Radium-223–Induced Bystander Effects Cause DNA Damage and Apoptosis in Disseminated Tumor Cells in Bone Marrow
Bibliographic record
Abstract
Abstract Radiation-induced bystander effects have been implicated in contributing to the growth delay of disseminated tumor cells (DTC) caused by 223RaCl2, an alpha particle–emitting radiopharmaceutical. To understand how 223RaCl2 affects the growth, we have quantified biological changes caused by direct effects of radiation and bystander effects caused by the emitted radiations on DTC and osteocytes. Characterizing these effects contribute to understanding the efficacy of alpha particle–emitting radiopharmaceuticals and guide expansion of their use clinically. MDA-MB-231 or MCF-7 human breast cancer cells were inoculated intratibially into nude mice that were previously injected intravenously with 50 or 600 kBq/kg 223RaCl2. At 1-day and 3-days postinoculation, tibiae were harvested and examined for DNA damage (γ-H2AX foci) and apoptosis in osteocytes and cancer cells located within and beyond the range (70 μm) of alpha particles emitted from the bone surface. Irradiated and bystander MDA-MB-231 and MCF-7 cells harbored DNA damage. Bystander MDA-MB-231 cells expressed DNA damage at both treatment levels while bystander MCF-7 cells required the higher administered activity. Osteocytes also had DNA damage regardless of inoculated cancer cell line. The extent of DNA damage was quantified by increases in low (1–2 foci), medium (3–5 foci), and high (5+ foci) damage. MDA-MB-231 but not MCF-7 bystander cells showed increases in apoptosis in 223RaCl2-treated animals, as did irradiated osteocytes. In summary, radiation-induced bystander effects contribute to DTC cytotoxicity caused by 223RaCl2. Implications: This observation supports clinical investigation of the efficacy of 223RaCl2 to prevent breast cancer DTC from progressing to oligometastases.
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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 | 0.001 |
| 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".