Reduction in gap junction intercellular communication promotes glioma migration
Bibliographic record
Abstract
// Qurratulain Aftab 1 , Wun-Chey Sin 1 , Christian C. Naus 1 1 Department of Cellular & Physiological Sciences, Life Sciences Institute, The University of British Columbia, Vancouver, BC Correspondence to: Christian C. Naus, e-mail: cnaus@interchange.ubc.ca Keywords: connexin, gap junction, glioma, migration Received: July 15, 2014 Accepted: February 19, 2015 Published: March 19, 2015 ABSTRACT Glioblastoma Multiforme (GBM), an aggressive form of adult brain tumor, is difficult to treat due to its invasive nature. One of the molecular changes observed in GBM is a decrease in the expression of the gap junction protein Connexin43 (Cx43); however, how a reduction in Cx43 expression contributes to glioma malignancy is still unclear. In this study we examine whether a decrease in Cx43 protein expression has a role in enhanced cell migration, a key feature associated with increased tumorigenicity. We used a 3D spheroid migration model that mimics the in vivo architecture of tumor cells to quantify migration changes. We found that down-regulation of Cx43 expression in the U118 human glioma cell line increased migration by reducing cell-ECM adhesion, and changed the migration pattern from collective to single cell. In addition gap junction intercellular communication (GJIC) played a more prominent role in mediating migration than the cytoplasmic interactions of the C-terminal tail. Live imaging revealed that reducing Cx43 expression enhanced relative migration by increasing the cell speed and affecting the direction of migration. Taken together our findings reveal an unexplored role of GJIC in facilitating collective migration.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".