MicroRNA-138 Modulates DNA Damage Response by Repressing Histone H2AX Expression
Bibliographic record
Abstract
Precise regulation of DNA damage response is crucial for cellular survival after DNA damage, and its abrogation often results in genomic instability in cancer. Phosphorylated histone H2AX (γH2AX) forms nuclear foci at sites of DNA damage and facilitates DNA damage response and repair. MicroRNAs (miRNA) are short, nonprotein-encoding RNA molecules, which posttranscriptionally regulate gene expression by repressing translation of and/or degrading mRNA. How miRNAs modulate DNA damage response is largely unknown. In this study, we developed a cell-based screening assay using ionizing radiation (IR)-induced γH2AX foci formation in a human osteosarcoma cell line, U2OS, as the readout. By screening a library of human miRNA mimics, we identified several miRNAs that inhibited γH2AX foci formation. Among them, miR-138 directly targeted the histone H2AX 3'-untranslated region, reduced histone H2AX expression, and induced chromosomal instability after DNA damage. Overexpression of miR-138 inhibited homologous recombination and enhanced cellular sensitivity to multiple DNA-damaging agents (cisplatin, camptothecin, and IR). Reintroduction of histone H2AX in miR-138 overexpressing cells attenuated miR-138-mediated sensitization to cisplatin and camptothecin. Our study suggests that miR-138 is an important regulator of genomic stability and a potential therapeutic agent to improve the efficacy of radiotherapy and chemotherapy with DNA-damaging agents.
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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".