Prostate cancer liver metastases: Genomic profiling and clinical outcomes.
Bibliographic record
Abstract
189 Background: Patients (pts) with metastatic prostate cancer and liver metastases have poor prognosis, but clinicogenomic analyses are limited. We examined the clinical and genomic features of a cohort with prostate cancer liver metastases (PCLM). Methods: Pts were identified from a prospective population-based biobank in British Columbia, Canada. Eligible pts had PCLM identified on imaging prior to any line of treatment. We collated clinical outcomes with cell-free DNA (cfDNA) sequencing results including circulating tumor DNA fraction (ctDNA%) and genomic alterations. Results: 2048 metastatic prostate cancer pts were enrolled from October 2016 to July 2024, of whom 1258 had sufficient clinical annotation to evaluate PCLM status. Of these, 167 (13%) were diagnosed with PCLM: 36 (22%) with castration-sensitive prostate cancer (mCSPC), 48 (29%) prior to first-line castration-resistant prostate cancer treatment (1L mCRPC), 30 (18%) prior to 2L mCRPC, and 53 (32%) prior to ≥3L mCRPC. Median follow-up was 60.3 months. Median age at metastatic diagnosis was 68.7 (IQR 61.8-74.7) years, 93 (56%) had de novo metastatic disease, 20 (12%) had histologically proven small cell carcinoma, 27 (16%) had low PSA (<5ng/mL) at baseline, and 111 (66%) had ≥3 liver metastases. For mCSPC pts, 27 (75%) received treatment intensification beyond ADT alone, including 5 (14%) with platinum chemotherapy. Median overall survival (mOS) for mCSPC pts was 15.5 months (95% CI 11.7-28.1), and median time to castration resistance was 8.1 months (95% CI 5.7-10.7). For mCRPC pts, 94 (72%) had prior exposure to ARPI, 56 (43%) to taxane, and 8 (6%) to platinum. mOS for 1L mCRPC pts was 9.4 months (95% CI 6.7-12.6), for 2L mCRPC 4.9 months (95% CI 3.5-9.7) and for ≥3L mCRPC 5.6 months (95% CI 4.1-8.4). For 134 pts with cfDNA results the median ctDNA% was 24.7 (IQR 4.6-53.9). Alterations were found in TP53 (47%), PTEN (26%), RB1 (19%), with 82 pts (61%) having alterations in at least one tumor suppressor gene (TSG) and 34 (25%) in more than one TSG. 14 pts (10%) had a BRCA2 alteration. ctDNA% and detectable TSG alterations were associated with survival of pts with PCLM (Table). Of 17 long survivors (pts who lived >24 months from start of next line treatment), 12 had cfDNA results available, median ctDNA% was 13.6%, and only 1 had TSG loss detected ( PTEN ). Conclusions: Pts with PCLM exhibit poor clinical outcomes; both elevated ctDNA% and TSG loss correlate with reduced overall survival. mCSPCmOS (months)N = 24 pts with cfDNA 1L mCRPCmOS (months) N = 35 pts with cfDNA 2L mCRPCmOS (months)N = 25 pts with cfDNA TSG status No alteration detected 57 23.6 8 Alteration detected 11.7 6.8 4.3 Univariable HR (95% CI) 9.3 (2.0-42.7)p<0.01 5.6 (2.1-15.5)p<0.01 1.4 (0.6-3.2)p=0.4 ctDNA% ≤ median ctDNA% (24.7%) 57 18.1 9 > median ctDNA% (24.7%) 14.7 5.8 12 Univariable HR (95% CI) 2.4 (1.0-5.4)p<0.05 2.7 (1.5-5.0)p<0.01 1.1 (0.6-2.0)p=0.8
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".