Stationary-to-migratory transition in glioblastoma stem-like cells driven by a fatty acid-binding protein 7-RXR<b>α</b> neurogenic pathway
Bibliographic record
Abstract
BACKGROUND: Glioblastoma (GBM) stem-like cells (GSCs) are crucial drivers of treatment resistance and tumor recurrence. While the concept of "migrating" cancer stem cells was proposed a decade ago, the roles and underlying mechanisms of the heterogeneous populations of GSCs remain poorly defined. METHODS: Cell migration using GBM cell lines and patient-derived GSCs was examined using Transwell inserts and the scratch assay. Single-cell RNA sequencing data analysis were used to map GSC drivers to specific GBM cell populations. Xenografted mice were used to model the role of brain-type fatty acid-binding protein 7 (FABP7) in GBM infiltration and expansion. The mechanism by which FABP7 and its fatty acid ligands promote GSC migration was examined by gel shift and luciferase gene reporter assays. RESULTS: A subpopulation of FABP7-expressing migratory GSCs was identified, with FABP7 upregulating SOX2, a key modulator for GBM stemness and plasticity, and ZEB1, a prominent factor in GBM epithelial-mesenchymal transition and invasiveness. Our data indicate that GSC migration is driven by nuclear FABP7 through activation of RXRα, a nuclear receptor activated by polyunsaturated fatty acids (PUFAs). CONCLUSION: Infiltrative progression in GBM is driven by migratory GSCs through activation of a PUFA-FABP7-RXRα neurogenic pathway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".