Prognostic significance of mucins in colorectal cancer with different DNA mismatch-repair status
Bibliographic record
Abstract
BACKGROUND: Expression of mucin antigen MUC1 and down regulation of MUC2 are associated with adverse prognosis in colorectal cancer (CRC), but their prognostic significance with respect to differing DNA mis- match repair (MMR) status is poorly understood. OBJECTIVE: To determine the prognostic significance of MUC1 and MUC2 in CRC with different MMR statuses. METHODS: Using the tissue microarray (TMA) technique, a series of 1420 unselected, non-consecutive CRC resections was subdivided into three groups: (1) MMR-proficient; (2) MLH1-negative; and (3) presumed hereditary non-polyposis colon cancer (HNPCC). Immunohistochemical analysis of MUC1 and MUC2 expression (>0%) and loss (0%) was performed, and the results were correlated with clinicopathological parameters. RESULTS: In MMR-proficient CRC, MUC1 expression was more frequently found in tumours with higher tumour stage (p=0.004) and higher tumour grade (p=0.041) and loss of MUC2 was associated with higher tumour stage (p=0.028), node stage (p=0.001), presence of vascular invasion (p=0.028) and worse survival (p=0.034). In MLH1-negative CRC, MUC2 loss was associated with the presence of lymph node metastasis (p=0.028) and worse survival (p=0.015), but there was no association between MUC1 expression and clinicopathological features. In presumed HNPCC, MUC1 expression and MUC2 loss were not associated with clinicopathological parameters. CONCLUSIONS: Mucins have a prognostic significance in sporadic CRC, but not in hereditary CRC. Loss of MUC2 is an adverse prognostic factor in MMR-proficient and MLH1-negative CRC, whereas MUC1 expression is associated with tumour progression in MMR-proficient CRC only.
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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 | 0.002 |
| 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".