miRNAs 484 and 210 regulate Pax-5 expression and function in breast cancer cells
Bibliographic record
Abstract
Recent studies have enabled the identification of important factors regulating cancer progression, such as paired box gene 5 (Pax-5). This transcription factor has consistently been associated to B-cell cancer lesions and more recently solid tumors including breast carcinoma. Although Pax-5 downstream activity is relatively well characterized, aberrant Pax-5 expression in a cancer-specific context is poorly understood. To investigate the regulation of Pax-5 expression, we turned to micro RNAs (miRNAs), small non-coding RNA molecules that regulate key biological processes. Extensive studies show that miRNA deregulation is prevalent in cancer lesions. In this study, we aim to elucidate a causal link between differentially expressed miRNAs in cancer cells and their putative targeting of Pax-5-dependent cancer processes. Bioinformatic prediction tools indicate that miRNAs 484 and 210 are aberrantly expressed in breast cancer and predicted to target Pax-5 messenger RNA (mRNA). Through conditional modulation of these miRNAs in breast cancer cells, we demonstrate that miRNAs 484 and 210 inhibit Pax-5 expression and regulate Pax-5-associated cancer processes. In validation, we show that these effects are probably caused by direct miRNA/mRNA interaction, which are reversible by Pax-5 recombinant expression. Interestingly, miRNAs 484 and 210, which are both overexpressed in clinical tumor samples, are also modulated during epithelial-mesenchymal transitioning and hypoxia that correlate inversely to Pax-5 expression. This is the first study demonstrating the regulation of Pax-5 expression and function by non-coding RNAs. These findings will help us better understand Pax-5 aberrant expression within cancer cells, creating the possibility for more efficient diagnosis and treatments for cancer patients.
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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".