Somatic Mosaicism and Cancer: A Micro-Genetic Examination into the Role of the Androgen Receptor Gene in Prostate Cancer
Bibliographic record
Abstract
Recent evidence has shown that the androgen receptor (AR) plays a major role in all prostate cancer stages, including both androgen-dependent and -independent tumors. A large number of studies have examined the possible effects of a functional polymorphism in the AR gene, a variable-length CAG repeat, on the development of prostate cancer, but the results to date have been inconclusive. We have considered the fact that the tissue heterogeneity present in almost all prostate cancer tumors has rarely been regarded as an indicator of AR genetic heterogeneity. To determine if genetic heterogeneity exists and is a significant event in prostate cancer development, we have examined prostate cancer tumors for somatic shortening of the AR gene CAG repeat. All 72 laser capture microdissected samples from archival prostate cancer tissues, as well as samples from freshly prepared prostate cancer tissues, showed some genetic heterogeneity (somatic mosaicism) for AR CAG repeat length. Cancerous tissues showed a much greater degree of genetic heterogeneity than adjacent benign tissues, as well as a very significant shortening of their CAG repeat lengths. However, CAG repeat length heterogeneity was not observed in normal prostate tissues. It is hypothesized that somatic mosaicism of the AR CAG repeat in prostate cancer tumors may be found to be an important genetic event in precancerous tissue, which may subsequently lead to the development of prostate 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) | 0.001 | 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".