Topographical analysis of telomere length and correlation with genomic instability in whole mount prostatectomies
Bibliographic record
Abstract
BACKGROUND: Many critical events in prostatic carcinogenesis appear to relate to the emergence of genomic instability. Characteristic genomic abnormalities such as 8p loss, 8q gain, trisomy 7, and PTEN microdeletions may provide selective advantages to increase neoplastic transformation. Evidence suggests that telomere dysfunction is a plausible mechanism for some of these abnormalities on the basis of the break-fusion-bridge cycle that can lead to manifestations of genomic instability. METHODS: In this study, we correlate telomere length measured by quantitative FISH in various prostatic histologies with markers of genomic instability and immunohistochemical measures of proliferation and oxidative stress. RESULTS: We find that telomere shortening is correlated with abnormalities on chromosome 8, but not with trisomy 7 or abnormalities of the PTEN locus. There are associations with C-MYC aberrations in stroma with greater proximity to cancer and a correlation between telomere length in a number of prostatic histologies and the adjacent stroma, suggesting the importance of microenvironmental effects on telomere maintenance in the prostate. This finding was also supported by the finding of the correlation between telomere attrition and the levels of oxidative stress as measured by malondialdehyde staining in HPIN lesions close to cancer. CONCLUSIONS: Telomere attrition in the prostate gland is associated with particular genomic aberrations that contribute to the genomic instability characteristic of prostatic carcinogenesis. Correlations between various histologies and adjacent stroma telomere length suggest it is also may reveal microenvironmental effects within the prostate gland. Oxidative stress may contribute to telomere attrition in HPIN close to cancer.
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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 | 0.001 | 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) | 0.002 | 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".