Epigenetic silencing of miRNA-9 is associated with HES1 oncogenic activity and poor prognosis of medulloblastoma
Bibliographic record
Abstract
BACKGROUND: microRNA-9 is a key regulator of neuronal development aberrantly expressed in brain malignancies, including medulloblastoma. The mechanisms by which microRNA-9 contributes to medulloblastoma pathogenesis remain unclear, and factors that regulate this process have not been delineated. METHODS: Expression and methylation status of microRNA-9 in medulloblastoma cell lines and primary samples were analysed. The association of microRNA-9 expression with medulloblastoma patients' clinical outcome was assessed, and the impact of microRNA-9 restoration was functionally validated in medulloblastoma cells. RESULTS: microRNA-9 expression is repressed in a large subset of MB samples compared with normal fetal cerebellum. Low microRNA-9 expression correlates significantly with the diagnosis of unfavourable histopathological variants and with poor clinical outcome. microRNA-9 silencing occurs via cancer-specific CpG island hypermethylation. HES1 was identified as a direct target of microRNA-9 in medulloblastoma, and restoration of microRNA-9 was shown to trigger cell cycle arrest, to inhibit clonal growth and to promote medulloblastoma cell differentiation. CONCLUSIONS: microRNA-9 is a methylation-silenced tumour suppressor that could be a potential candidate predictive marker for poor prognosis of medulloblastoma. Loss of microRNA-9 may confer a proliferative advantage to tumour cells, and it could possibly contribute to disease pathogenesis. Thus, re-expression of microRNA-9 may constitute a novel epigenetic regulation strategy against medulloblastoma.
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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".