miR‐5191 acts as a tumor suppressor in salivary adenoid cystic carcinoma by targeting Notch‐2
Bibliographic record
Abstract
OBJECTIVE: This study sought to investigate the effect of miR-5191 on proliferation, invasion and metastasis in salivary adenoid cystic carcinoma (SACC). MATERIALS AND METHODS: The differential expression level of miR-5191 between 5 primary tumor and adjacent non-neoplastic samples, and in two SACC cell lines was detected by quantitative real-time PCR. Cell proliferation, invasion, and migration were performed, followed by luciferase reporter assay and western analysis. The effect of miR-5191 on cell proliferation and apoptosis was evaluated by cell growth and apoptosis assay. The function of miR-5191 in SACC tumorigenesis and metastasis in vivo was investigated by nude mice experiment. The associations between miR-5191/Notch-2 expression and clinicopathological features were analyzed. RESULTS: miR-5191 was downregulated in primary tumor tissues and SACC-LM cells. By targeting Notch-2, miR-5191 expression level affected the migration, invasion, and proliferation of SACC cells. Overexpression of miR-5191 inhibited the expression levels of Notch-2, followed by the decreased expression of c-Myc, Bcl-2, Hes-1, Hey-1, and Cyclin D1. In vivo, miR-5191 overexpression suppressed the SACC tumorigenesis and pulmonary metastasis in mice. In SACC patients, higher expression of miR-5191 was related to better prognoses and lower possibility of metastasis. CONCLUSIONS: miR-5191 acts as a tumor suppressor in SACC by targeting Notch-2.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".