ArticleNature genetics2026
Tumor DNA methylation subtypes predict immunotherapy outcomes in pleural mesothelioma patients in the NIBIT-EPI-MESO study.
Article in Nature genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Damage-Associated Molecular Patterns in Mesothelioma: Drivers of Inflammation and Therapeutic Targets.International journal of molecular sciences · 2026Review
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Authors and funding
31 authors.
Funding
Abstract
Pleural mesothelioma (PM) has a poor prognosis and standard therapy with immune checkpoint inhibitors (ICIs) CTLA-4 and PD-1 is still clinically unsatisfying. No predictive biomarkers of ICI efficacy in PM are available yet. In the retrospective multicenter NIBIT-EPI-MESO study, multi-omics analysis of pre-ICI therapy tumor lesions from 91 patients with PM treated in earlier clinical trials or in daily practice identified four PM subsets with progressively increasing global DNA methylation profiles-demethylated, LOW, intermediate and CpG island methylator phenotype (CIMP). These methylation subsets predicted response and survival to ICI therapy. The LOW subset was enriched in responder patients, who had the longest median overall survival and the highest 3-year overall survival rate, and showed a T cell- and B cell-rich immune microenvironment. Conversely, the CIMP subtype was enriched in nonresponder patients with the shortest median overall survival and overall survival, along with a depleted immune microenvironment. A methylation-based probabilistic decision-making classification tool to predict the outcome of ICI treatment in patients with PM was developed.
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Registered trials
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