Abstract 271: Influence of autophagy modulation on synergistic interactions of lapatinib and mTOR targeted agents in HER2-amplified lapatinib resistant breast cancer models in vitro and in vivo
Bibliographic record
Abstract
Abstract Background: Resistance against HER2 targeted agents ultimately limits the therapeutic success in patients with HER2-positive breast cancer. It was shown that PIK3CA mutations contribute to lapatinib resistance and achieving control of a downstream PI3K/mTOR signaling is necessary for optimal effectiveness of HER2 blockade. We and others have shown that catalytic mTORC1/2 inhibitors reverse lapatinib resistance and inhibit growth of HER2-overexpressing breast cancer models in vitro and in vivo. However, activity of these targeted agents is hindered by the compensatory and adaptive mechanisms that arise to assure cell survival. One of the pro-survival responses is cytoprotective autophagy induced by lapatinib and mTORC1/2 inhibitors. Thus, we examined whether impairing autophagy could augment activity of lapatinib/mTORC1/2 inhibitors combinations in lapatinib-resistant breast cancer models. Methods: The combination of lapatinib with catalytic mTORC1/2 inhibitors KU-0063794 (KU) or AZD2014 (AZD) was evaluated in vitro and in vivo in lapatinib resistant PIK3CA mutated HER2-overexpressing/amplified MDA-MB-361, JIMT-1 and MDA-MB-453 breast cancer models in the presence of siRNA-based (Atg7, Beclin-1) and pharmacological (hydroxychloroquine (HCQ)) inhibitors of autophagy. Results: In vitro lapatinib/mTORC1/2 combinations elevated autophagy to a greater extent that either compound alone. Genetic or pharmacological inhibition of treatment-induced autophagy further decreased cell viability, suggesting that autophagy was playing a cytoprotective role in this context. In vivo, lapatinib and AZD combinations achieved effective tumor growth inhibition of 98%, 111% and 152% in MDA-MB-361, JIMT-1 and MDA-MB-453 models respectively, however addition of HCQ did not significantly enhance this therapeutic response (p>0.05). Conclusion: Negligible effects of HCQ in vivo in tumors treated with lapatinib/AZD combinations may be attributed to ineffective inhibition of autophagy-mediated survival signals that, if significantly blocked, could increase efficacy of the treatment. Utilizing carrier nanotechnology to optimize delivery of HCQ to the tumor site and molecular analysis of HCQ-engendered off target effects on survival and proliferation pathways in tumor tissue are being pursued. Citation Format: Wieslawa H. Dragowska, Sherry A. Weppler, William Wei Chu, Norman S. Chow, Jenna S. Rawji, Ashleen S. Prasad, Karen A. Gelmon, Sharon M. Gorski, Marcel B. Bally. Influence of autophagy modulation on synergistic interactions of lapatinib and mTOR targeted agents in HER2-amplified lapatinib resistant breast cancer models in vitro and in vivo. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 271.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".