Autophagy Inhibition Enhances Sunitinib Efficacy in Clear Cell Ovarian Carcinoma
Bibliographic record
Abstract
Abstract Clear cell ovarian carcinoma (CCOC) is an aggressive form of epithelial ovarian cancer that exhibits low response rates to systemic therapy and poor patient outcomes. Multiple studies in CCOC have revealed expression profiles consistent with increased hypoxia, and our previous data suggest that hypoxia is correlated with increased autophagy in CCOC. Hypoxia-induced autophagy is a key factor promoting tumor cell survival and resistance to therapy. Recent clinical trials with the molecular-targeted receptor tyrosine kinase (RTK) inhibitor sunitinib have demonstrated limited activity. Here, it was evaluated whether the hypoxia–autophagy axis could be modulated to overcome resistance to sunitinib. Importantly, a significant increase in autophagic activity was found with a concomitant loss in cell viability in CCOC cells treated with sunitinib. Pharmacologic inhibition of autophagy with the lysosomotropic analog Lys05 inhibited autophagy and enhanced sunitinib-mediated suppression of cell viability. These results were confirmed by siRNA targeting the autophagy-related gene Atg5. In CCOC tumor xenografts, Lys05 potentiated the antitumor activity of sunitinib compared with either treatment alone. These data reveal that CCOC tumors have an autophagic dependency and are an ideal tumor histotype for autophagy inhibition as a strategy to overcome resistance to RTK inhibitors like sunitinib. Implications: This study shows that autophagy inhibition enhances sunitinib-mediated cell death in a preclinical model of CCOC. Mol Cancer Res; 15(3); 250–8. ©2017 AACR.
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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) | 0.000 | 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 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".