (anoikis). Importantly, we demonstrated that the acquisition of anoikis resistance via these miRNAs is achieved through down-regulation of caspase 3 expression. Moreover, overexpression of these miRNAs resulted in a decrease of other types of caspase 3-dependent cell death and enhanced the survival of MCF10A acinar cells in morphogenesis assays, suggesting a putative role as oncomirs. In summary, this novel methodology provides a powerful and effective way for identifying novel small RNAs involved in a particular biological process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".