Significance of Dysregulated Metadherin and MicroRNA-375 in Head and Neck Cancer
Bibliographic record
Abstract
PURPOSE: Despite recent improvements in local control of head and neck cancers (HNC), distant metastasis remains a major cause of death. Hence, further understanding of HNC biology, and in particular, the genes/pathways driving metastasis is essential to improve outcome. EXPERIMENTAL DESIGN: Quantitative reverse transcriptase PCR (qRT-PCR) was used to measure the expression of miR-375 and metadherin (MTDH) in HNC patient samples. Targets of miR-375 were confirmed using qRT-PCR, Western blot analysis, and luciferase assays. Phenotypic effects of miR-375 reexpression and MTDH knockdown were assessed using viability (MTS), clonogenic survival, cell migration/invasion, as well as in vivo tumor formation assays. The prognostic significance of miR-375 or MTDH in nasopharyngeal carcinoma (NPC) was determined by comparing low versus high expression groups. RESULTS: MiR-375 expression was significantly reduced (P = 0.01), and conversely, MTDH was significantly increased (P = 0.0001) in NPC samples. qRT-PCR, Western blots, and luciferase assays corroborated MTDH as a target of miR-375. Reexpression of miR-375 and siRNA knockdown of MTDH both decreased cell viability and clonogenic survival, cell migration/invasion, as well as in vivo tumor formation. NPC patients whose tumors expressed high levels of MTDH experienced significantly lower survival and, in particular, higher distant relapse rates (5-year distant relapse rates: 26% vs. 5%; P = 0.005). CONCLUSIONS: Dysregulation of miR-375 and MTDH may represent an important oncogenic pathway driving human HNC progression, particularly distant metastases, which is now emerging as a major cause of death for HNC patients. Hence, targeting this pathway could potentially be a novel therapeutic strategy by which HNC patient outcome could be improved.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".