Evaluating the role of liquid biopsy to detect pathogenic DNA Damage Repair (DDR) gene alterations in metastatic prostate cancer
Bibliographic record
Abstract
Abstract Background Metastatic prostate cancers frequently harbor pathogenic aberrations in DNA damage repair (DDR) genes, that confer sensitivity to PARP inhibitors (PARPi). Therefore, accurate identification of all eligible patients is needed. The development of circulating tumor DNA (ctDNA) testing alternative is promising as genomic testing of archived tissue leads to up to 30-40% failure rate in prostate cancer. Methods This was a bi-institutional retrospective cohort study of patients with metastatic prostate cancer 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 a chart review. Chi-square, Fisher’s exact test, and Mann-Whitney tests were used to assess differences between groups. Results We identified 484 metastatic prostate cancer patients. Somatic and germline testing for DDR was performed in 55.4% (n=268) and 20% (n=97) patients, respectively. Somatic testing was performed on tissue (n=192, 71.6%) or ctDNA from liquid biopsies (n=18, 6.7%) or both (n=58, 21.7%). Pathogenic somatic DDR alterations were detected in 48 patients (17.9%). BRCA2 was the most frequent (n=17) followed by ATM (n=11), then CHEK2 (n=5). Amongst patients with germline testing 13/97 (13.4%) had pathogenic alterations predicting to lead to deficient DDR, mostly BRCA2 (n=9) and 3 had detectable BRCA2 in tissue. Dual testing modality (tissue+ctDNA) significantly enhanced the detection rate of DDR alterations 19/58 (32.7%) vs 29/210 (13.8%) for single testing modality (tissue or ctDNA) P=0.008. The rate of inconclusive results was significantly lower in dual testing modality 0/58 (0%) vs 25/210 in single testing modality (11.9%), P=0.003. Amongst the 14 patients who had discordant results between liquid and tissue tests, DDR abnormalities were more frequently identified in ctDNA (n=11) vs. tissue (n=3). Patients who had DDR deficiency detected only in ctDNA, had older tissue samples (median 5.6 years) compared to those who had deficient DDR detected only in tissue (median 0.2 years; P=0.14). Conclusion These data highlight a potential role in implementing liquid biopsy - especially in patients who only have older archival tissue available or failed tissue testing - to improve the detection rate of deficient DDR. Our ongoing prospective study will further validate whether the addition of liquid biopsy can identify more patients who are eligible to receive precision therapies.by increasing the rate of detection of DDR deficiency compared to routine tissue testing alone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.000 | 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".