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.

Tumor DNA methylation subtypes predict immunotherapy outcomes in pleural mesothelioma patients in the NIBIT-EPI-MESO study / Calabrò, Luana; Caruso, Francesca P; Covre, Alessia; Noviello, Teresa M R; Lofiego, Maria F; Tufano, Rossella; Ferraro, Luigi; Grisolia, Piera; De Falco, Antonio; Lagano, Vincenzo; Sgambelluri, Francesco; Sabella, Giovanna; Rossi, Giulia; Gibilisco, Giulia; Marzani, Francesco; Bello, Emma; Simonetti, Elena; D'Alonzo, Vincenzo; Caraglia, Michele; Coral, Sandra; De Angelis, Antonina; Cerbone, Luigi; Delfanti, Sara; Giannarelli, Diana; Grosso, Federica; Di Giacomo, Anna Maria; Milione, Massimo; Mortarini, Roberta; Anichini, Andrea; Ceccarelli, Michele; Maio, Michele. - In: NATURE GENETICS. - ISSN 1546-1718. - 58:5(2026), pp. 1100-1111. [10.1038/s41588-026-02580-4]

Tumor DNA methylation subtypes predict immunotherapy outcomes in pleural mesothelioma patients in the NIBIT-EPI-MESO study

Caruso, Francesca P
Co-primo
;
Tufano, Rossella;Ferraro, Luigi;De Falco, Antonio;Ceccarelli, Michele
;
2026

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.
2026
Tumor DNA methylation subtypes predict immunotherapy outcomes in pleural mesothelioma patients in the NIBIT-EPI-MESO study / Calabrò, Luana; Caruso, Francesca P; Covre, Alessia; Noviello, Teresa M R; Lofiego, Maria F; Tufano, Rossella; Ferraro, Luigi; Grisolia, Piera; De Falco, Antonio; Lagano, Vincenzo; Sgambelluri, Francesco; Sabella, Giovanna; Rossi, Giulia; Gibilisco, Giulia; Marzani, Francesco; Bello, Emma; Simonetti, Elena; D'Alonzo, Vincenzo; Caraglia, Michele; Coral, Sandra; De Angelis, Antonina; Cerbone, Luigi; Delfanti, Sara; Giannarelli, Diana; Grosso, Federica; Di Giacomo, Anna Maria; Milione, Massimo; Mortarini, Roberta; Anichini, Andrea; Ceccarelli, Michele; Maio, Michele. - In: NATURE GENETICS. - ISSN 1546-1718. - 58:5(2026), pp. 1100-1111. [10.1038/s41588-026-02580-4]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/1047428
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