3D Telomere Structure Analysis to Detect Genomic Instability and Cytogenetic Evolution in Myelodysplastic Syndromes
Bibliographic record
Abstract
The disease course of myelodysplastic syndromes (MDS) features chromosome instability and clonal evolution, leading to the sequential acquisition of novel cytogenetic aberrations and the accumulation of these abnormalities in the bone marrow. Although clonal cytogenetic abnormalities can be detected by conventional cytogenetics in 50% of patients with MDS, such distinguishing patterns are lacking in the other 50%. Despite the increase in the prognostic value of some biomarkers, none of them is specific and able to discriminate between stable and unstable patients that subsequently progress to acute myeloid leukemia. This pilot study aimed to investigate the potential use of the 3D telomere profiling to detect genomic instability in MDS patients with or without clonal cytogenetic evolution. The comparison between different time points in patients with cytogenetic changes showed that in the CD34+ MDS cells, there was a significant decrease in the total number of telomeric signals, the average intensity of signals and the total intensity of telomeres. By contrast, the number of aggregates increased during cytogenetic evolution (p < 0.001). This pattern was observed only for MDS patients with cytogenetic evolution but was absent in patients without cytogenetic changes. In conclusion, we demonstrated that the 3D nuclear telomere organization was significantly altered during the MDS disease course, and may have contributed to cytogenetic clonal evolution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".