Dual mTORC1/2 Blockade Inhibits Glioblastoma Brain Tumor Initiating Cells <i>In Vitro</i> and <i>In Vivo</i> and Synergizes with Temozolomide to Increase Orthotopic Xenograft Survival
Bibliographic record
Abstract
PURPOSE: The EGFR and PI3K/mTORC1/2 pathways are frequently altered in glioblastoma (GBM), but pharmacologic targeting of EGFR and PI3K signaling has failed to demonstrate efficacy in clinical trials. Lack of relevant models has rendered it difficult to assess whether targeting these pathways might be effective in molecularly defined subgroups of GBMs. Here, human brain tumor-initiating cell (BTIC) lines with different combinations of endogenous EGFR wild-type, EGFRvIII, and PTEN mutations were used to investigate response to the EGFR inhibitor gefitinib, mTORC1 inhibitor rapamycin, and dual mTORC1/2 inhibitor AZD8055 alone and in combination with temozolomide (TMZ) EXPERIMENTAL DESIGN: In vitro growth inhibition and cell death induced by gefitinib, rapamycin, AZD8055, and TMZ or combinations in human BTICs were assessed by alamarBlue, neurosphere, and Western blotting assays. The in vivo efficacy of AZD8055 was assessed in subcutaneous and intracranial BTIC xenografts. Kaplan-Meier survival studies were performed with AZD8055 and in combination with TMZ. RESULTS: We confirm that gefitinib and rapamycin have modest effects in most BTIC lines, but AZD8055 was highly effective at inhibiting Akt/mTORC2 activity and dramatically reduced the viability of BTICs regardless of their EGFR and PTEN mutational status. Systemic administration of AZD8055 effectively inhibited tumor growth in subcutaneous BTIC xenografts and mTORC1/2 signaling in orthotopic BTIC xenografts. AZD8055 was synergistic with the alkylating agent TMZ and significantly prolonged animal survival. CONCLUSION: These data suggest that dual inhibition of mTORC1/2 may be of benefit in GBM, including the subset of TMZ-resistant GBMs.
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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 | 0.004 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".