Abstract 942: Decreasing the AKT feedback loop with arsenic trioxide enhances mTORi anti-tumor effects.
Bibliographic record
Abstract
Abstract Inhibitors of the mammalian target of rapamycin (mTORi) have exciting clinical activity in renal cell carcinoma, breast cancer, and some hematologic malignancies. However, the potential benefits of mTOR inhibition may be limited by a feedback mechanism that results in AKT activation. While mTORi can block important growth promoting events downstream from TORC1, an increased activation of AKT may inhibit apoptotic signals. Increased AKT activity resulting from mTOR inhibition is a result of increased growth factor/MAPK signaling or alternatively, via the second mTOR complex, TORC2. We have previously shown that arsenic trioxide (ATO) inhibits AKT activity and in some cases, decreases AKT protein expression. Therefore, we propose that combining ATO and mTORi may circumvent the AKT feedback loop and increase the anti-tumor effects of these drugs. Using a panel of breast cancer cell lines, we find that ATO, at clinically achievable doses, can enhance the inhibitory activity of the mTORi temsirolimus in some, but not all, cell lines. MCF-7, MDA-MB-468, and SKBR3, but not T47D cells, exhibit a decrease in cell number that correlates with an increase in the percentage of cells arrested in the G0/G1 phase of the cell cycle. In all these cell lines, temsirolimus treatment resulted in AKT activation, which was decreased by concomitant ATO treatment only in MCF-7, MDA-MB-468, and SKBR3 cell lines. Treatment with mTORi also results in activated ERK signaling, which is decreased with ATO co-treatment in MCF7, MDA-MB-468, and SKBR3. These data indicate that, when effective, ATO decreases phospho-AKT and ERK concomitantly. We next tested the toxicity and efficacy of rapamcyin plus ATO combination therapy in a MDA-MB-468 xenograft model. The combination was well-tolerated, and rapamycin did not increase ATO-induced liver enzyme levels. In contrast, the combination was significantly more effective at inhibiting tumor growth. The increased anti-tumor effects corresponded with ATO decreasing the rapamycin-induced phospho-Akt, phospho-ERK, and phospho-4EBP1 within the tumor. Therefore, we propose that adding ATO to mTORi treatment may overcome the negative feedback loop by decreasing MAPK and activated AKT in addition to the downstream targets of mTOR/TORC1. Citation Format: Cynthia Guilbert, Matthew G. Annis, Peter Siegel, Wilson H. Miller, Koren K. Mann. Decreasing the AKT feedback loop with arsenic trioxide enhances mTORi anti-tumor effects. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 942. doi:10.1158/1538-7445.AM2013-942
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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) | 0.003 | 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".