Tumor-induced inflammation in mammary adipose tissue stimulates a vicious cycle of autotaxin expression and breast cancer progression
Bibliographic record
Abstract
Compared to normal tissues, many cancer cells overexpress autotaxin (ATX). This secreted enzyme produces extracellular lysophosphatidate, which signals through 6 GPCRs to drive cancer progression. Our previous work showed that ATX inhibition decreases 4T1 breast tumor growth in BALB/c mice by 60% for about 11 d. However, 4T1 cells do not produce significant ATX. Instead, the ATX is produced by adjacent mammary adipose tissue. We investigated the molecular basis of this interaction in human and mouse breast tumors. Inflammatory mediators secreted by breast cancer cells increased ATX production in adipose tissue. The increased lysophosphatidate signaling further increased inflammatory mediator production in adipose tissue and tumors. Blocking ATX activity in mice bearing 4T1 tumors with 10 mg/kg/d ONO-8430506 (a competitive ATX inhibitor, IC90 = 100 nM; Ono Pharma Co., Ltd., Osaka, Japan) broke this vicious inflammatory cycle by decreasing 20 inflammatory mediators by 1.5-8-fold in cancer-inflamed adipose tissue. There was no significant decrease in inflammatory mediator levels in fat pads that did not bear tumors. ONO-8430506 also decreased plasma TNF-α and G-CSF cytokine levels by >70% and leukocyte infiltration in breast tumors and adjacent adipose tissue by >50%. Hence, blocking tumor-driven inflammation by ATX inhibition is effective in decreasing tumor growth in breast cancers where the cancer cells express negligible ATX.—Benesch, M. G. K., Tang, X., Dewald, J., Dong, W.-F., Mackey, J. R., Hemmings, D. G., McMullen, T. P. W., Brindley, D. N. Tumor-induced inflammation in mammary adipose tissue stimulates a vicious cycle of autotaxin expression and breast cancer progression. FASEB J. 29, 3990-4000 (2015). www.fasebj.org
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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".