Integrating polygenic and methylation risk scores for pleural mesothelioma risk stratification

Pleural mesothelioma (PM) is a lethal cancer primarily caused by asbestos exposure. Not all exposed individuals develop PM, suggesting the involvement of additional factors. This underscores the need for robust predictive models integrating biomarkers from multi-omic domains to improve risk stratification and early detection. We developed and evaluated polygenic risk scores (PRS) and methylation risk scores (MRS) using a retrospective case-control study (749 participants: 387 PM cases, 362 controls) and a nested case-control European Prospective Investigation into Cancer and Nutrition (EPIC)-Meso study (268 participants: 134 preclinical PM cases, 134 matched controls) within the EPIC cohort. Genome-wide association analyses in the retrospective case-control study identified PM-associated variants. The PRS (1123 SNPs with p < 0.001) in the retrospective training subset stratified disease risk in the test set (ORs 3.46-9.54 across top percentiles) and improved model discrimination (AUC = 0.75 vs. 0.71 in baseline model, p = 0.04). In EPIC-Meso, PRS performance was limited (AUC = 0.52). External validation in the UK-Biobank (UKBB) confirmed a modest but consistent association with PM-risk. A Meta-PRS derived from the UKBB-FinnGen meta-analysis replicated this trend in the full retrospective dataset, showing higher OR across top percentiles (2.5-12.3) and improved discrimination (AUC 0.74 vs. 0.72, p = 0.016). MRS, with 68 differentially methylated CpGs (effect-size >|0.10|, FDR p < 0.05) in the retrospective training set, increased the AUC from 0.66 to 0.85 (p < 0.001) in the test set and from 0.51 to 0.62 in EPIC-Meso. PRS was most predictive in low-exposure groups, while MRS remained robust across exposure levels. Combined PRS-MRS models improved discrimination. Integrating multi-omic biomarkers can enhance PM-risk stratification and support earlier, targeted interventions in high-risk asbestos-exposed groups.

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Publication Details

Journal
International Journal of Cancer
Published
2025-12-30
DOI
https://doi.org/10.1002/ijc.70316
Primary Topic
Occupational and environmental lung diseases
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating polygenic and methylation risk scores for pleural mesothelioma risk stratification

Giovanna Tagliabue, Elton Jalis Herman, Corrado Enrico Magnani, Khadija Sana Hafeez et al.
International Journal of Cancer
Occupational and environmental lung diseases
article

Integrating polygenic and methylation risk scores for pleural mesothelioma risk stratification

Giovanna Tagliabue, Elton Jalis Herman, Corrado Enrico Magnani, Khadija Sana Hafeez, Anna Aspesi, Carla Debernardi, Irma Dianzani, Carlotta Sacerdote, Matthias Bernd Schulze, Marta La Vecchia, F. Grosso, Elisabetta Casalone, Simonetta Guarrera, Giovanna Masala, P. Vineis, S. Panico, Anne Marie Tjønneland, Giuseppe Matullo, Elisabete Weiderpass, Daniela Ferrante, Antonio Agudo, Alessandra Allione, Yaszan Asgari, Marcela Guevara, Marika Sculco, Christina M. Lill, Seehyun Park
article en

Abstract

Pleural mesothelioma (PM) is a lethal cancer primarily caused by asbestos exposure. Not all exposed individuals develop PM, suggesting the involvement of additional factors. This underscores the need for robust predictive models integrating biomarkers from multi-omic domains to improve risk stratification and early detection. We developed and evaluated polygenic risk scores (PRS) and methylation risk scores (MRS) using a retrospective case-control study (749 participants: 387 PM cases, 362 controls) and a nested case-control European Prospective Investigation into Cancer and Nutrition (EPIC)-Meso study (268 participants: 134 preclinical PM cases, 134 matched controls) within the EPIC cohort. Genome-wide association analyses in the retrospective case-control study identified PM-associated variants. The PRS (1123 SNPs with p < 0.001) in the retrospective training subset stratified disease risk in the test set (ORs 3.46-9.54 across top percentiles) and improved model discrimination (AUC = 0.75 vs. 0.71 in baseline model, p = 0.04). In EPIC-Meso, PRS performance was limited (AUC = 0.52). External validation in the UK-Biobank (UKBB) confirmed a modest but consistent association with PM-risk. A Meta-PRS derived from the UKBB-FinnGen meta-analysis replicated this trend in the full retrospective dataset, showing higher OR across top percentiles (2.5-12.3) and improved discrimination (AUC 0.74 vs. 0.72, p = 0.016). MRS, with 68 differentially methylated CpGs (effect-size >|0.10|, FDR p < 0.05) in the retrospective training set, increased the AUC from 0.66 to 0.85 (p < 0.001) in the test set and from 0.51 to 0.62 in EPIC-Meso. PRS was most predictive in low-exposure groups, while MRS remained robust across exposure levels. Combined PRS-MRS models improved discrimination. Integrating multi-omic biomarkers can enhance PM-risk stratification and support earlier, targeted interventions in high-risk asbestos-exposed groups.

International Journal of Cancer
Università degli Studi del Piemonte Orientale “Amedeo Avogadro” (IT), Inserm (FR), Universidad Pública de Navarra (UPNA) (ES), University of Potsdam (DE), University of Münster (DE), Prevention Institute (US), Institut Gustave Roussy (FR), Bellvitge University Hospital (ES), Public Health England (GB), Instituto de Salud Pública de Navarra (ES), Azienda Ospedaliera Citta' della Salute e della Scienza di Torino (IT), Institut d'Investigació Biomédica de Bellvitge (ES), Institut Català d'Oncologia (ES), Department of Medical Sciences (RU), Navarre Institute of Health Research (ES), Federico II University Hospital (IT), National Cancer Registry (IE), Italian institute for Genomic Medicine (IT), National Cancer Institute (UA), National Cancer Institute (MY), Danish Cancer Society (DK), Candiolo Cancer Institute (IT), Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (ES), Piedmont University (US), Azienda Ospedaliera Nazionale SS. Antonio e Biagio e Cesare Arrigo (IT), Novamont (Italy) (IT), German Institute of Human Nutrition (DE), Centre international de recherche sur le cancer (FR), Imperial College London (GB), University of Turin (IT)
Gender equality
Openalex Percentile: Top 27%
Occupational and environmental lung diseases
DOIOpen Access PDFOpenAlex
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