Reversine-Induced Telomere Architecture Remodeling in Chronic Myeloid Leukemia Cell Lines: Insights from TeloView® Analysis of 3D Nuclear Architecture
Bibliographic record
Abstract
Reversine is a small-molecule Aurora kinase inhibitor known for its pro-apoptotic effects and potential to remodel chromatin architecture. Although its impact on mitotic regulation is established, its effects on telomere dynamics and nuclear organization in chronic myeloid leukemia (CML) remain unclear. This study aimed to investigate the effects of reversine on telomere architecture, genomic instability, and apoptosis in CML cell lines (K-562 and MEG-01). Reversine was applied at increasing concentrations, and cytotoxicity was assessed using caspase-3/7 activation assays. Quantitative PCR was used to measure AURKA and AURKB mRNA expressions. Three-dimensional telomere architecture was analyzed with TeloView® v1.03 software after Q-FISH labeling to quantify telomere number, signal intensity, aggregation, nuclear volume, and a/c ratio. Reversine induced a dose- and time-dependent apoptotic response in both cell lines and significantly downregulated AURKA and AURKB expressions. Three-dimensional telomere analysis revealed a marked reduction in telomere number and aggregates, signal intensity, and nuclear volume. While reduced signal intensity may indicate telomere shortening, the concurrent decrease in aggregation and altered spatial parameters suggests telomeric reorganization rather than progressive instability. These features reflect structural nuclear remodeling and early apoptotic commitment. Differences between K-562 and MEG-01 responses underscore potential heterogeneity in telomere maintenance mechanisms. Reversine modulates genomic stability in CML cells through dual mechanisms involving Aurora kinase inhibition and telomere architecture remodeling. The integration of 3D telomere profiling highlights reversine’s potential as a therapeutic agent targeting nuclear disorganization and mitotic dysregulation in leukemia.
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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".