Induction of apoptosis in glioblastoma cells by an atypical protein kinase C pseudosubstrate peptide.
Bibliographic record
Abstract
BACKGROUND: Glioblastoma responds poorly to standard chemotherapy agents. The expression of a mutant, constitutively-active EGF receptor (EGFRvIII) is common in glioblastoma and contributes to chemotherapy resistance. We have assessed the cytotoxicity of an inhibitor of atypical protein kinase C on glioblastoma cells expressing EGFRvIII. MATERIALS AND METHODS: Glioblastoma cells were treated with a peptide-based atypical protein kinase C inhibitor. Apoptosis was assessed by morphological criteria, TUNEL assays, annexin V staining, Hoechst staining and colorimetric assays for cell viability. RESULTS: The atypical protein kinase C inhibitor induced rapid apoptosis in glioblastoma cells expressing EGFRvIII and killed these cells with an IC50 of 16 microM. Glioblastoma cells which do not express EGFRvIII were less sensitive. Apoptosis was not affected by caspase inhibitors and occurred without detectable caspase activation. CONCLUSION: An atypical protein kinase C inhibitor induces rapid apoptosis in glioblastoma cells by a caspase-independent mechanism that is enhanced, rather than inhibited, by EGFRvIII.
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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".