SOX10 induces epithelial–mesenchymal transition and contributes to nasopharyngeal carcinoma progression
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate the role of SOX10 in nasopharyngeal carcinoma (NPC) and the underlying molecular mechanisms. METHODS: The expression of SOX10 was initially assessed in human NPC tissues and a series of NPC cell lines through quantitative real-time PCR (qRT-PCR) and Western blot. Then, cell proliferation, cycle, migration, and the invasiveness of NPC cells with knockdown of SOX10 were examined by MTT, flow cytometry, and Transwell migration and invasion assays, respectively. Finally, nude mice tumorigenicity experiments were performed to evaluate the effects of SOX10 on NPC growth and metastasis in vivo. RESULTS: SOX10 was significantly increased in NPC tissues and cell lines. In-vitro experiments revealed that loss of SOX10 obviously inhibited cell proliferation, migration, and invasiveness, as well as the epithelial-mesenchymal transition (EMT) process in NPC cells. In-vivo experiments further demonstrated that disrupted SOX10 expression restrained NPC growth and metastasis, especially in lung and liver. CONCLUSION: Taken together, our data confirmed the role of SOX10 as an oncogene in NPC progression, and revealed that SOX10 may serve as a novel biomarker for diagnosis of NPC, as well as a potential therapeutic target against this disease.
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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) | 0.002 | 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".