Surface Expression of ASIC2 Inhibits the Amiloride-sensitive Current and Migration of Glioma Cells
Bibliographic record
Abstract
Gliomas are primary brain tumors with a complex biology characterized by antigenic and genomic heterogeneity and a propensity for invasion into normal brain tissue. High grade glioma cells possess a voltage-independent, amiloride-inhibitable, inward Na+ current. This current does not exist in normal astrocytes or low grade tumor cells. Inhibition of this conductance decreases glioma growth and cell migration making it a potential therapeutic target. Our previous results have shown that the acid-sensing ion channels (ASICs), members of the epithelial Na+ channel (ENaC)/degenerin (DEG) family of ion channels are part of this current pathway. We hypothesized that one member of the ENaC/DEG family, ASIC2, is retained intracellularly and that it is the lack of functional expression of ASIC2 at the cell surface that results in hyperactivity of this conductance in high grade gliomas. In this study we show that the chemical chaperone, glycerol, and the transcriptional regulator, sodium 4-phenylbutyrate, inhibit the constitutively activated inward current and reduce cell growth and migration in glioblastoma multiforme. The results suggest that these compounds induce the movement of ASIC2 to the plasma membrane, and once there, the basally active inward current characteristic of glioma cells is abolished by inherent negative regulatory mechanisms. This in turn compromises the ability of the glioma cell to migrate and proliferate. These results support the hypothesis that the conductance pathway in high grade glioma cells is comprised of ENaC/DEG subunits and that abolishing this channel activity promotes a reversion of a high grade glioma cell to a phenotype resembling that of normal astrocytes.
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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) | 0.001 | 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".