Inhibition of Autotaxin with GLPG1690 Increases the Efficacy of Radiotherapy and Chemotherapy in a Mouse Model of Breast Cancer
Bibliographic record
Abstract
Abstract Autotaxin catalyzes the formation of lysophosphatidic acid, which stimulates tumor growth and metastasis and decreases the effectiveness of cancer therapies. In breast cancer, autotaxin is secreted mainly by breast adipocytes, especially when stimulated by inflammatory cytokines produced by tumors. In this work, we studied the effects of an ATX inhibitor, GLPG1690, which is in phase III clinical trials for idiopathic pulmonary fibrosis, on responses to radiotherapy and chemotherapy in a syngeneic orthotopic mouse model of breast cancer. Tumors were treated with fractionated external beam irradiation, which was optimized to decrease tumor weight by approximately 80%. Mice were also dosed twice daily with GLPG1690 or vehicle beginning at 1 day before the radiation until 4 days after radiation was completed. GLPG1690 combined with irradiation did not decrease tumor growth further compared with radiation alone. However, GLPG1690 decreased the uptake of 3′-deoxy-3′-[18F]-fluorothymidine by tumors and the percentage of Ki67-positive cells. This was also associated with increased cleaved caspase-3 and decreased Bcl-2 levels in these tumors. GLPG1690 decreased irradiation-induced C-C motif chemokine ligand-11 in tumors and levels of IL9, IL12p40, macrophage colony-stimulating factor, and IFNγ in adipose tissue adjacent to the tumor. In other experiments, mice were treated with doxorubicin every 2 days after the tumors developed. GLPG1690 acted synergistically with doxorubicin to decrease tumor growth and the percentage of Ki67-positive cells. GLPG1690 also increased 4-hydroxynonenal-protein adducts in these tumors. These results indicate that inhibiting ATX provides a promising adjuvant to improve the outcomes of radiotherapy and chemotherapy for breast cancer.
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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".