Abstract
Simple SummaryOur study investigated DNA methylation differences in easily accessible white blood cells (WBCs) between malignant pleural mesothelioma (MPM) cases and asbestos-exposed cancer-free controls. A multiple regression model highlighted that the methylation level of two single CpGs (cg03546163 in FKBP5 and cg06633438 in MLLT1) are independent MPM markers. The epigenetic changes at the FKBP5 and MLLT1 genes were robustly associated with MPM in asbestos-exposed subjects. Interaction analyses showed that MPM cases and cancer-free controls showed DNAm differences which may be linked to asbestos exposure.Malignant pleural mesothelioma (MPM) is a rare and aggressive neoplasm. Patients are usually diagnosed when current treatments have limited benefits, highlighting the need for noninvasive tests aimed at an MPM risk assessment tool that might improve life expectancy. Three hundred asbestos-exposed subjects (163 MPM cases and 137 cancer-free controls), from the same geographical region in Italy, were recruited. The evaluation of asbestos exposure was conducted considering the frequency, the duration and the intensity of occupational, environmental and domestic exposure. A genome-wide methylation array was performed to identify novel blood DNA methylation (DNAm) markers of MPM. Multiple regression analyses adjusting for potential confounding factors and interaction between asbestos exposure and DNAm on the MPM odds ratio were applied. Epigenome-wide analysis (EWAS) revealed 12 single-CpGs associated with the disease. Two of these showed high statistical power (99%) and effect size (>0.05) after false discovery rate (FDR) multiple comparison corrections: (i) cg03546163 in FKBP5, significantly hypomethylated in cases (Mean Difference in beta values (MD) = −0.09, 95% CI = −0.12|−0.06, p = 1.2 × 10−7), and (ii) cg06633438 in MLLT1, statistically hypermethylated in cases (MD = 0.07, 95% CI = 0.04|0.10, p = 1.0 × 10−6). Based on the interaction analysis, asbestos exposure and epigenetic profile together may improve MPM risk assessment. Above-median asbestos exposure and hypomethylation of cg03546163 in FKBP5 (OR = 20.84, 95% CI = 8.71|53.96, p = 5.5 × 10−11) and hypermethylation of cg06633438 in MLLT1 (OR = 11.71, 95% CI = 4.97|29.64, p = 5.9 × 10−8) genes compared to below-median asbestos exposure and hyper/hypomethylation of single-CpG DNAm, respectively. Receiver Operation Characteristics (ROC) for Case-Control Discrimination showed a significant increase in MPM discrimination when DNAm information was added in the model (baseline model, BM: asbestos exposure, age, gender and white blood cells); area under the curve, AUC = 0.75; BM + cg03546163 at FKBP5. AUC = 0.89, 2.1 × 10−7; BM + cg06633438 at MLLT1. AUC = 0.89, 6.3 × 10−8. Validation and replication procedures, considering independent sample size and a different DNAm analysis technique, confirmed the observed associations. Our results suggest the potential application of DNAm profiles in blood to develop noninvasive tests for MPM risk assessment in asbestos-exposed subjects.
Highlights
Mesothelioma has a long latency period, usually emerging 20–40 years after asbestos exposure [1]
A multivariate analysis confirmed that DNA methylation (DNAm) at cg03546163 in FKBP Prolyl Isomerase 5 (FKBP5) and cg06633438 in MLLT1 were independently associated with Malignant pleural mesothelioma (MPM) detection
We used a whole genome microarray approach to investigate DNAm in WBCs from MPM cases and asbestos-exposed cancer-free controls from a region with a history of asbestos exposure (Piedmont, Italy) [10] in order to identify new noninvasive epigenetic markers related to MPM
Summary
Mesothelioma has a long latency period, usually emerging 20–40 years after asbestos exposure [1]. Fasanelli et al observed an association between exposure to tobacco and site-specific CpG methylation They used peripheral blood DNA to evaluate the importance of these epigenetic alterations in the aetiology of lung cancer [16]. Cancers 2021, 13, 2636 of reliable DNAm biomarkers with high sensitivity and specificity for MPM risk assessment would be a major advancement. DiDffeerRL26een..o13fcnee××rgse11’bsn00eMm2c−−Tt.78ewo3oeimimiidd.nnnneseeIettteellnFFeensddatrrKKnaeiiaaW CWrdaarBBeccannpBPPttseeciiMGh55tvvoottioeeaaonnaawwsBssnllnniuuettnMmmteeddrAeeeaeddsssoosn+cce..ddttbsaggachhtaleen00igymseell66d0es..aiil666iinnstCCn6a33ette3ds33aaee3b44mttrrw4eee33aao3iggs88cctd8htttooeoiiii(trrnnlooMshii(nncceBMMeLaaMDbbxLllLLeTpee)LvvLLtto1owworaaTT)snrrBu11eegiiM..eeaa’rsennbbt+ellwaaeesSsstssi.enbbrg((eeeqqlsseuuttcCoooaapssnnnGeettsiixxiDlldppeeNeooiiArssnne0uumffd.oorr8.ee9rrAammaasUnnaapCddttrDiieooDDidnnfNNfie))crAAtewwonmmrceeserrslleeoee6bvvf.euu3teeMwss×lleessePdde1aaMn0ttcc−cccooogg8rnnni00ssss33ikdii55ddei44reene66rrd11iitnnh66gg33e CpG sites and asbestos exposure were considered as predictors of MPM risk in the interaction model. Considered as predictors of MPM risk in thWee tested the interaction between asbestos exposure and DNAm levels at cg03546163 quantile information) were used considneFrKinBgP5 and cg06633438 in MLLT1.
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