miRNA-34a decreases ovarian cancer cell proliferation and chemoresistance by targeting HDAC1
Bibliographic record
Abstract
This study aimed to explore the roles of miRNA-34a (miR-34a) in ovarian cancer (OC) cells and uncover possible mechanisms. The proliferation of OC cells was measured with an MTT assay and soft agar colony formation assay. TargetScan analysis, real-time PCR, and a luciferase reporter assay were used to demonstrate the downstream target of miR-34a in OC cells. HDAC1 expression levels were detected by immunoblot analysis. miR-34a inhibited the proliferation of SKOV3 and OVCA433 cells and enhanced cisplatin sensitivity in cisplatin-resistant SKOV3cp cells. The results of TargetScan analysis, real-time PCR, and luciferase reporter assay confirmed that miR-34a downregulated HDAC1 expression by directly targeting the 3'-UTR of HDAC1 mRNA. The overexpression of HDAC1 decreased cisplatin sensitivity and promoted proliferation in OC cells. MTT assay and soft agar colony formation assay showed that HDAC1 overexpression blocked the suppressive effects of miR-34a on SKOV3 cell proliferation. In addition, treatment with the miR-34a mimic partially recovered the cisplatin sensitivity of SKOV3cp cells, whereas HDAC1 overexpression blocked the above phenomena caused by treatment with the miR-34a mimic. miR-34a exhibited suppressive effects on OC cells via directly binding and downregulating HDAC1 expression, which subsequently decreased the resistance to cisplatin and suppressed proliferation in OC cells.
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) | 0.000 | 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".