Lysophosphatidate signaling stabilizes Nrf2 and increases the expression of genes involved in drug resistance and oxidative stress responses: implications for cancer treatment
Bibliographic record
Abstract
The present work elucidates novel mechanisms for lysophosphatidate (LPA)‐induced chemoresistance using human breast, lung, liver, and thyroid cancer cells. LPA (0.5–10 μM) increased Nrf2 transcription factor stability and nuclear localization by ≤5‐fold. This involved lysophosphatidate type 1 (LPA 1 ) receptors as identified with 1 μM wls‐31 (LPA 1/2 receptor agonist) and blocking this effect with 20 μM Ki16425 (LPA 1‐3 antagonist, K i = 0.34 μM). Knockdown of LPA 1 by 50% to 60% with siRNA decreased Nrf2 stability and expressing LPA 1 , but not LPA 2/3 , in human HepG2 cells increased Nrf2 stabilization. LPA‐induced Nrf2 expression increased transcription of multidrug‐resistant transporters and antioxidant genes by 2‐ to 4‐fold through the antioxidant response element. This protected cells from doxorubicin‐induced death. This pathway was verified in vivo by orthotopic injection of 20,000 mouse 4T1 breast cancer cells into syngeneic mice. Blocking LPA production with 10 mg/kg per d ONO‐8430506 (competitive autotaxin inhibitor, IC 90 = 100 nM) decreased expression of Nrf2, multidrug‐resistant transporters, and antioxidant genes in breast tumors by ≥90%. Combining 4 mg/kg doxorubicin every third day with ONO‐8430506 synergistically decreased tumor growth and metastasis to lungs and liver by >70%, whereas doxorubicin alone had no significant effect. This study provides the first evidence that LPA increases antioxidant gene and multidrug‐resistant transporter expression. Blocking this aspect of LPA signaling provides a novel strategy for improving chemotherapy.—Venkatraman, G., Benesch, M. G. K., Tang, X., Dewald, J., McMullen, T. P. W., Brindley, D. N., Lysophosphatidate signaling stabilizes Nrf2 and increases the expression of genes involved in drug resistance and oxidative stress responses: implications for cancer treatment. FASEB J. 29, 772–785 (2015). www.fasebj.org
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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".