Genetic alterations of epithelial polarity genes are associated with loss of polarity in invasive breast cancer
Bibliographic record
Abstract
Breast cancer remains a leading cause of cancer-related death for women. The stepwise development of breast cancer through preinvasive to invasive disease is associated with progressive disruption of cellular and tissue organization. Apical-basal polarity is thought to be a barrier to breast cancer development, but the extent and potential mechanisms that contribute to disrupted polarity are incompletely understood. To investigate the cell polarity status of invasive breast cancers, we performed multiplex imaging of polarity markers on tissue cores from 432 patients from a spectrum of grades, stages and molecular subtypes. Apical-basal cell polarity was lost in 100% of cells in all cases studied, indicating that loss of epithelial polarity may be a universal feature of invasive breast cancer. We then analyzed genomic events from the TCGA dataset for an 18-gene set of core polarity genes. Coamplification of polarity genes with established breast oncogenes was found, which is consistent with functional cooperation within signaling amplicons. Gene-expression levels of several polarity genes were significantly associated with survival, and protein localization of Par6 correlated with higher grade, nodal metastasis and molecular subtype. Finally, multiple hotspot mutations in protein-protein interaction domains critical for cell polarity were identified. Our data indicate that genomic events likely contribute to pervasive disruption of epithelial polarity observed in invasive breast cancer.
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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".