CD95 maintains stem cell-like and non-classical EMT programs in primary human glioblastoma cells
Bibliographic record
Abstract
Glioblastoma (GBM) is one of the most aggressive types of cancer with limited therapeutic options and unfavorable prognosis. Stemness and non-classical epithelial-to-mesenchymal transition (ncEMT) features underlie the switch from normal to neoplastic states as well as resistance of tumor clones to current therapies. Therefore, identification of ligand/receptor systems maintaining this privileged state is needed to devise efficient cancer therapies. In this study, we show that the expression of CD95 associates with stemness and EMT features in GBM tumors and cells and serves as a prognostic biomarker. CD95 expression increases in tumors and with tumor relapse as compared with non-tumor tissue. Recruitment of the activating PI3K subunit, p85, to CD95 death domain is required for maintenance of EMT-related transcripts. A combination of the current GBM therapy, temozolomide, with a CD95 inhibitor dramatically abrogates tumor sphere formation. This study molecularly dissects the role of CD95 in GBM cells and contributes the rational for CD95 inhibition as a GBM therapy.
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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".