Clinical significance of steroid and xenobiotic receptor and its targeted gene CYP3A4 in human prostate cancer
Bibliographic record
Abstract
The steroid and xenobiotic receptor (SXR) regulates cytochrome P450 (CYP) enzymes, which are key inactivators of testosterone in the liver and prostate. In the present study, we investigated SXR expression in human prostate tissues. We determined SXR immunoreactivity using an anti-SXR antibody in benign (n = 78) and cancerous (n = 106) tissues obtained by radical prostatectomy. Stained slides were evaluated for the proportion and staining intensity of immunoreactive cells. Total immunoreactivity (IR) scores (range: 0-8) were calculated as the sum of the proportion and intensity scores. Associations between the clinicopathological features of the patients, SXR status, and CYP3A4 immunoreactivity were analyzed. Western blot analyses validated the specificity of the anti-SXR antibody in 293T cells transfected with pcDNA-FLAG-SXR. Positive (IR score: ≥ 2) nuclear SXR staining was observed in 91% (71/78) of benign foci and 47% (50/106) of cancerous lesions. Immunoreactivity scores were significantly lower in the cancerous lesions than in the benign foci (P < 0.0001). Clinicopathological analyses showed that cancer-specific survival in patients with high SXR IR scores (≥ 4) was significantly increased (P = 0.046). Combined data of present and previous studies showed that high IR scores for both the SXR and CYP3A4 correlated with significantly better cancer-specific survival rates in multivariate regression analyses (hazard ratio: 2.15, 95% confidence interval: 1.25-3.55, P = 0.007). We showed differential SXR expression in human prostate tissues. The high expression of the SXR and CYP3A4 is a strong prognostic indicator of favorable outcomes in prostate cancer, and could be a therapeutic target.
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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".