Up-regulation of ITCH is associated with down-regulation of LATS1 during tumorigenesis and progression of cervical squamous cell carcinoma
Bibliographic record
Abstract
PURPOSE: The molecular basis for the normal cervical squamous epithelium advance to cervical intraepithelial neoplasia (CIN I, CIN II, CIN III) and ultimately to invasive carcinoma has not yet been defined. We explored the abnormal expression of ITCH (AIP4) and its degrading substrate Large Tumor Suppressor 1 (LATS1) in CINs and cervical cancers, which might disrupt the normal differentiation of the cervical epithelia and contribute to the tumorigenesis of the cervix. METHODS: A series of 110 samples, comprising 24 cases of normal cervical tissues, 20 cases of CIN I, 26 cases of CIN II/ III and 40 cases of squamous cancer of the cervix (SCC) were used for analysis. The expression of ITCH and LATS1 was assessed in the tissues by immunohistochemistry, and statistically analyzed by SPSS13.0. RESULTS: The increased nuclear and cytoplasmic expression levels of ITCH and the low membrane expression of LATS1 were strongly associated with the malignant transformation of the cervical epithelium and the histological progression of SCC. Moreover, the high nuclear and cytoplasmic expression levels of ITCH were significantly correlated with clinical stage (P=0.036, P=0.003, respectively) and tumor size (P=0.046,P=0.039, respectively); the low membrane expression of LATS1 was significantly correlated with clinical stage (P=0.036)and tumor size (P=0.023). Both the nuclear and cytoplasmic expression levels of ITCH were inversely associated with the membrane expression of LATS1 in cervical tissues (P<0.001, P<0.001, respectively). CONCLUSIONS: ITCH up-regulation and LATS1 down-regulation were closely associated with tumorigenesis and progression of SCC; therefore, inhibiting the expression of ITCH may serve as a novel therapeutic strategy for impeding the progression of precancerous neoplasm to SCC.
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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".