MétaCan
Menu
← Back to cohort
Record W4416141026 · doi:10.1093/neuonc/noaf201.0119

BIOM-31. PLASMA CELL-FREE DNA METHYLOME PREDICTS RESPONSE TO COMBINED PARP AND IMMUNE CHECKPOINT INHIBITION IN IDH-MUTANT GLIOMA

2025· article· en· W4416141026 on OpenAlexaff
Yosef Ellenbogen, Kevin Wang, Vikas Patil, Alexander Landry, Jeff Liu, Justin Z. Wang, Leeor S. Yefet, Mathew Voisin, Jeffrey Zuccato, Andrew Ajisebutu, Phooja Persaud, Olivia Singh, Chloe Gui, Warren Mason, Farshad Nassiri, Eric X. Chen, Gelareh Zadeh

Bibliographic record

VenueNeuro-Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsToronto Public Health
Fundersnot available
KeywordsOlaparibImmune checkpointDNA methylationPARP inhibitorDurvalumabGliomaImmune systemBiomarkerEpigenetics

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION Recurrent IDH-mutant gliomas pose a significant therapeutic challenge, with limited treatment options following progression after standard therapy. Combining PARP inhibitors with immune checkpoint blockade has been proposed as a synergistic strategy in IDH-mutant high-grade gliomas, leveraging vulnerabilities in homologous recombination repair and increased PD-L1 expression following PARP inhibition. OBJECTIVE This phase II trial (NCT03991832) evaluated the combination of the PARP inhibitor olaparib and the PD-L1 inhibitor durvalumab in patients with recurrent IDH-mutant glioma. We also investigated the potential of the plasma tumor methylome as a non-invasive biomarker of treatment response. METHODS Twenty-nine patients (median age 40.5 years; 41% female) were enrolled between January 2020 and February 2023. All patients received olaparib (300 mg twice daily) and durvalumab (1,500 mg IV every four weeks) until radiographic or clinical progression. Plasma samples were collected at baseline and monthly, and cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) was performed. RESULTS The objective response rate was 10%, and median overall survival was 9.3 months. Longitudinal cfMeDIP-seq profiling enabled development of a circulating methylome classifier that accurately distinguished responders from non-responders. Integration with matched tumor transcriptomic and methylation data revealed enrichment of immune and DNA repair pathways in responders. Whole-exome sequencing identified no consistent mutational correlates. Spatial transcriptomic analysis demonstrated a more interactive, immune-rich tumor microenvironment and reduced malignant cell state diversity in responders. CONCLUSION This study supports the safety of combined PARP and PD-L1 blockade in recurrent IDH-mutant glioma and highlights the plasma methylome as a promising non-invasive biomarker of therapeutic response.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.307
Teacher spread0.290 · 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 designObservational
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 routes1
Has abstractyes

Explore more

Same venueNeuro-Oncology→Same topicPARP inhibition in cancer therapy→French-language works237,207→