Protein kinase Cι and SRC signaling define reciprocally related subgroups of glioblastoma with distinct therapeutic vulnerabilities
Bibliographic record
Abstract
We report that atypical protein kinase Cι (PKCι) is an oncogenic driver of glioblastoma (GBM). Deletion or inhibition of PKCι significantly impairs tumor growth and prolongs survival in murine GBM models. GBM cells expressing elevated PKCι signaling are sensitive to PKCι inhibitors, whereas those expressing low PKCι signaling exhibit active SRC signaling and sensitivity to SRC inhibitors. Resistance to the PKCι inhibitor auranofin is associated with activated SRC signaling and response to a SRC inhibitor, whereas resistance to a SRC inhibitor is associated with activated PKCι signaling and sensitivity to auranofin. Interestingly, PKCι- and SRC-dependent cells often co-exist in individual GBM tumors, and treatment of GBM-bearing mice with combined auranofin and SRC inhibitor prolongs survival beyond either drug alone. Thus, we identify PKCι and SRC signaling as distinct therapeutic vulnerabilities that are directly translatable into an improved treatment for GBM.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".