Ionizing Radiation Enhances Breast Tumor Cell Migration In Vitro
Bibliographic record
Abstract
In preclinical studies, several tumor cell lines have demonstrated an epithelial-to-mesenchymal (EMT)-dependent enhancement in migration when exposed to ionizing radiation at doses of 10 Gy or higher. The goal of this study was to determine whether a lower dose (2.3 Gy) of radiation enhances breast tumor cell migration, and to elucidate the potential contribution of EMT and pro-migratory secreted factors in radiation-induced tumor cell migration. Three human breast cancer cell lines were irradiated and imaged in real-time over 72 h to quantify changes in single cell migration, chemotactic migration and invasion. EMT markers were assessed and conditioned media from irradiated cells was used to determine whether cellular migration was influenced by secreted factors. We observed that a 2.3 Gy dose of radiation did not induce EMT in epithelial-like MCF-7 cells and did not increase the ability of MCF-7 cells or highly motile MDA-MB-231 LM2-4 cells to migrate. In addition, a 2.3 Gy dose significantly increased MDA-MB-231 migration, as detected by single cell tracking and transwell migration assays, but did not increase invasion of MDA-MB-231 cells through reconstituted basement membrane. Cells from all three cell lines migrated further from their point of origin after irradiation, suggesting the cells may be responding to soluble factors produced by other irradiated cells. Consistently, conditioned media derived from 2.3 Gy irradiated MDA-MB-231 cells contained increased levels of several pro-migratory chemokines, and conditioned media from irradiated cells enhanced the migration of nonirradiated MDA-MB-231 cells. These findings indicate that 2.3 Gy dose of radiation is sufficient to increase migration of MDA-MB-231 cells and to alter the single cell migration behavior of three human breast cancer cell lines. Our data suggest the involvement of soluble factors released by 2.3 Gy irradiated cells, and support further in vitro and in vivo studies to identify potential therapeutic targets to prevent tumor cell migration after irradiation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".