<i>LINC00641</i> contributes to nasopharyngeal carcinoma cell malignancy through <i>FOXD1</i> upregulation at the post-transcriptional level
Bibliographic record
Abstract
Nasopharyngeal carcinoma (NPC) is a common tumor in the head and neck and is prevalent in China, especially in the southern regions. Molecular mechanisms have attracted much attention in NPC research. FOXD1 has been reported to be a tumor promoter in various cancers. The present study was designed to explore the function of FOXD1 in NPC cells. Functional analyses, including the trypan blue staining assay, EdU and JC-1 assay, and flow cytometry analysis, revealed that FOXD1 facilitated NPC cell proliferation and inhibited NPC cell apoptosis. Next, by means of “starBase” database and mechanism analyses, such as RIP assay, RNA pull-down assay and luciferase reporter assay, miR-378a-3p was found to target FOXD1 and negatively regulate FOXD1 expression in NPC cells. Moreover, miR-378a-3p plays a suppressive role in NPC cells. LINC00641 was identified as a sponge of miR-378a-3p and positively modulated FOXD1 expression in NPC cells. Finally, a series of rescue assays indicated that LINC00641 accelerated NPC cell proliferation and hindered NPC cell apoptosis through FOXD1 upregulation. In conclusion, the present study demonstrated an innovative ceRNA mechanism of LINC00641/miR-378a-3p/FOXD1 in NPC cells, which might provide new insights into NPC treatment.
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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 | 0.001 |
| 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) | 0.003 | 0.001 |
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".