Co‐assessment of cytoplasmic and nuclear androgen receptor location in prostate specimens: potential implications for prostate cancer development and prognosis
Bibliographic record
Abstract
OBJECTIVE: To address, by co-assessing cytoplasmic and nuclear androgen receptor (AR) expression in prostate tissues, the contribution of the AR throughout the stages of prostate cancer (PC) and its value as a marker for predicting biochemical recurrence (BCR) after radical prostatectomy (RP). PATIENTS AND METHODS: Archival prostate specimens from patients who were cancer-free (43), with hormone-sensitive prostate cancer (HSPC, 62), and with androgen-independent prostate cancer (AIPC, 30) were used to construct tissue microarrays (total 135). Prostatic intraepithelial neoplasia (PIN) and non-neoplastic tissues (NA) found adjacent to HSPC were also included. Nuclear and cytoplasmic AR expression was scored by two observers using a composite scale, after immunohistochemical detection of the AR. The nuclear/cytoplasmic AR expression ratio was also calculated. Univariate Kaplan-Meier plots, and multivariate Cox and survival-tree analyses, were then used to assess the ability of the AR to predict BCR in the patients with HSPC. RESULTS: There was markedly greater nuclear AR staining intensity in NA than in normal prostate tissues from cancer-free patients. Cytoplasmic AR expression was highest in AIPC and markedly more than in HSPC. The nuclear/cytoplasmic AR expression ratio was highest in NA and PIN. In univariate analyses, a low nuclear AR, low cytoplasmic AR, and a high nuclear/cytoplasmic AR expression ratio were associated with BCR. Although cytoplasmic AR was an independent predictor of BCR in a Cox multivariate model (hazard ratio 2.736, 95% confidence interval 1.228-6.091, P = 0.014), survival-tree analyses suggested a complex relationship between AR expression and clinicopathological features. CONCLUSION: We propose that increased nuclear AR expression might be a precursor to PC and that cytoplasmic AR could contribute to the AIPC phenotype. The predictive ability of the AR might be closely linked to clinicopathological features.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".