The Down-Regulation of Circ_0059707 in Acute Myeloid Leukemia Promotes Cell Growth and Inhibits Apoptosis by Regulating miR-1287-5p
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is the most common type of hematological malignancy. Recently, an increasing number of reports have shown that many circular RNAs can act as effective targets for AML. However, the roles of circ_0059707 in AML remain largely unclear. In this study, we found that the expression levels of circ_0059707 were significantly decreased in AML patients with respect to normal controls (p < 0.001). Low expression levels of circ_0059707 were also associated with a poor prognosis. Furthermore, circ_0059707 overexpression inhibited cell growth and promoted apoptosis in leukemia cells, compared with control cells. Circ_0059707- and empty plasmid-transfected cells were injected subcutaneously into BALB/c nude mice. We found that the tumor volume was significantly lower in mice in the circ_0059707 group than in control mice (p < 0.01). Nuclear pyknosis, nuclear fragmentation, nuclear dissolution, and cell necrosis were observed in the circ_0059707 group by HE staining. CircInteractome analysis showed that 25 microRNAs (miRNAs), including miR-1287-5p, ©-miR-1825, a©hsa-miR-326, may be potential targets for circ_0059707. The expression of these miRNAs was analyzed in both the GEO GSE51908 and the GSE142700 databases. miR-1287-5p expression was lower in AML patients compared with controls in both the GSE51908 and the GSE142700 datasets. Moreover, we demonstrated that miR-1287-5p expression was down-regulated in AML patients and up-regulated in circ_0059707-overexpressing cells. Collectively, our research demonstrated that the down-regulation of circ_0059707 was highly evident in de novo AML patients. Our analysis also demonstrated that circ_0059707 inhibited cell growth and promoted apoptosis by up-regulating miR-1287-5p.
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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".