Claudin 1 overexpression increases invasion and is associated with aggressive histological features in oral squamous cell carcinoma
Bibliographic record
Abstract
BACKGROUND: The authors have previously shown that overexpression of claudin 1 (CLDN1) is associated with advanced disease stage in oral squamous cell carcinomas (OSCCs). Their goal was to examine CLDN1 expression in a large series of primary OSCCs and to further investigate whether CLDN1 overexpression plays a role in invasion in OSCC. METHODS: CLDN1 gene expression levels were determined by quantitative real-time reverse transcription polymerase chain reaction (QRT-PCR) in 100 primary OSCCs. CLDN1 protein expression was examined by immunohistochemistry in 70 of 100 OSCCs. E-Cadherin protein levels were also assessed in 58 OSCCs. The authors performed a transwell Matrigel invasion assay for assessment of the invasive potential of CLDN1 overexpressing oral carcinoma cells. Western blotting and QRT-PCR were used to assess CLDN1 expression in transfected cells and controls. RESULTS: CLDN1 mRNA was increased (median = 18.5) in 79 of 100 OSCCs, compared with normal oral mucosa (expression = 1.0). CLDN1 overexpression was associated with angiolymphatic (P = .037) and perineural invasion (P = .051). CLDN1 was highly expressed in 48 of 70 (68%) OSCCs. E-Cadherin was lost or underexpressed in 49 of 58 (84%) OSCCs. The invasion assay showed that cells overexpressing CLDN1 have increased invasive potential, whereas small interfering RNA-mediated depletion of CLDN1 decreased the invasive potential of cells. CONCLUSIONS: CLDN1 overexpression is associated with angiolymphatic and perineural invasion, consistent with aggressive tumor behavior. Overexpression of CLDN1 protein is associated with increased invasiveness of oral carcinoma cells.
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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 | 0.001 | 0.001 |
| 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".