Sialidase NEU4 is involved in glioblastoma stem cell survival
Bibliographic record
Abstract
The human sialidase, NEU4, has emerged as a possible regulator of neuronal differentiation and its overexpression has been demonstrated to promote the acquisition of a stem cell-like phenotype in neuroblastoma cells. In this paper, we demonstrated that glioblastoma stem cells (GSCs) isolated from glioblastoma multiforme (GBM) cell lines and patients' specimens as neurospheres are specifically marked by the upregulation of NEU4; in contrast, the expression of NEU4 is very low in non-neurosphere-differentiated GBM cells. We showed that NEU4 silencing by miRNA or a chemical inhibitor of its catalytic activity triggered key events in GSCs, including (a) the activation of the glycogen synthase kinase 3β, with the consequent inhibition of Sonic Hedgehog and Wnt/β-catenin signalling pathways; (b) the decrease of the stem cell-like gene expression and marker signatures, evidenced by the reduction of NANOG, OCT-4, SOX-2, CD133 expression, ganglioside GD3 synthesis, and an altered protein glycosylation profile; and (c) a significant decrease in GSCs survival. Consistent with this finding, increased NEU4 activity and expression induced in the more differentiated GBM cells by the NEU4 agonist thymoquinone increased the expression of OCT-4 and GLI-1. Thus, NEU4 expression and activity appeared to help to determine the molecular signature of GSCs and to be closely connected with their survival properties. Given the pivotal role played by GSCs in GBM lethality, our results strongly suggest that NEU4 inhibition could significantly improve current therapies against this tumour.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".