Impaired Autophagy Mediates Resistance to Low-Dose Metronomic Cyclophosphamide Chemotherapy
Bibliographic record
Abstract
Low-dose metronomic (LDM) chemotherapy was developed to overcome resistance to standard, maximum tolerated dose (MTD) chemotherapy by shifting the primary treatment target from the highly adaptive tumor cells to diploid endothelial cells. As such, LDM chemotherapy exerts potent antiangiogenic effects. However, it became rapidly apparent that LDM chemotherapy is subject to resistance on its own, albeit by distinct mechanisms compared to MTD chemotherapy. To address the lack of detailed knowledge on the mechanisms of resistance to LDM chemotherapy, we decided to analyze the characteristics of prostate and breast cancer models with stable acquired resistance to LDM cyclophosphamide (CPA). Whereas our studies suggest that compensatory angiogenic activity does not account for such resistance in a major way, we identified low autophagic activity of tumor cells to be associated with resistance to LDM CPA. In addition, autophagy inhibition by using chloroquine in the PC-3 human prostate cancer model, or genetically engineered autophagy deficiency in immortalized baby mouse kidney cell tumors reversed the antitumor effects of LDM CPA. These findings contrast with observations from others showing that autophagy inhibition might enhance the antitumor effects of vascular endothelial growth factor (VEGF) targeted antiangiogenic therapy. On the other hand, the impact of autophagy modulation in cancer is known to be highly context-dependent. Since a subset of malignancies is expected to have intrinsic autophagy defects, assessing the autophagy status of tumors may become a tool to select patients for VEGF pathway targeted versus LDM antiangiogenic therapy. Keywords: Autophagy, cyclophosphamide, low-dose metronomic chemotherapy, maximum tolerated dose chemotherapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".