Significance of Dysregulated Metadherin and MicroRNA-375 in Head and Neck Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it