Expression of Versican 3′-Untranslated Region Modulates Endogenous MicroRNA Functions
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Bibliographic record
Abstract
BACKGROUND: Mature microRNAs (miRNAs) are single-stranded RNAs that regulate post-transcriptional gene expression. In our previous study, we have shown that versican 3'UTR, a fragment of non-coding transcript, has the ability to antagonize miR-199a-3p function thereby regulating expression of the matrix proteins versican and fibronectin, and thus resulting in enhanced cell-cell adhesion and organ adhesion. However, the impact of this non-coding fragment on tumorigenesis is yet to be determined. METHODS AND FINDINGS: Using computational prediction confirmed with in vitro and in vivo experiments, we report that the expression of versican 3'UTR not only antagonizes miR-199a-3p but can also lower its steady state expression. We found that expression of versican 3'UTR in a mouse breast carcinoma cell line, 4T1, decreased miR-199a-3p levels. The decrease in miRNA activity consequently translated into differences in tumor growth. Computational analysis indicated that both miR-199a-3p and miR-144 targeted a cell cycle regulator, Rb1. In addition, miR-144 and miR-136, which have also been shown to interact with versican 3'UTR, was found to target PTEN. Expression of Rb1 and PTEN were up-regulated synergistically in vitro and in vivo, suggesting that the 3'UTR binds and modulates miRNA activities, freeing Rb1 and PTEN mRNAs for translation. In tumor formation assays, cells transfected with the 3'UTR formed smaller tumors compared with cells transfected with a control vector. CONCLUSION: Our results demonstrated that a 3'UTR fragment can be used to modulate miRNA functions. Our study also suggests that miRNAs in the cancer cells are more susceptible to degradation, due to its interaction with a non-coding 3'UTR. This non-coding component of mRNA may be used retrospectively to modulate miRNA activities.
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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 it