The importance of MUC1 cellular localization in patients with breast carcinoma
Bibliographic record
Abstract
BACKGROUND: The MUC1 mucin is present on the apical surface of normal secretory epithelia. In breast carcinoma, MUC1 expression is variable in amount and cellular localization, the significance of which is controversial. The authors undertook a detailed analysis of staining pattern combined with a comprehensive literature review to better understand the role of MUC1 in breast carcinoma. METHODS: Seventy-one patients with breast carcinoma were examined for MUC1, beta-catenin, and E-cadherin staining patterns. These data were compared with data from 25 articles from the literature examining the expression of MUC1 in breast carcinoma. RESULTS: All invasive carcinomas showed some MUC1 staining. In invasive ductal carcinomas, MUC1 was detected in the apical membrane (15%), cytoplasm (93%), or circumferential membrane (13%), with 81% of tumors showing a mixture of patterns. Tumors with low overall MUC1 expression (< or = 50% positive tumor cells) had a higher nuclear grade than tumors with high overall MUC1 expression (> 50%; P = 0.01). Tumors with high and low cytoplasmic expression had no difference in nuclear grade (P > 0.3). Circumferential membrane staining was correlated with positive lymph node status (P = 0.011). CONCLUSIONS: In the literature, similar findings prevailed in which overall MUC1 expression was increased in lower grade (10 of 14 studies), estrogen receptor positive (8 of 13 studies) tumors and was associated with a better prognosis (8 of 13 studies). High cytoplasmic staining was associated with a worse prognosis, an association that was not explained by differences in histologic grade. Thus, the presence of MUC1 in the majority of tumor cells is associated with better differentiated tumors and with an improved prognosis. However, aberrantly localized MUC1 in the tumor cell cytoplasm or nonapical membrane is associated with a worse prognosis.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".