Dual inhibition of autophagy and the AKT pathway in prostate cancer
Bibliographic record
Abstract
Genetic inactivation of PTEN through either gene deletion or mutation is common in metastatic prostate cancer, leading to activation of the phosphoinositide 3-kinase (PI3K-AKT) pathway, which is associated with poor clinical outcomes. The PI3K-AKT pathway plays a central role in various cellular processes supporting cell growth and survival of tumor cells. To date, therapeutic approaches to develop inhibitors targeting the PI3K-AKT pathway have failed in both pre-clinical and clinical trials. We showed that a novel AKT inhibitor, AZD5363, inhibits the AKT downstream pathway by reducing p-MTOR and p-RPS6KB/p70S6K. We specifically reported that AZD5363 monotherapy induces G2 growth arrest and autophagy, but fails to induce significant apoptosis in PC-3 and DU145 prostate cancer cell lines. Blocking autophagy using pharmacological inhibitors (3-methyladenine, chloroquine and bafilomycin A 1) or genetic inhibitors (siRNA targeting ATG3 and ATG7) enhances cell death induced by AZD5363 in these prostate cancer cells. Importantly, the combination of AZD5363 with chloroquine significantly reduces tumor volume compared with the control group, and compared with either drug alone in prostate tumor xenograft models. Taken together, these data demonstrate that AKT inhibitor AZD5363, synergizes with the lysosomotropic inhibitor of autophagy, chloroquine, to induce apoptosis and delay tumor progression in prostate cancer models that are resistant to monotherapy, with AZD5363 providing a new therapeutic approach potentially translatable to patients.
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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 | 0.001 |
| 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".