Clinical and molecular features of low prostate-specific membrane antigen (PSMA) expression in patients (pts) with metastatic castration resistant prostate cancer (mCRPC).
Bibliographic record
Abstract
167 Background: Low PSMA uptake on positron-emission tomography is seen in up to 30% of mCRPC pts and represents a clinically distinct subgroup with adverse outcomes. We assessed transcriptional and clinical features associated with low PSMA ( FOLH1) gene expression in mCRPC. Methods: A retrospective analysis of mCRPC biopsy samples with RNA-seq data was undertaken. Normalized FOLH1 expression was compared across histologic subtypes and sites of disease. We assessed the association between FOLH1 expression, selected androgen receptor (AR) target genes, master regulators of neuroendocrine differentiation, and previously validated AR activity and treatment-associated small cell neuroendocrine carcinoma (t-SCNC) transcriptional signature scores using Pearson correlations. Associations between FOLH1 and both PSA50 response to subsequent AR-targeted therapy and overall survival (OS) were examined by logistic regression and Cox proportional hazard models, respectively. Results: Samples from 97 pts were identified, of which 18% harbored t-SCNC histology. 45% of pts had visceral metastases at the time of biopsy, and 41% received subsequent AR-targeted therapy. Median FOLH1 expression was lower in pts with visceral metastases vs no visceral metastases (14.7 vs 15.6, p = 0.02) but was not significantly different across t-SCNC vs adenocarcinoma biopsies (14.3 vs 15.4, p = 0.13). FOLH1 expression was positively correlated with AR transcriptional activity and AR target genes, and negatively correlated with master regulators of neuroendocrine differentiation and t-SCNC transcriptional signature scores (Table). Low FOLH1 expression did not predict PSA50 response to subsequent AR-targeted therapy (OR 0.97, p = 0.8), but was associated with shorter OS on univariate analysis (HR 1.09, 95% CI 1.02-1.16, p=0.01). A post-hoc analysis revealed a trend towards decreased median OS in pts with FOLH1 expression <12 (7.5 vs 17.1 months, log-rank p = 0.06). Conclusions: In this retrospective analysis of mCRPC pts, low FOLH1 expression was associated with transcriptional features of t-SCNC, decreased AR activity, and shorter OS. These findings are hypothesis-generating and prospective validation is needed.[Table: see text]
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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 | 0.000 | 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".