Role of liquid biopsy in the detection of homologous recombination repair gene mutations (HRRm) in metastatic prostate cancer (mPC).
Bibliographic record
Abstract
51 Background: The treatment landscape of mPC is rapidly evolving to include more precision therapies for patients with actionable genomic alterations. Specifically, deleterious aberrations in HRR genes (HRRm) confer sensitivity to PARP inhibitors (PARPi) which have demonstrated survival benefit in this context. Therefore, accurate identification of potentially actionable HRRm is indicated. Somatic testing for HRRm in archival tissue is inadequate due to poor DNA quality or lack of tissue availability in 30-40% of cases. We evaluated whether circulating tumor DNA (ctDNA) testing using liquid biopsies is associated with an increased rate of HRRm detection. Methods: This was a multi-institutional retrospective cohort study of mPC patients (pts) treated at the Jewish General Hospital or the McGill University Health Center, Montreal Canada, between 2021-23. Molecular data and treatment information was abstracted from chart review. Fisher’s exact test and Wilcoxon test were used to assess differences between groups. Results: We identified 282 mPC pts, mostly castration resistant (n=181, 64.2%). Median age was 67 years (43-92). Somatic and germline testing for HRRm was performed in 78.3% (n=224) and 23.4% (n=66) pts, respectively. Somatic testing was performed on tissue (n=164, 73.2%) or ctDNA from liquid biopsies (n=17, 7.5%) or both (n=43, 19.3%). Pathogenic somatic HRRm were detected in 37 pts (13.2%): BRCA2 (n=13), ATM (n=8), CHEK2 (n=4), PALB2 (n=4), CDK12 (n=4) and BRCA1 (n=2). Amongst pts with germline testing 10/66 (15.1%) had pathogenic HRRm, mostly BRCA2 (n=9) and 4/10 had detectable HRRm in tissue. The somatic HRRm detection rate was 14.6% (24/164) on tissue and 11.7% (2/17) in ctDNA, respectively. Pts who had both tissue and liquid biopsy experienced a higher detection rate (25.5%, 11/43) vs. either modality alone (P=0.064). Inconclusive results were less frequent in pts who had both liquid and tissue testing vs. tissue alone (2.3% vs 7.3%). Amongst the 10 pts who had discordant results between liquid and tissue tests, HRRm were more frequently identified in ctDNA (n=7) vs. tissue (n=3). Pts who had HRRm detected only in ctDNA, had significantly older tissue samples (median 5.1 years) compared to those who had HRRm detected only in tissue (median 0.2 years, P=0.0156). Conclusions: Our data highlight a potential role of implementing liquid biopsy to improve the detection rate of HRRm. We are currently conducting a multi-center prospective study to determine if liquid biopsy increases the rate of detection of HRRm compared to routine tissue testing, and therefore allows to identify more patients who are eligible to receive precision therapies.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".