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Re-VOLVE: Phase II clinical trial in women with ovarian cancer progressing post-PARP inhibitor with treatment adapted to real-time assessment of evolving genomic resistance.

2025· article· en· W4410813020 on OpenAlexafffund
Pamela Soberanis Pina, Amit M. Oza, Neesha C. Dhani, Lisa Wang, Robert C. Grant, Diane Provencher, Blaise Clarke, Sahaj Arora, Janelle Ramsahai, Judy Quintos, Prathuha Dhanabalan, Valerie Bowering, Bernard Lam, Madhuran Thiagarajah, Alexander Fortuna, Trevor J. Pugh, Stéphanie Lheureux

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsOntario Institute for Cancer ResearchUniversity of TorontoPrincess Margaret Cancer CentreCentre Hospitalier de l’Université de MontréalUniversity Health Network
FundersPrincess Margaret Cancer Foundation
KeywordsMedicinePARP inhibitorOvarian cancerOncologyInternal medicineClinical trialPoly ADP ribose polymeraseCancerCancer researchGynecologyGeneticsDNABiologyPolymerase

Abstract

fetched live from OpenAlex

5561 Background: As the use of PARPi increases in high-grade serous ovarian cancer (HGSOC) resistance mechanisms ultimately arise. Emerging therapeutic strategies to overcome PARPi resistance is a pressing concern. Re-VOLVE study is a phase II in HGSOC women post-PARPi with treatment adapted to real-time assessment of evolving genomic resistance to guide treatment decision (NCT05065021). Methods: It enrolled patients (pts) with HGSOC progressing post-PARPi to receive induction phase (IP) 2-3 cycles of niraparib 200-300mg/bevacizumab 7.5mg/kg followed by personalized phase based on initial RECIST response and real-time assessment of evolving genomic resistance from baseline biopsy (whole genome RNA sequencing/WGTS) and ctDNA (12 gene panel). If progression/stable disease after IP pts were assigned to cohort A (niraparib/bevacizumab/dostarlimab 500mg) if no resistance mechanisms and to B (weekly paclitaxel 80mg/m2/bevacizumab/dostarlimab) if any present and to cohort C (continue niraparib/bevacizumab) if partial response after IP. Primary endpoint was to assess response rate of combination therapies. Results: 50 pts were screened; 7 were screen fail and 43 were enrolled. Of the 43, 3 pts were taken off due to progression during IP, 1 withdrew from study, 3 are on IP and 36 continued to personalized phase. Of these 36, 78% were white, 20% Asian, 2% others; 69% BRCA wild-type (25/36); 61% platinum-resistant (PR;22/36) and 39% platinum-sensitive (PS;14/36). Median age 62.5 years (33-87). Pts had median 2 prior therapy lines (1-5); 22% (8/36) prior bevacizumab. Median days from collection to ctDNA results were 59 days and to WGTS 54 days. Twenty-seven pts (75%) had biopsy and ctDNA to guide therapy. 36 pts were assigned to personalized phase: 78% cohort A, 14% to B (4 CCNE1 amplification and 1 CHEK2 mutation) and 8% to C (3 with response during IP). Of the 31/36 pts assessed for response during personalized phase (others too early) 10 achieved partial response (32.2%; 7 PR, 3 PS). Nineteen pts (61.3%; 11 PR, 8 PS) had stable disease. By cohort, 3 pts had partial response (12.5%; 3/24) cohort A, 4 partial response cohort B (100%; 4/4 all with resistance mechanisms) and 3 partial response (100%; 3/3) cohort C. Median PFS in the personalized phase was 7.8 months (m) for those in cohort A, 6.2m for B and 13.1m for C. Median PFS for PR pts was 6.9m (4.4-13.1) and for PS pts not reached. Grade (G) 3 AE related to therapy per cohort: A) 4 pts with anemia, 2 neutropenia, 1 thrombocytopenia, 1 nausea; B) 2 pts neutropenia; C) no G3. No G4 AE. No G3-G4 immune related AE. Conclusions: These findings highlight the potential clinical activity of a chemo-free approach and confirmed the feasibility of guiding personalized therapy in real-time in recurrent OC pts post-PARPi. This strategy was safe and provided clinical benefit to some pts. Further translational analysis is ongoing. Clinical trial information: NCT05065021 .

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.104
GPT teacher head0.527
Teacher spread0.422 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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