Considerations on the identification and management of metastatic prostate cancer patients with DNA repair gene alterations in the Canadian context
Bibliographic record
Abstract
Olaparib is the first Health Canada-approved agent in metastatic prostate cancer to use a companion diagnostic to identify alterations in BRCA1, BRCA2, or ATM. As olaparib is introduced, clinicians must learn to access and interpret germline and somatic next-generation sequencing (NGS) results, and how to manage affected patients who appear to have distinct clinical features. The traditional model of referring patients to a hereditary cancer clinic (HCC) for germline testing is likely impractical in this disease, as the metastatic prostate cancer patient population would be overwhelming. Alternate approaches to this are clinician-ordered genetic testing (so-called “mainstreaming”), out-of-pocket payment for third-party private company genetic testing, or germline testing done in conjunction with somatic testing, particularly cell free circulating tumor DNA (ctDNA). Germline testing alone is not sufficient for identifying Olaparib-eligible patients, as less than half of BRCA1, BRCA2, or ATM alterations are germline in origin, but it is critically important to identify family members who are carriers so that risk-reduction measures can be undertaken. Somatic testing is not widely available in Canada, but some patients can access it through research protocols or by paying out-of-pocket. Somatic testing can be performed on archival or fresh solid tissue biopsy samples, or through whole blood samples to access plasma-derived circulating tumor DNA (ctDNA). Both testing approaches have relative advantages and disadvantages, but neither may be informative in all patients and, therefore, ideal somatic NGS pathways should provide options for both tissue and ctDNA testing. We advocate that clinicians begin discussions with their provincial lab formularies, HCC, and molecular pathology labs to highlight the importance of germline and somatic testing in this population and identify pathways for patient access. While olaparib has approval for use in BRCA1, BRCA2, and ATM-altered mCRPC, emerging evidence suggests that PARP inhibitors have variable activity in these three genes, with BRCA2 alterations appearing to be the most responsive. Retrospective and prospective series have reported varying outcomes to standard of care therapies, such as ARATs and taxane-based chemotherapy, in metastatic castration-resistant prostate cancer (mCRPC) patients with DNA damage repair (DDR) gene alterations, such as BRCA2. In the absence of high-level evidence showing a lack of benefit, we believe this patient population should still be considered for these treatments. In addition, platinum-based chemotherapy appears to have activity in DDR gene-altered mCRPC and should be considered another option when access to olaparib is not possible. At present, there is no evidence to support an optimal treatment sequence in this patient population, therefore, physician and patient preferences will need to be taken into consideration when selecting therapies. As olaparib and other PARP inhibitors are tested in different disease states and in combination with other therapies, we will likely see a more refined approach to use of these agents and management of this new biomarker-defined patient population.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".