PI3K/AKT/mTOR inhibition in combination with doxorubicin is an effective therapy for leiomyosarcoma
Bibliographic record
Abstract
BACKGROUND: Leiomyosarcoma (LMS) is a common type of soft tissue sarcoma that responds poorly to standard chemotherapy. Thus the goal of this study was to identify novel selective therapies that may be effective in leiomyosarcoma by screening cell lines with a small molecule library comprised of 480 kinase inhibitors to functionally determine which signalling pathways may be critical for LMS growth. METHODS: LMS cell lines were screened with the OICR kinase library and a cell viability assay was used to identify potentially effective compounds. The top 10 % of hits underwent secondary validation to determine their EC50 and immunoblots were performed to confirm selective drug action. The efficacy of combination drug therapy with doxorubicin (Dox) in vitro was analyzed using the Calcusyn program after treatment with one of three dosing schedules: concurrent treatment, initial treatment with a selective compound followed by Dox, or initial treatment with Dox followed by the selective compound. Single and combination drug therapy were then validated in vivo using LMS xenografts. RESULTS: Compounds that targeted PI3K/AKT/mTOR pathways (52 %) were most effective. EC50s were determined to validate these initial hits, and of the 11 confirmed hits, 10 targeted PI3K and/or mTOR pathways with EC50 values <1 μM. We therefore examined if BEZ235 and BKM120, two selective compounds in these pathways, would inhibit leiomyosarcoma growth in vitro. Immunoblots confirmed on-target effects of these compounds in the PI3K and/or mTOR pathways. We next investigated if there was synergy with these agents and first line chemotherapy doxorubicin (Dox), which would allow for earlier introduction into patient care. Only combined treatment of BEZ235 and Dox was synergistic in vitro. To validate these findings in pre-clinical models, leiomyosarcoma xenografts were treated with single agent and combination therapy. BEZ235 treated xenografts (n = 8) demonstrated a decrease in tumor volume of 42 % whereas combining BEZ235 with Dox (n = 8) decreased tumor volume 68 % compared to vehicle alone. CONCLUSIONS: In summary, this study supports further investigation into the use of PI3K and mTOR inhibitors alone and in combination with standard treatment in leiomyosarcoma patients.
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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 | 0.000 | 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) | 0.000 | 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".