Abstract 996: Loss of alpha-dystroglycan laminin binding in epithelium-derived cancers is caused by silencing of <i>LARGE</i>
Bibliographic record
Abstract
Abstract Dystroglycan is a ubiquitously expressed cell membrane receptor that mediates interactions between cells and basement membranes in various epithelia. Dystroglycan is synthesized as a preprotein that is cleaved in two peptides: the transmembranal beta-dystroglycan, and the extracellular laminin receptor alpha-dystroglycan. In many epithelium-derived cancers, beta-dystroglycan is detected but alpha-dystroglycan has been reported to be absent. Here we report that alpha-dystroglycan is correctly expressed and trafficked to the cell membrane but lack its laminin-binding capabilities as a result of the silencing of the glycosyltransferase LARGE in a cohort of highly metastatic epithelial cell lines derived from breast, cervical, and lung cancers. As a result of this glycosylation defect, alpha-dystroglycan presents a lower MW on Western blot analysis. Exogenous expression of LARGE in these cancer cells restores the normal glycosylation and laminin-binding of alpha-dystroglycan leading to enhanced cell adhesion and reduced cell migration in vitro. The relevance of alpha-dystroglycan glycosylation in breast cancer is highlighted by the loss of the functionally active form of the receptor during mammary tumor growth in the mouse model for breast cancer MMTV-Neu(YD). Our findings demonstrate that LARGE repression underlies the defective dystroglycan-mediated cell adhesion that is observed in epithelium-derived cancer cells and uncovers dystroglycan hypo-glycosylation as factor in cancer progression. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 996.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".