microRNAome changes in bystander three-dimensional human tissue models suggest priming of apoptotic pathways
Bibliographic record
Abstract
The radiation-induced bystander effect (RIBE) is a phenomenon whereby unexposed cells exhibit molecular symptoms of stress exposure when adjacent or nearby cells are traversed by ionizing radiation (IR). Recent data suggest that RIBE may be epigenetically mediated by microRNAs (miRNAs), which are small regulatory molecules that target messenger RNA transcripts for translational inhibition. Here, we analyzed microRNAome changes in bystander tissues after α-particle microbeam irradiation of three-dimensional artificial human tissues using miRNA microarrays. Our results indicate that IR leads to a deregulation of miRNA expression in bystander tissues. We report that major bystander end points, including apoptosis, cell cycle deregulation and DNA hypomethylation, may be mediated by altered expression of miRNAs. Specifically, c-MYC-mediated upregulation of the miR-17 family was associated with decreased levels of E2F1 and RB1, suggesting a switch to a proliferative state in bystander tissues, while priming these cells for impending death signals. Upregulation of the miR-29 family resulted in decreased levels of its targets DNMT3a and MCL1, consequently affecting DNA methylation and apoptosis. Altered expression of miR-16 led to changes in expression of BCL2, suggesting modulation of apoptosis. Thus, our data clearly show that miRNAs play a profound role in the manifestation of late RIBE end points. In summary, this study creates a roadmap for understanding the role of microRNAome in RIBE and for developing novel RIBE biomarkers.
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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".