Expression of Receptors for Luteinizing Hormone-Releasing Hormone (LH-RH) in Prostate Cancers following Therapy with LH-RH Agonists
Bibliographic record
Abstract
PURPOSE: In addition to their expression on pituitary cells, receptors for luteinizing hormone-releasing hormone (LH-RH) are found on most prostate cancer cells. These tumoral LH-RH receptors mediate the direct cytotoxic effects of LH-RH analogs and are potential therapeutic targets. Although pituitary LH-RH receptors are downregulated following prolonged exposure to LH-RH agonists, there is no evidence that tumoral receptors behave in a similar manner. To better characterize expression of tumoral LH-RH receptors, specimens of prostate cancer from various cohorts of patients were analyzed. EXPERIMENTAL DESIGN: Surgical specimens were obtained from untreated patients with prostate cancer and from patients with metastatic castration-resistant prostate cancer previously treated with bilateral orchiectomy. To address the possibility of receptor downregulation, two additional cohorts of patients who had been previously treated with LH-RH agonists were included. One group received neoadjuvant therapy prior to prostatectomy, and the other group was treated for metastatic disease with LH-RH agonists and, at progression, required palliative resection of the prostate. Lymph node metastases from previously untreated patients were subjected to similar analysis. RESULTS: Expression of LH-RH receptors was found in most specimens. The relative expression of LH-RH receptor mRNA in untreated patients was greater in patients whose tumor had received a Gleason score <8. CONCLUSIONS: LH-RH receptor expression persisted despite prolonged exposure to LH-RH agonists. These findings support the concept of targeting cytotoxic LH-RH analogs to prostatic LH-RH receptors, using these receptors to gain entry into cancer cells to deliver a hybridized cytotoxic moiety for the treatment 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 | 0.000 | 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".