Peroxisome Proliferator Activated Receptor Gamma (PPARγ) Activation by Enterolactone Enhances Endoplasmic Reticulum Stress to Sensitize Anti‐cancer Agents
Bibliographic record
Abstract
The limitations of anticancer drugs bespeak a need for a multi‐target, yet safe approach that effectively thwarts cell survival adaptations. Tumor cells with endoplasmic reticulum (ER) stress evoke an adaptive mechanism, the unfolded protein response, for survival. This has become a promising drug target for tumors that upregulate protein synthesis and therefore depend on continuous protein folding to meet the demand. Clear therapeutic prospects exist for PPARγ inducing natural products given their multi‐target activity. PPARγ, a subfamily of the nuclear receptor superfamily can interfere with proliferation, angiogenesis, and differentiation in various cell types and disfavor carcinogenesis. Flaxseed lignans (FLNs) have putative health benefits and evidence to target key cancer survival pathways. Recent studies in our lab demonstrated safety and tolerability of a FLN‐enriched complex in frail and healthy elderly at pharmacological doses and blood levels of total lignans following chronic daily dosing of the FLN‐enriched complex consistent with ability of lignans to exert pharmacological activity. A transactivation assay and glucose uptake assay revealed enterolactone (ENL) as a potential PPARγ partial agonist. We hypothesize that combination of mammalian lignan ENL with clinically relevant anticancer drugs will cause chronic ER stress and in turn enhance anti‐tumor activity in‐vitro . We concluded/plan several experiments to confirm key targets/changes involved in energy metabolism, reactive oxygen species, ER stress, cell survival, vesicular trafficking, and cytoskeletal dynamics using a battery of in‐vitro assays in cancer cell lines. Lignan ENL modulates cellular energy metabolism markers (Examples: Fatty acid synthase/FASN, Sterol regulatory element‐binding proteins/SREBPs, Insulin induced gene 1/INSIG1, Low density lipoprotein receptor/LDLR, PPARγ, Glucose transporter 1/GLUT1, and Pyruvate kinase muscle isozyme M2/PKM2), and ER stress markers (Examples: Activating transcription factor 4/ATF4, CCAAT‐enhancer‐binding protein homologous protein/CHOP, Growth arrest and DNA damage‐inducible protein 34/GADD34 and Glucose‐regulated protein 58/GRP58). ENL reduced mitochondrial redox function and caused mitochondrial toxicity in‐vitro . Various anticancer drugs in combination with ENL caused significant reduction in cell viability. These findings warrant further investigations to support FLNs' ability to enhance ER stress as the key mechanism involved in the disruption of cellular survival adaptations when combined with anticancer drugs. Lignans are safe and therefore are good candidates for adjuvant/combination therapy that could improve patient longevity and quality of life. Support or Funding Information Saskatchewan Health Research Foundation (Research Funding), and College of Pharmacy & Nutrition, College of Graduate & Post‐doctoral Studies, and Apotex Canada (Graduate Student Scholarships) This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".