OS10 - 147 Tumor-Associated Astrocytes Promote Glioma Invasion via Cx43
Bibliographic record
Abstract
Although genetic mutations are usually responsible for the initial tumor formation and progression, changes in the microenvironment also have a critical role in facilitating this process. Many ''untransformed'' cells infiltrate the tumors, and recent evidence suggests cancer cells can ‘reprogram’ normal cells by miRNAs, which are small, non-coding RNA molecules that regulate several protein targets. One prominent feature of glioma pathology is massive gliosis, an inflammatory response consisting of reactive astrocytes, in and around the tumor. We show that expression of Cx43, a major gap junction protein in astrocytes, is significantly enhanced in astrocytes at the tumor border. Using a mouse model consisting of syngeneic intracranial implantation of GL261 glioma cells into Nestin-Cre:Cx43fl/fl mice in which Cx43 is selectively eliminated in astrocytes, we demonstrate that reduction of astrocytic Cx43 decreases the dissemination of glioma cells from the tumor core. Similarly, knocking down Cx43 in astrocytes also reduces glioma invasion in a co-culture of glioma cells and astrocytes. By comparing the microRNA profiles of the astrocytes before and after co-culture with human glioma cells, we have identified a miR-5096 that appears to reprogram astrocytes to enhance the invasiveness of glioma cells. We are now examining whether we can prevent glioma cells from invading the brain and establishing recurrent secondary tumors by stopping the exchange of materials between glioma cells and astrocytes through eliminating Cx43 channel activity.
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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".