EZH2 Protein Expression Associates with the Early Pathogenesis, Tumor Progression, and Prognosis of Non–Small Cell Lung Carcinoma
Bibliographic record
Abstract
PURPOSE: Enhancer of zeste homolog 2 (EZH2) promotes carcinogenesis by epigenetically silencing tumor suppressor genes. We studied EZH2 expression by immunohistochemistry in a large series of non-small cell lung carcinomas (NSCLC) in association with tumor characteristics and patient outcomes. EXPERIMENTAL DESIGN: EZH2 immunohistochemistry expression was analyzed in 265 normal and premalignant bronchial epithelia, 541 primary NSCLCs [221 squamous cell carcinomas (SCC) and 320 adenocarcinomas] and 36 NSCLCs with paired brain metastases. An independent set of 91 adenocarcinomas was also examined. EZH2 expression was statistically correlated with clinico-pathological information, and EGFR/KRAS mutation status. RESULTS: EZH2 expression was significantly (P < 0.0001) higher in SCCs compared with adenocarcinomas and in brain metastasis relative to matched primary tumors (P = 0.0013). EZH2 expression was significantly (P < 0.0001) elevated in bronchial preneoplastic lesions with increasing severity. In adenocarcinomas, higher EZH2 expression significantly correlated with younger age, cigarette smoking, and higher TNM stage (P = 0.02 to P < 0.0001). Higher EZH2 expression in adenocarcinoma was associated with worse recurrence-free survival (RFS; P = 0.025; HR = 1.54) and overall survival (OS; P = 0.0002; HR = 1.96). Furthermore, lung adenocarcinomas with low EZH2 levels and high expression of the lineage-specific transcription factor, TTF-1, exhibited significantly improved RFS (P = 0.009; HR = 0.51) and OS (P = 0.0011; HR = 0.45), which was confirmed in the independent set of 91 adenocarcinomas. CONCLUSION: In lung, EZH2 expression is involved in early pathogenesis of SCC and correlates with a more aggressive tumor behavior of adenocarcinoma. When EZH2 and TTF-1 expressions are considered together, they serve as a prognostic marker in patients with surgically resected lung adenocarcinomas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".