Distinct Oxidative Stress Adaptations Driven by the Overexpression of miR-526b, miR-655, and COX-2 in Breast Cancer
Bibliographic record
Abstract
Oxidative stress has a dual role in breast cancer, promoting growth at moderate levels while causing cell death at higher levels, such as during therapeutic interventions that increase reactive oxygen species production. Oncogenic microRNAs miR-526b and miR-655 promote aggressive cancer traits—such as proliferation, migration, invasion, hypoxia response, cancer stem cell properties, and metastasis—via COX-2/EP4/PI3K pathways. These miRNAs and oxidative stress appear to engage in a self-amplifying loop, where miRNA overexpression increases ROS levels, and moderate oxidative stress, in turn, enhances miRNA expression—although the mechanisms are not yet fully understood. This study investigates how overexpressing miR-526b, miR-655, and COX-2 influences breast cancer cell responses to oxidative stress induced by H2O2. We examined cell viability, DNA damage, and transcriptomic changes in MCF7, MCF7-miR526b, MCF7-miR655, and MCF7-COX2 cell lines. Overexpression of COX-2 provided the most significant protection against oxidative stress, decreasing apoptosis and promoting cell cycle progression. Cells with miR-526b and miR-655 exhibited distinct yet overlapping stress responses, including decreased expression of DNA damage markers and alterations in p53 signaling. RNA-sequencing and network analyses identified hub genes involved in redox balance, immune, and metabolic pathways, which may have clinical significance (OAS2, TNF, CACNA1C, CALML5). Overall, these findings suggest that miR-526b, miR-655, and COX-2 play novel roles in promoting resistance to oxidative stress through transcriptional reprogramming in breast cancer; the identified markers could serve as potential biomarkers or therapeutic targets.
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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".