Role of Interleukin-1β in Radiation-Enhancement of MDA-MB-231 Breast Cancer Cell Invasion
Bibliographic record
Abstract
The ability of radiation to increase the invasiveness of cancer cells is associated with the inflammatory response, which is induced in almost all irradiated patients. For breast cancer patients, elevated plasma levels of the inflammatory cytokine interleukin-1β (IL1β) persisted for a few weeks after completion of radiotherapy. The aim of this study was to determine whether IL1β is involved in the enhancement of breast cancer cell invasion induced by radiation. The role of IL1β was assessed with invasion chambers where irradiated fibroblasts were used as chemoattractant for the MDA-MB-231 breast cancer cells plated in the upper compartment. The ability of IL1β to stimulate the expression of cyclooxygenase-2 (COX-2) and biosynthesis of the prostaglandin E2 (PGE2) in MDA-MB-231 cells were also determined. Our results show that radiation-enhancement of MDA-MB-231 cell invasion was prevented with an anti-IL1β antibody. The production of IL1β was increased in irradiated fibroblasts, while the invasiveness of the MDA-MB-231 cells not exposed to irradiated fibroblasts was favored by adding this cytokine. Furthermore, addition of the COX-2 inhibitor NS-398 prevented the stimulation of cancer cell invasion induced either by irradiated fibroblasts or IL1β. We propose that the effect of IL1β on the invasiveness of the MDA-MB-231 cells involves elevation of matrix metalloproteinase-9 (MMP-9) production, induction of COX-2 expression and PGE2 biosynthesis. In conclusion, this study supports the involvement of IL1β in the radiation-enhancement of breast cancer cell invasion.
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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) | 0.001 | 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".