Rucaparib: a novel PARP inhibitor for BRCA advanced ovarian cancer
Bibliographic record
Abstract
Ilaria Colombo, Stephanie Lheureux, Amit Manulal Oza Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada Abstract: Rucaparib is a potent small-molecule inhibitor of poly (ADP-ribose) polymerase (PARP) proteins (PARP-1, PARP-2 and PARP-3) that play an important role in repairing DNA damage and maintaining genomic stability. Tumors with mutations in BRCA1/2 or other homologous recombination deficiency (HRD) genes are particularly sensitive to PARP inhibitors because of “synthetic lethality”, whereby a therapeutic agent can take advantage of an intrinsic weakness in DNA repair. Rucaparib has been investigated in several preclinical and clinical studies showing promising activity in BRCA-mutant and BRCA–wild-type epithelial ovarian cancers (EOCs). Dose-escalation Phase I studies have established the recommended Phase II dose to be 600 mg twice a day for oral rucaparib. Phase II and III studies have defined its role as treatment for BRCA-mutant recurrent high-grade EOC and as maintenance treatment for platinum-sensitive relapsed EOC following response to platinum-based chemotherapy. Genomic loss of heterozygosity has also been investigated as a potential signature of HRD and as a potential predictive biomarker of response. Treatment-induced adverse events (AEs) have been observed in almost all patients treated with rucaparib, but mainly lower grade; with the most common being nausea, vomiting, asthenia/fatigue, anemia and transient transaminitis. The majority of AEs occurred early in treatment, were transient and have been easily managed with supportive treatment, dose interruption or discontinuation. This review will analyze the results of clinical trials investigating efficacy and safety of rucaparib in patients with ovarian cancer. Keywords: rucaparib, ovarian cancer, BRCA mutations, homologous recombination deficiency, maintenance treatment, PARP inhibitor
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".