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Enterolactone Suppress Prostate Cancer (PC) Cells Linking Cellular Metabolism and TGFβ

2019· article· en· W3176062496 on OpenAlexaff
Franklyn De Silva

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlutathione Transferases and Polymorphisms
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLNCaPCancer researchCancer cellEnterolactoneProstate cancerCancerUnfolded protein responseChemistryPharmacologyMedicineBiologyEndoplasmic reticulumInternal medicineCell biology

Abstract

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PC cells susceptible to androgen deprivation therapy (ADT) and relapse of aggressive resistant cells are a principal cause of mortality. Cell metabolism plays a key role in cancer prevention, treatment and disease free survival. Naturally occurring polyphenolic lignans are capable of modulating serum and hepatic cholesterol levels. Diverse plant lignanoid constituents can be precursors of enterolactone (ENL) a mammalian lignan. Despite the information gathered throughout the years, the effects and mechanisms of action of bioactive lignans (LN) are not completely understood. As drug discovery efforts continue to move towards multi‐targeted and combination effects, ENL's drug‐like characteristics warrants further attention to fully grasp LN enriched products' and ENL analogs' potential use in the clinic. Additionally, a clinical trial concluded by our lab with an appropriate LN enriched product indicates that it can provide a clinically relevant dose without significant toxicities. Furthermore, dysregulated cells can exhibit endoplasmic reticulum (ER) stress. A link between LNs anti‐cancer effects might exist through the ability of FLNs to modulate ER stress and metabolism in dysregulated cells such as cancer. TGFβ mediated signaling is reported to be involved in the epithelial mesenchymal transition (EMT) of PC cells especially with metastases after ADT. Hypothesis ENL's anti‐cancer effects in PC cells are a result of increased ER stress and decreased TGFβ. ENL alone did not cause cytotoxicity (sulforhodamine B) to non‐cancerous cells at 1000μM, but to cancerous cells at 50 – 200μM (LNCap, PC3, C4‐2, RWPE‐1, and 3T3‐L1). Binding assay (PolarScreen™ PPARγ‐competitor), transactivation assay (Cignal reporter), and uptake assay (2‐NBD glucose) revealed ENL as a PPARϒ partial agonist compared with controls Rosiglitazone (full agonist) and FMOC (partial agonist). ENL modulated metabolism markers (FASN, SREBPs, LDLR, PPARϒ, GLUT1, PKM2), reduced EMT markers (TGFβ) and increased ER stress markers (ATF4, CHOP, GADD34, GRP58). ENL reduced mitochondrial redox function (Alamar blue) and caused mitochondrial toxicity (Cell‐Glo ATP) in (non)glycolytic phenotype representing cells using glucose and galactose media. ENL sensitized select anticancer drugs; microtubule inhibitors (Cabazitaxel and Docetaxel), and AR / synthesis inhibitors (Enzalutamide and Abiraterone) to decrease cell viability (Calcein AM, colony forming assay) and cell motility (migration/invasion, cell adherent, wound healing assay) and increased apoptosis (Caspase 3/7 Assay). Microscopy using F‐actin stain (Phalloidin conjugate) revealed changes in cytoskeleton. There might be a novel target in the regulation of metabolism and cell motility, by ENL connecting PPARγ and TGFβ. ENL ↓metabolism, modulate ATP generation, ↑oxidative/ER stress, activate pro‐apoptotic factors leading to mitochondrial toxicity related cell death, and reduced cell motility. All these suggest that the combination of enterolactone with chemotherapy could be an efficacious therapeutic strategy for the treatment of prostate cancer. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.214
Teacher spread0.208 · 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 teacher head, 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".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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