Telomere Length on Chromosome 17q Shortens More than Global Telomere Length in the Development of Breast Cancer
Bibliographic record
Abstract
It is known that total telomere length is shorter in invasive breast cancer than in normal breast tissue but the status of individual telomere lengths has not been studied. Part of the difficulty is that usually telomere length in interphase cells is measured on all chromosomes together. In this study we compared normal breast epithelium, duct carcinoma in situ (DCIS), and invasive duct carcinoma (IDC) from 18 patients. Telomere length was specifically measured on chromosome 17q and was found to be shorter in DCIS and IDC than in normal breast epithelial cells, with more heterogeneity in telomere length in DCIS associated with IDC than in DCIS alone. More importantly, we found that the shortening of telomere on chromosome 17q is greater than the average shortening of all telomeres. This finding indicates that telomere shortening is not simply the result of the end replication problem; otherwise, all telomeres should be subjected to the same rate of telomere shortening. It seems there are mechanisms that preferentially erode some telomeres more than others or preferentially protect some chromosome ends. Our results suggest that the increased level of telomere shortening on 17q may be involved in chromosome instability and the progression of DCIS.
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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 | 0.001 |
| 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 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".