Fragile histidine triad protein expression in nonsmall cell lung cancer and correlation with Ki-67 and with p53
Bibliographic record
Abstract
Fragile histidine triad (FHIT) is a tumour suppressor gene, which is altered in a variety of epithelial tumours, including lung cancer. Biochemical and functional pathways of its tumourigenicity are not yet understood. Its role in tumour proliferation is particularly controversial. The purpose of this study was to correlate the expression of FHIT protein in nonsmall cell lung cancer (NSCLC) with tumour proliferation as estimated by Ki-67 antigen and with p53, a suppressor gene. FHIT, Ki-67 and p53 expression were evaluated by immunohistochemistry in 119 resected NSCLC. Altogether, 58 tumours were negative (expression <10%) for FHIT. The median expression in tumours was 15% positive cells, in comparison with 100% in normal matched lung tissue. The expression was as strong as in normal tissue in only 19 cases. FHIT expression was significantly lower in squamous cell carcinoma (SCC) (5%) than in adenocarcinoma (ADC) (64%). The median expression of Ki-67 was 20% and 69% of tumours were positives (expression >10%). Ki-67 expression was significantly higher in SCC (33.3%) than in ADC (10%). The loss of FHIT protein was not correlated with the expression of p53 (median: 7.5%, 58% of positive tumours for a cut-off of 10% of positive cells) or Ki-67. But percentage of labelled cells for p53 and Ki-67 were significantly correlated. The results suggest that for fragile histidine triad, the pathway of tumourigenesis is independent of p53 and of tumoural proliferation, as reported previously in vitro.
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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".