<scp>MiR</scp>‐548k suppresses apoptosis in breast cancer cells by affecting <scp>PTEN</scp>/<scp>PI3K</scp>/<scp>AKT</scp> signaling pathway
Bibliographic record
Abstract
Breast cancer is the most aggressive and fatal form of cancer among women globally. Although the role of some miRNAs that are often dysregulated in breast cancer has been deciphered, the regulatory function of others still remains unknown. The current study was aimed at determining the biological role and underlying mechanism of miR-548k in breast cancer. In this study, the significant overexpression of miR-548k in breast cancer tissues compared to adjacent normal tissues was confirmed. Also, bioinformatics analysis indicated that PTEN, as a negative regulator of PI3K/AKT signaling pathway, was a potential target of miR-548k, and its expression was downregulated in breast cancer tissues rather than normal tissues. Furthermore, the ectopic increase of miR-548k decreased the expression of PTEN in breast cancer, suggesting that PTEN is one of the potential downstream targets of miR-548k. Besides, functional analysis was conducted to assess the capability of miR-548k to alter apoptosis along with the changed expression levels of miR-548k in breast cancer cells. Based on this investigation, forced increase of miR-548k disrupted programmed cell death in MCF-7 cells. Apart from this, in silico study of miR-548 family supported its association with the main components of PI3K/Akt signaling pathway, opening a prospective research area in cancer therapy. In brief, suppression of PTEN partly mediated by miR-548k diminished apoptosis and promoted cell proliferation through PI3K/Akt pathway in breast cancer, suggesting a novel therapeutic axis, miR-548k/PTEN/ PI3K/Akt, for treatment of breast cancer in the future.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".