Connexin 43 mediated gap junctional communication enhances breast tumor cell diapedesis in culture
Bibliographic record
Abstract
INTRODUCTION: Metastasis involves the emigration of tumor cells through the vascular endothelium, a process also known as diapedesis. The molecular mechanisms regulating tumor cell diapedesis are poorly understood, but may involve heterocellular gap junctional intercellular communication (GJIC) between tumor cells and endothelial cells. METHOD: To test this hypothesis we expressed connexin 43 (Cx43) in GJIC-deficient mammary epithelial tumor cells (HBL100) and examined their ability to form gap junctions, establish heterocellular GJIC and migrate through monolayers of human microvascular endothelial cells (HMVEC) grown on matrigel-coated coverslips. RESULTS: HBL100 cells expressing Cx43 formed functional heterocellular gap junctions with HMVEC monolayers within 30 minutes. In addition, immunocytochemistry revealed Cx43 localized to contact sites between Cx43 expressing tumor cells and endothelial cells. Quantitative analysis of diapedesis revealed a two-fold increase in diapedesis of Cx43 expressing cells compared to empty vector control cells. The expression of a functionally inactive Cx43 chimeric protein in HBL100 cells failed to increase migration efficiency, suggesting that the observed up-regulation of diapedesis in Cx43 expressing cells required heterocellular GJIC. This finding is further supported by the observation that blocking homocellular and heterocellular GJIC with carbenoxolone in co-cultures also reduced diapedesis of Cx43 expressing HBL100 tumor cells. CONCLUSION: Collectively, our results suggest that heterocellular GJIC between breast tumor cells and endothelial cells may be an important regulatory step during metastasis.
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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) | 0.001 | 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".