Abstract 4329: In vivo visualization of epithelial-mesenchymal transition in real time using a rapidly tuneable E-cadherin
Bibliographic record
Abstract
Abstract The transformation of benign tumour cells to invasive, metastatic tumour cells involves the dynamic redeployment of factors involved in cell adhesion and motility collectively known as epithelial-mesenchymal transition (EMT). While the loss of E-cadherin localization at cell-cell junctions is a hallmark feature of EMT, the impact of E-cadherin re-expression and modulation in metastatic cancer cells at distinct steps of the metastatic cascade has not been explored. To address this, we developed an intravital imaging approach that allows us to visualize changes in behaviour of highly metastatic MDA-MB-231-LN breast cancer cells in real time using a dynamically tuneable form of E-cadherin. Here, we show that upon induction of E-cadherin in vivo, cell-cell adherens junctions begin to appear within 30 minutes, concurrent with the accumulation of plasma membrane-localized E-cadherin and the retraction of tumour cell protrusions and the induction of a rounded epithelial-like morphology. Furthermore, subsequent depletion of E-cadherin results in a rapid reversion to the mesenchymal morphology. These studies demonstrate that E-cadherin is sufficient to induce a rapid mesenchymal to epithelial transition in vivo, and that sustained E-cadherin expression is required to maintain this less invasive morphology. 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 4329.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".