Multi-omic screening for pleural mesothelioma in Asbestos-Exposed Populations: A literature review and Recommendations

Lung Cancer 2026 February [Link]

Kathleen Zwijsen, Ellen Heirwegh, Eline Schillebeeckx, Elly Marcq, Adrian Covaci, Ken Op de Beeck, Jan P van Meerbeeck, Jo Raskin, Annelies Janssens, Annemiek Snoeckx, Kevin Lamote

Abstract

Objectives: Pleural mesothelioma (PM) is an aggressive thoracic cancer related to historical exposure to asbestos fibres. Symptoms often appear at an advanced stage, leading to delayed diagnosis and dismal prognosis. Early diagnosis is thus crucial in improving patient outcome. Current biomarker research for early detection focuses on different -omics research fields (genomics, proteomics, transcriptomics, metabolomics and volatomics), however with no clinically useful result. Moreover, currently no screening program is advocated for asymptomatic individuals with an established asbestos exposure. The aim of this review is to summarise the advances in different -omics fields and to pinpoint state-of-the art biomarkers with the highest potential to serve as primary targets in clinical trials for early PM detection or screening.

Methods: A literature search was performed in the databases MEDLINE and Web Of Science. Research articles published before 1 August 2025 were eligible.

Results: In total, 63 articles were included in this review, with specific focus on radiomics, genomics, transcriptomics, epigenomics, proteomics, metabolomics, and volatomics. Several research groups have focused on investigating biomarkers or screening techniques for pleural mesothelioma among individuals with a history of asbestos exposure. Notable approaches include using low-dose Computed Tomography, and determining mesothelin levels and micro-RNAs in blood, and volatile organic compounds in exhaled breath.

Discussion: Single biomarkers like miRNAs, mesothelin, and VOCs show promise, but further validation is needed in larger cohorts with correct control groups. A multi-omics approach, which integrates biomarker panels from various -omics areas, has the potential to enhance diagnostic accuracy.