Cell Polarity Proteins in Breast Cancer Progression
Bibliographic record
Abstract
Breast cancer, one of the leading causes of cancer related death in women worldwide, is a heterogeneous disease with diverse subtypes that have different properties and prognoses. The developing mammary gland is a highly proliferative and invasive tissue, and some of the developmental programs may be aberrantly activated to promote breast cancer progression. In the breast, luminal epithelial cells exhibit apical-basal polarity, and the failure to maintain this organizational structure, due to disruption of polarity complexes, is implicated in promoting hyperplasia and tumors. Therefore, understanding the mechanisms underlying loss of polarity will contribute to our knowledge of the early stages leading to the pathogenesis of the disease. In this review, we will discuss recent findings that support the idea that loss of apical-basal cell polarity is a crucial step in the acquisition of the malignant phenotype. Oncogene induced loss of tissue organization shares a conserved cellular mechanism with developmental process, we will further describe the role of the individual polarity complexes, the Par, Crumbs, and Scribble, to couple cell division orientation and cell growth. We will examine symmetric or asymmetric cell divisions in mammary stem cell and their contribution to the development of breast cancer subtypes and cancer stem cells. Finally, we will highlight some of the recent advances in our understanding of the molecular mechanisms by which changes in epithelial polarity programs promote invasion and metastasis through single cell and collective cell modes. J. Cell. Biochem. 117: 2215-2223, 2016. © 2016 Wiley Periodicals, Inc.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".