MicroRNA‐196a promotes an oncogenic effect in head and neck cancer cells by suppressing annexin A1 and enhancing radioresistance
Bibliographic record
Abstract
Radiotherapy is a major treatment modality for head and neck squamous cell carcinoma (HNSCC). Up to 50% of patients with locally advanced disease relapse after radical treatment and there is therefore a need to develop predictive bomarkers for clinical use that allow the selection of patients who are likely to respond. MicroRNA (miRNA) expression profiling of a panel of HNSCC tumours with and without recurrent disease after surgery and radiotherapy detected miR-196a as one of the highest upregulated miRNAs in the poor prognostic group. To further study the role of miR-196a, its expression was determined in eight head and neck cancer cell lines. Overexpression of miR-196a in HNSCC cells, with low endogenous miR-196a expression, significantly increased cell proliferation, migration and invasion, and induced epithelial to mesenchymal transition. Conversely, miR-196a knockdown in cells with high endogenous expression levels significantly reduced oncogenic behaviour. Importantly, overexpression of miR-196a increased radioresistance of cells as measured by gamma H2AX staining and MTT survival assay. Annexin A1 (ANXA1), a known target of miR-196a, was found to be directly modulated by miR-196a as measured by luciferase assay and confirmed by Western blot analysis. ANXA1 knockdown in HNSCC exhibited similar phenotypic effects to miR-196a overexpression, suggesting the oncogenic effect of miR-196a may at least be partly regulated through suppression of ANXA1. In conclusion, this study identifies miR-196a as a potential important biomarker of prognosis and response of HNSCC to radiotherapy. Furthermore, our data suggest that miR-196a and/or its target gene ANXA1 could represent important therapeutic targets in HNSCC.
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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".