Comprehensive MicroRNA Profiling for Head and Neck Squamous Cell Carcinomas
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Bibliographic record
Abstract
PURPOSE: The objective of this study is to investigate the significance of microRNAs (miRNA) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC). EXPERIMENTAL DESIGN: A global miRNA profiling was done on 51 formalin-fixed archival HNSCC samples using quantitative reverse transcription-PCR approach, correlated with patients' clinical parameters. Functional characterization of HNSCC-associated miRNAs was conducted on three HNSCC cell lines. Cell viability and proliferation were investigated using MTS and clonogenic assays, respectively; cell cycle analyses were assessed using flow cytometry. RESULTS: Thirty-eight of the 117 (33%) consistently detected miRNAs were significantly differentially expressed between malignant versus normal tissues. Concordant with previous reports, overexpression of miR-21, miR-155, let-7i, and miR-142-3p and underexpression of miR-125b and miR-375 were detected. Upregulation of miR-423, miR-106b, miR-20a, and miR-16 as well as downregulation of miR-10a were newly observed. Exogenous overexpression of miR-375 in HNSCC cell lines reduced proliferation and clonogenicity and increased cells in sub-G(1). Similar cellular effects were observed in knockdown studies of the miR-106b-25 cluster but with accumulation of cells in G(1) arrest. No major difference was detected in miRNA profiles among laryngeal, oropharyngeal, or hypopharyngeal cancers. miR-451 was found to be the only significantly overexpressed miRNA by 4.7-fold between nonrelapsed and relapsed patients. CONCLUSION: We have identified a group of aberrantly expressed miRNAs in HNSCC and showed that underexpression of miR-375 and overexpression of miR-106b-25 cluster might play oncogenic roles in this disease. Further detailed examinations of miRNAs will provide opportunities to dissect the complex molecular abnormalities driving HNSCC progression.
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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 | 0.001 | 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 it