MétaCan
Menu
Back to cohort
Record W4407162975 · doi:10.1056/nejmoa2405008

Efficacy of Zenocutuzumab in <i>NRG1</i> Fusion–Positive Cancer

2025· article· en· W4407162975 on OpenAlexaff
Alison M. Schram, Kōichi Goto, Dong-Wan Kim, Teresa Macarulla, Antoine Hollebecque, Eileen M. O’Reilly, Sai‐Hong Ignatius Ou, Jordi Rodón, Sun Young Rha, Kazumi Nishino, M. Duruisseaux, Joon Oh Park, Cindy Neuzillet, Stephen V. Liu, Benjamin A. Weinberg, James M. Cleary, Emiliano Calvo, Kumiko Umemoto, Misako Nagasaka, Christoph Springfeld, Tanios Bekaii‐Saab, Grainne M. O’Kane, Frans L. Opdam, Kim A. Reiss, Andrew K. Joe, Ernesto Wasserman, Viktoriya Stalbovskaya, Jim Ford, Shola Adeyemi, Lokesh Jain, Shekeab Jauhari, Alexander Drilon

Bibliographic record

VenueNew England Journal of Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer Institute
KeywordsMedicineCancerFusionOncologyInternal medicineMathematicsPhilosophy

Abstract

fetched live from OpenAlex

BackgroundNeuregulin 1 (NRG1) fusions are recurrent oncogenic drivers found in multiple solid tumors. NRG1 binds to human epidermal growth factor receptor 3 (HER3), leading to heterodimerization with HER2 and activation of downstream growth and proliferation pathways. The efficacy and safety of zenocutuzumab, a bispecific antibody against HER2 and HER3, in patients with NRG1 fusion–positive solid tumors are unclear. MethodsIn this registrational, phase 2 clinical study, we assigned patients with advanced NRG1 fusion–positive cancer involving any tumor type to receive zenocutuzumab at a dose of 750 mg intravenously every 2 weeks. The primary end point was overall response (complete or partial response) according to investigator assessment. Secondary end points included duration of response, progression-free survival, and safety. ResultsA total of 204 patients with 12 tumor types were enrolled and treated. Among 158 patients who had measurable disease and were enrolled at least 24 weeks before the data-cutoff date, a response occurred in 30% (95% confidence interval [CI], 23 to 37). The median duration of response was 11.1 months (95% CI, 7.4 to 12.9); 19% of responses were ongoing at the data-cutoff date. Responses were observed in multiple tumor types — including in 27 of 93 patients (29%; 95% CI, 20 to 39) with non–small-cell lung cancer (NSCLC) and 15 of 36 patients (42%; 95% CI, 25 to 59) with pancreatic cancer — and across multiple NRG1 fusion partners. The median progression-free survival was 6.8 months (95% CI, 5.5 to 9.1). Adverse events were primarily grade 1 or 2. The most common adverse events that were considered by the investigator to be related to zenocutuzumab were diarrhea (in 18% of the patients), fatigue (in 12%), and nausea (in 11%). Infusion-related reactions (composite term) were observed in 14% of the patients. One patient discontinued zenocutuzumab owing to a treatment-related adverse event. ConclusionsZenocutuzumab showed efficacy in patients with advanced NRG1 fusion–positive cancer, notably NSCLC and pancreatic cancer, with mainly low-grade adverse events. (Funded by Merus; eNRGy ClinicalTrials.gov number, NCT02912949.)

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.389
Teacher spread0.363 · 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 designRandomized 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

Citations104
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNew England Journal of MedicineSame topicHER2/EGFR in Cancer ResearchFrench-language works237,207