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Abstract B014: Metabolic reprogramming in high-grade sarcomas: repurposing anti-cholesterol agents as a novel therapeutic strategy

2022· article· en· W4296131277 on OpenAlexaffabout
Jen Dorsey, Yael Babichev, Rosemarie E. Venier, Richard Marcellus, Rima Al‐awar, Linda Z. Penn, Albiruni Abdul Razak, Brendan C. Dickson, Eric Chen, Irene L. Andrulis, Jay S. Wunder, Rebecca A. Gladdy

Bibliographic record

VenueClinical Cancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity Health NetworkOntario Institute for Cancer ResearchMount Sinai HospitalSickKids FoundationLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsSimvastatinPI3K/AKT/mTOR pathwayMevalonate pathwayPharmacologyCancer researchDoxorubicinIn vivoProtein kinase BCell growthStatinMedicineBiologyChemotherapySignal transductionInternal medicineCell biologyEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction and Objective: Undifferentiated pleomorphic sarcoma (UPS) and leiomyosarcoma (LMS) are treated with surgery, radiation, and/or chemotherapy. Current drug therapies, such as doxorubicin, have limited response rates and severe toxicities. We performed a drug screen with over 3000 compounds on four patient-derived UPS cell lines and uncovered sensitivity to simvastatin, which inhibits the rate limiting enzyme in the mevalonate pathway. Statins are well tolerated drugs used to lower cholesterol in patients with hypercholesterolemia. The mevalonate pathway can be exploited by cancer through metabolic reprogramming and phosphoinositide 3-kinase/mammalian target of rapamycin (PI3K/mTOR) signaling to enhance proliferation. Thus, the goals of our study are to define the mechanism(s) responsible for simvastatin sensitivity and determine the efficacy when combined with doxorubicin in vivo. Hypothesis: Dysregulation of the mevalonate pathway and/or PI3K/mTOR pathway will render certain high-grade sarcomas sensitive to simvastatin. Methods: We confirmed simvastatin sensitivity in UPS, as well as in LMS cell lines, with dose-response curves. We investigated the mechanisms whereby simvastatin inhibits UPS and LMS viability with immunoblotting and flow cytometry. Proliferation was quantified using a cell proliferation dye. To assess in vivo efficacy and toxicity of simvastatin we performed a murine study with an established xenograft UPS model from our lab. We are currently assessing the efficacy of this novel combination in an LMS xenograft. Results: We found decreased phosphorylated AKT (pAKT ser473) and increased rates of active caspase-3 in most sensitive UPS cell lines with simvastatin (1uM) treatment. This indicates downregulation of PI3K/mTOR signaling and an increase in apoptosis, respectively. Importantly, these effects were rescued with the addition of mevalonate (200uM), an effector immediately downstream of the rate limiting enzyme that statins inhibit, indicating an on-target effect. In four sensitive LMS cell lines treated with simvastatin (1.5uM or 2uM) a decrease in pAKT ser473 is not consistently seen, revealing that downregulation of PI3K/mTOR signalling may not be a universal mechanism. Furthermore, in some UPS and LMS cell lines there was a significant reduction in proliferation with simvastatin + doxorubicin (0.5uM) treatment (p<0.05). Our in vivo study demonstrated that simvastatin (50mg/kg) in combination with doxorubicin (1.2mg/kg) reduced the volume of UPS tumors in mice. Furthermore, mice treated with combination therapy had higher concentrations of simvastatin and doxorubicin within the tumor than those treated with either single agent. However, this study was not designed to look at pharmacokinetics (PK), so to confirm these results a PK study is underway in an LMS xenograft. Conclusion: UPS and LMS are sensitive to simvastatin, suggesting these sarcomas rely on metabolic reprogramming to sustain viability. Thus, simvastatin may be a novel therapy for certain sarcoma patients. Citation Format: Jen Dorsey, Yael Babichev, Rosemarie E. Venier, Richard Marcellus, Rima Al-awar, Linda Z. Penn, Albiruni A. Razak, Brendan C. Dickson, Eric Chen, Irene L. Andrulis, Jay Wunder, Rebecca A. Gladdy. Metabolic reprogramming in high-grade sarcomas: repurposing anti-cholesterol agents as a novel therapeutic strategy [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B014.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.192
GPT teacher head0.484
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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