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599 The MATRiX trial: a multicenter, randomized, phase II study of ATR inhibition (via tuvusertib) with or without avelumab in patients with advanced anti-PD-(L)1-refractory merkel cell carcinoma

2025· article· W4416088080 on OpenAlexaff
Rashmi Bhakuni, Evan Hall, George Ansstas, Shailender Bhatia, Andrew S. Brohl, Melissa Burgess, Sunandana Chandra, Maya Dimitrova, Ling Gao, Jeffrey J. Ishizuka, Gino K. In, Evan J. Lipson, Jose Lutzky, Rupali Nabar, Sam Saibil, Ann W. Silk, Daniel Wang, Alice Y. Zhou, Jina Yun, Isaac Brownell, Judy Murray, Yvonne M. Mowery, Ted Gooley, Steven D. Gore, Suzanne L. Topalian, Paul Nghiem

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2025
Typearticle
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Cancer InstituteEMD Serono
KeywordsAvelumabMerkel cell carcinomaMerkel cellPhase (matter)CarcinomaMatrix (chemical analysis)

Abstract

fetched live from OpenAlex

Background Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer driven by UV-induced mutations or the Merkel cell polyomavirus. It is aggressive, with a high Ki-67 proliferative index. Despite an ~55% response rate to PD-1 pathway inhibitors, most patients develop primary or acquired resistance. ATR (ataxia telangiectasia and Rad3-related) kinase, a critical cell cycle checkpoint regulator, ensures genome fidelity in cancer cells experiencing high replication stress. Recent preclinical 1 2 and clinical3–6 data suggest that ATR inhibition can enhance anti-tumor immunity and synergize with anti-PD-(L)1 therapy. Our preclinical findings suggest transcriptional induction of NF-κB-associated proinflammatory mechanisms with ATR inhibition. The potent, selective, oral ATR inhibitor tuvusertib has shown antitumor activity in phase I trials.6 We hypothesize that tuvusertib with anti-PD-(L)1 therapy, may induce tumor regression in advanced anti-PD-(L)1-refractory MCC.Methods The multicenter, randomized, phase II MATRiX trial tests the safety and efficacy of tuvusertib ± avelumab in patients with metastatic MCC refractory to PD-(L)1 blockade ( figure 1). Patients with progressive disease per Response Evaluation Criteria in Solid Tumors (RECIST v1.1) within 120 days of their last anti-PD-(L)1 therapy are eligible. Subjects in Arm 1 or 2 receive tuvusertib 180 mg QD on days 1-14 of each 21-day cycle (figure 2). Subjects in Arm 2 also receive avelumab 1600 mg IV on day 1 of each cycle. Imaging at week 9 and every 12 weeks thereafter is assessed per RECIST v1.1. The primary endpoint is progression-free survival (PFS). With a targeted enrollment of 50 patients, this trial has 83% power (one-sided level of 10%) to detect a hazard ratio of 2.0 for PFS using a stratified (primary vs. acquired resistance) log-rank test. Binary outcomes will be compared via a Mantel-Haenszel test. Tumor, blood, and stool specimens will be profiled for multi-omic signatures of immune-mediated therapeutic outcomes.Results Between June 2024 and June 2025, 24 subjects were enrolled across 15 centers. Arm 1 (tuvusertib monotherapy) enrolled 10 patients and was closed for lack of efficacy on 5/12/2025, as per the pre-defined statistical plan; 5 crossed over to Arm 2. All additional new patients will be enrolled on Arm 2, with a target of 25 subjects.Conclusions There is a need for additional therapeutic approaches for immunotherapy-refractory MCC, as demonstrated by robust enrollment on this trial. This orthogonal approach to solid tumor immunotherapy, relevant to more common immunogenic cancers, may guide future combination strategies to better harness anti-tumor immunity.Acknowledgements NCI Experimental Therapeutics Clinical Trials Network, protocol writing, and regulatory teams. Patients, families, and partnering teams for their commitment to advancing our understanding of this disease. EDDOP Leadership Award-P30 Administrative Supplement, the Mark Foundation for Cancer Research, the Kelsey Dickson Team Science Courage Research Team Award, and the MCC Patient Gift Fund. This study is financially supported by EMD Serono (CrossRef Funder ID: 10.13039/100004755), which provides avelumab and tuvusertib.Trial Registration NCT05947500References Vendetti FP, Karukonda P, Clump DA, et al. ATR kinase inhibitor AZD6738 potentiates CD8+ T cell-dependent antitumor activity following radiation. J Clin Invest. 2018;128(9):3926–3940.Hardaker EL, Sanseviero E, Karmokar A, et al. The ATR inhibitor ceralasertib potentiates cancer checkpoint immunotherapy by regulating the tumor microenvironment. Nat Commun. 2024;15(1):1700.Thomas A, Takahashi N, Rajapakse VN, et al. Therapeutic targeting of ATR yields durable regressions in small cell lung cancers with high replication stress. Cancer Cell. 2021;39(4):566-579.e7.Kim R, Kwon M, An M, et al. Phase II study of ceralasertib (AZD6738) in combination with durvalumab in patients with advanced/metastatic melanoma who have failed prior anti-PD-1 therapy. Ann Oncol. 2022;33(2):193–203.Besse B, Pons-Tostivint E, Park K, et al. Biomarker-directed targeted therapy plus durvalumab in advanced non-small-cell lung cancer: a phase 2 umbrella trial. Nat Med. 2024;30(3):716–729.Yap TA, Tolcher AW, Plummer R, et al. First-in-human study of the ataxia telangiectasia and Rad3-related (ATR) inhibitor tuvusertib (M1774) as monotherapy in patients with solid tumors. Clin Cancer Res. 2024;30(10):2057-2067.Ethics Approval The study is reviewed by NCI’s Central Institutional Review Board; approval number is 10592.Abstract 599 Figure 1An overview of the multicenter, NCI-sponsored Phase II study designed to test the efficacy of tuvusertib, with or without avelumab, to address anti-PD-(L)1 resistance in advanced, refractory MCC; NCT05947500Abstract 599 Figure 2Timeline of treatment regimen and biospecimen acquisition for patients randomized to arm 1 and 2

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.008
GPT teacher head0.256
Teacher spread0.247 · 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".

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Citations0
Published2025
Admission routes1
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