New DNA Methylation Signals for Malignant Pleural Mesothelioma Risk Assessment

Our plain-English summary of New DNA Methylation Signals for Malignant Pleural Mesothelioma Risk Assessment, by G. Cugliari, A. Allione, A. Russo, et al (Cancers, 2021).

The study

• Authors: G. Cugliari, A. Allione, A. Russo, C. Catalano, E. Casalone, S. Guarrera, F. Grosso, D. Ferrante, M. Sculco, M. La Vecchia, C. Pirazzini, R. Libener, D. Mirabelli, C. Magnani, I. Dianzani, G. Matullo
• Journal: Cancers
• Published: 2021;13(11)
• Cited by: 8 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

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.

In plain English

This case-control study from Piedmont, Italy, compared DNA methylation (chemical tags on DNA) in blood from people with malignant pleural mesothelioma and cancer-free controls, all with above-background asbestos exposure. Methods list 159 cases and 137 controls; tables list 163 cases. Of 445,254 sites that passed quality control, 12 differed after statistical correction. The authors highlighted two, though Table 1 shows two others meeting their 0.05 effect-size cutoff. An FKBP5 site was less methylated in cases (mean difference on a 0-to-1 scale −0.09, 95% CI −0.12 to −0.06), and an MLLT1 site more (0.07, 95% CI 0.04 to 0.10). Adding either site to a model of asbestos exposure, age, gender and blood-cell estimates raised case-control discrimination (area under the curve) from 0.75 to 0.89. Above-median exposure combined with low FKBP5 methylation gave an odds ratio of 20.84 (95% CI 8.71 to 53.96) versus below-median exposure with high methylation. A separate sample of 140 cases and 104 controls showed the same directions. The authors concluded blood methylation may help develop noninvasive tests, but noted cases already had the disease, so findings likely reflect disease status.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Case-control study with a genome-wide (epigenome-wide) analysis of blood DNA methylation using the Infinium HumanMethylation450 BeadChip, followed by validation in an independent sample using a different method (EpiTYPER MassARRAY)
• Who was studied: 159 malignant pleural mesothelioma (MPM) cases (163 in the abstract and Tables 5 and 6) and 137 cancer-free controls, drawn from a larger case-control study. Controls were 100 men and 37 women; cases were 113 men and 50 women. All had asbestos exposure above background. Cases and controls were matched by date of birth (within plus or minus 18 months) and gender. Subjects came from Casale Monferrato and from main hospitals in Turin, Novara and Alessandria (Piedmont, Italy). A separate validation sample had 140 MPM cases and 104 cancer-free asbestos-exposed controls from the same areas.
• Exposure: Occupational, environmental and domestic asbestos exposure, assessed from interviewer-administered questionnaires by an experienced occupational epidemiologist. Exposure was combined into a cumulative index (fibers/mL years, rank-transformed) using frequency, duration and intensity. The Casale Monferrato exposure originated from the Eternit asbestos-cement plant. Fiber types are not specified.
• Main results:
  • At cg03546163 in the FKBP5 gene, methylation was lower in cases than controls. The mean difference in beta values (on a 0-to-1 scale) was −0.09 (95% CI −0.12 to −0.06, p = 1.2 × 10−7, FDR 0.028). The Results text prints 0.09 without the minus sign; the abstract gives −0.09 and Table 1 gives −0.089.
  • At cg06633438 in the MLLT1 gene, methylation was higher in cases than controls. The mean difference in beta values was 0.07 (95% CI 0.04 to 0.10, p = 1.0 × 10−6, FDR 0.049).
  • 445,254 methylation sites (CpGs) passed quality control and were analysed.
  • The authors state that 10 further sites differed after false discovery rate correction but did not reach the effect-size cutoff of 0.05. However, Table 1 lists two of these sites at or above that cutoff: cg02869235 at 0.058 and cg18860329 at 0.050. Only the FKBP5 and MLLT1 sites carry the table's additional significance marker.
  • A baseline model of asbestos exposure, age, gender and white blood cells gave an area under the curve (AUC) of 0.75. Adding cg03546163 (FKBP5) raised it to 0.89 (DeLong's test 2.1 × 10−7). Adding cg06633438 (MLLT1) also raised it to 0.89 (DeLong's test 6.3 × 10−8).
  • FKBP5 interaction analysis, compared with below-median asbestos exposure plus high methylation:
• Above-median exposure plus low methylation: OR 20.84 (95% CI 8.71 to 53.96, p = 5.5 × 10−11).
• Above-median exposure plus high methylation: OR 7.21 (95% CI 3.17 to 17.27).
• Below-median exposure plus low methylation: OR 2.79 (95% CI 1.26 to 6.33).
  • MLLT1 interaction analysis, compared with below-median asbestos exposure plus low methylation:
• Above-median exposure plus high methylation: OR 11.71 (95% CI 4.97 to 29.64, p = 5.9 × 10−8).
• Above-median exposure plus low methylation: OR 7.27 (95% CI 3.17 to 17.65).
• Below-median exposure plus high methylation: OR 1.29 (95% CI 0.70 to 3.81, p = 0.258), not statistically significant.
  • Asbestos exposure on its own, above-median versus below-median, was associated with mesothelioma: OR 6.11 (95% CI 3.73 to 10.20, p = 1.8 × 10−12).
  • By exposure quartile, compared with the lowest quartile:
• 2nd quartile: OR 1.83 (95% CI 0.93 to 3.69, p = 0.09).
• 3rd quartile: OR 6.63 (95% CI 3.30 to 13.81).
• 4th quartile: OR 11.00 (95% CI 5.26 to 24.30).
  • In the independent validation sample (140 cases, 104 controls), cases had lower methylation at cg03546163 (mean difference −0.061, 95% CI −0.087 to −0.036, p = 4.5 × 10−6). They had higher methylation at cg06633438 (mean difference 0.024, p = 4.0 × 10−2).
  • No evidence was found that smoking status (current, former, never) was linked to methylation differences at any of the 12 significant sites.
• The authors' conclusion: The authors concluded that methylation levels at single sites in the FKBP5 and MLLT1 genes are independent markers of MPM in asbestos-exposed subjects. In their view, this suggests blood methylation analysis could potentially serve as a noninvasive test for MPM detection, if verified in prospectively collected samples.
• Limitations the authors state:
  • Methylation in white blood cells may be a nonspecific marker of general tumour-related inflammation rather than a specific mesothelioma marker.
  • All cases already had mesothelioma at recruitment, so the findings likely reflect disease status rather than processes leading to disease onset.
  • No mesothelioma tissue was available from the same subjects, which limits functional interpretation.

Topics

Medical terms in this study, explained in our Lexicon: Pleural Mesothelioma, Neoplasm, Life Expectancy, Asbestos Exposure, Confounding, Odds Ratio, Discovery.

Related studies

• Peripheral Blood DNA Methylation as Potential Biomarker of Malignant Pleural Mesothelioma in Asbestos-Exposed Subjects — S. Guarrera, C. Viberti, et al. (2019)
• Genetic variants associated with increased risk of malignant pleural mesothelioma: a genome-wide association study — G. Matullo, S. Guarrera, et al. (2013)
• Serum Extracellular Vesicle-Derived microRNAs as Potential Biomarkers for Pleural Mesothelioma in a European Prospective Study — E. Casalone, G. Birolo, et al. (2022)
• Germline mutations in DNA repair genes predispose asbestos-exposed patients to malignant pleural mesothelioma — M. Betti, E. Casalone, et al. (2017)
• XRCC1 and ERCC1 variants modify malignant mesothelioma risk: a case-control study — M. Betti, D. Ferrante, et al. (2011)
• Diagnostics of BAP1-Tumor Predisposition Syndrome by a Multitesting Approach: A Ten-Year-Long Experience — M. Sculco, M. La Vecchia, et al. (2022)

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