DNA methylation changes measured in pre-diagnostic peripheral blood samples are associated with smoking and lung cancer risk

Epigenome-wide association study of lung cancer among never smokers in two prospective cohorts in Shanghai, China

BACKGROUND

The aetiology of lung cancer among individuals who never smoked remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Epigenetic alterations, particularly DNA methylation (DNAm) changes, have emerged as potential drivers. Yet, few prospective epigenome-wide association studies (EWAS), primarily focusing on peripheral blood DNAm with limited representation of never smokers, have been conducted.

METHODS

We conducted a nested case-control study of 80 never-smoking incident lung cancer cases and 83 never-smoking controls within the Shanghai Women's Health Study and Shanghai Men's Health Study. DNAm was measured in prediagnostic oral rinse samples using Illumina MethylationEPIC array. Initially, we conducted an EWAS to identify differentially methylated positions (DMPs) associated with lung cancer in the discovery sample of 101 subjects. The top 50 DMPs were further evaluated in a replication sample of 62 subjects, and results were pooled using fixed-effect meta-analysis.

RESULTS

Our study identified three DMPs significantly associated with lung cancer at the epigenome-wide significance level of p<8.22×10-8. These DMPs were identified as cg09198866 (MYH9; TXN2), cg01411366 (SLC9A10) and cg12787323. Furthermore, examination of the top 1000 DMPs indicated significant enrichment in epithelial regulatory regions and their involvement in small GTPase-mediated signal transduction pathways. Additionally, GrimAge acceleration was identified as a risk factor for lung cancer (OR=1.19 per year; 95% CI 1.06 to 1.34).

CONCLUSIONS

While replication in a larger sample size is necessary, our findings suggest that DNAm patterns in prediagnostic oral rinse samples could provide novel insights into the underlying mechanisms of lung cancer in never smokers.

Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis

Tobacco use is a major modifiable risk factor for adverse health outcomes, including cancer, and elicits profound epigenetic changes thought to be associated with long-term cancer risk. While electronic cigarettes (e-cigarettes) have been advocated as harm reduction alternatives to tobacco products, recent studies have revealed potential detrimental effects, highlighting the urgent need for further research into the molecular and health impacts of e-cigarettes. Here, we applied computational deconvolution methods to dissect the cell- and tissue-specific epigenetic effects of tobacco or e-cigarette use on DNA methylation (DNAme) in over 3,500 buccal/saliva, cervical, or blood samples, spanning epithelial and immune cells at directly and indirectly exposed sites. The 535 identified smoking-related DNAme loci [cytosine-phosphate-guanine sites (CpG)] clustered into four functional groups, including detoxification or growth signaling, based on cell type and anatomic site. Loci hypermethylated in buccal epithelial cells of smokers associated with NOTCH1/RUNX3/growth factor receptor signaling also exhibited elevated methylation in cancer tissue and progressing lung carcinoma in situ lesions, and hypermethylation of these sites predicted lung cancer development in buccal samples collected from smokers up to 22 years prior to diagnosis, suggesting a potential role in driving carcinogenesis. Alarmingly, these CpGs were also hypermethylated in e-cigarette users with a limited smoking history. This study sheds light on the cell type-specific changes to the epigenetic landscape induced by smoking-related products.

SIGNIFICANCE

The use of both cigarettes and e-cigarettes elicits cell- and exposure-specific epigenetic effects that are predictive of carcinogenesis, suggesting caution when broadly recommending e-cigarettes as aids for smoking cessation.

The association of cigarette smoking with DNA methylation and gene expression in human tissue samples

Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n = 212) and 2,735 in colon tissue (n = 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls

BACKGROUND

Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated.

METHODS

The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways.

RESULTS

Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified.

CONCLUSIONS

Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby.

PLAIN LANGUAGE SUMMARY

The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

The Influence of Smoking and Occupational Risk Factors on DNA Methylation in the AHRR and F2RL3 Genes

BACKGROUND

AHRR and F2RL3 hypomethylation has been associated with lung cancer. In this study, we investigated the cross-sectional association between smoking and occupational exposures, and AHRR and F2RL3 methylation.

METHODS

A case-control study was nested in CARTaGENE to examine the association between AHRR and F2RL3 methylation and lung cancer risk (200 cases; 400 controls). A secondary analysis was conducted using the data collected from this nested study; namely, baseline information on participants' smoking behavior and longest-held job was obtained. A cumulative smoking index summarized information on the number of cigarettes smoked, duration of smoking, and time since cessation. Exposure to 13 occupational agents was estimated using the Canadian Job Exposure Matrix. In baseline blood samples, methylation ratios of 40 CpG sites in the AHRR and F2RL3 genes were measured using Sequenom EpiTYPER. Separate least squares regression models were used to estimate the associations between smoking and occupational exposures, and average AHRR and F2RL3 methylation levels, while adjusting for confounders identified from directed acyclic graphs.

RESULTS

In both genes, smoking was associated with lower average methylation levels. Occupational exposure to aromatic amines, cadmium, and formaldehyde were associated with lower AHRR methylation while, only benzene was associated with F2RL3 hypomethylation; these associations were stronger among ever smokers.

CONCLUSIONS

Our findings support that smoking and occupational exposures to some agents are associated with AHRR and F2RL3 hypomethylation.

IMPACT

Our results inform on mechanisms underlying environmental exposures in lung cancer etiology; future studies should prioritize studying joint exposures.

Hypomethylation of DYRK4 in peripheral blood is associated with increased lung cancer risk

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. It is urgent to identify new biomarkers for the early detection of LC. DNA methylation in peripheral blood has been reported to be associated with cancers. We conducted two independent case-control studies and a nested case-control study (168 LC cases and 167 controls in study Ⅰ, 677 LC cases and 833 controls in study Ⅱ, 147 precancers and 21 controls in the nested case-control study). The methylation levels of DYRK4 CpG sites were measured using mass spectrometry and their correlations with LC were analyzed by logistic regression and nonparametric tests. Bonferroni correction was used for the multiple comparisons. LC-related decreased DYRK4 methylation was discovered in Study I and validated in Study II (the odds ratios [ORs] for the lowest vs. highest quartile of all three DYRK4 CpG sites ranged from 1.64 to 2.09, all p < 0.001). Combining the two studies, hypomethylation of DYRK4 was observed in stage I cases (ORs per -10% methylation ranged from 1.16 to 1.38, all p < 5.9E-04), and could be enhanced by male gender (ORs ranged from 1.77 to 4.17 via interquartile analyses, all p < 0.017). Hypomethylation of DYRK4_A_CpG_2 was significantly correlated with tumor size, length, and stage (p = 0.034, 0.002, and 0.002, respectively) in LC cases. Our study disclosed the association between DYRK4 hypomethylation in peripheral blood and LC, suggesting the feasibility of blood-based DNA methylation as new biomarker for LC detection.

Smoking, blood DNA methylation sites and lung cancer risk

Altered DNA methylation (DNAm) might be a biological intermediary in the pathway from smoking to lung cancer. In this study, we investigated the contribution of differential blood DNAm to explain the association between smoking and lung cancer incidence. Blood DNAm was measured in 2321 Strong Heart Study (SHS) participants. Incident lung cancer was assessed as time to event diagnoses. We conducted mediation analysis, including validation with DNAm and paired gene expression data from the Framingham Heart Study (FHS). In the SHS, current versus never smoking and pack-years single-mediator models showed, respectively, 29 and 21 differentially methylated positions (DMPs) for lung cancer with statistically significant mediated effects (14 of 20 available, and five of 14 available, positions, replicated, respectively, in FHS). In FHS, replicated DMPs showed gene expression downregulation largely in trans, and were related to biological pathways in cancer. The multimediator model identified that DMPs annotated to the genes AHRR and IER3 jointly explained a substantial proportion of lung cancer. Thus, the association of smoking with lung cancer was partly explained by differences in baseline blood DNAm at few relevant sites. Experimental studies are needed to confirm the biological role of identified eQTMs and to evaluate potential implications for early detection and control of lung cancer.

Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer

Methylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven case-control studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B-cell lymphoma (N cases = 3123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per SD increase of the MS, with and without adjustment for health-related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR = 1.5-1.7) with lung cancer risk for smoking MS; moderate associations (RR = 1.2-1.3) with urothelial cancer risk for smoking MS and with mature B-cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR = 1.1-1.2) for BMI and alcohol MS with several cancer types and cancer overall. Generally small AUC increases were observed after inclusion of several MS in the same model (colorectal, gastric, kidney, urothelial cancers: +3%; lung cancer: +7%; B-cell neoplasms: +8%). Methylation scores for smoking, BMI and alcohol consumption show independent associations with cancer risk, and may provide some improvements in risk prediction.

Household air pollution and epigenetic aging in Xuanwei, China

BACKGROUND

Household air pollution (HAP) from indoor combustion of solid fuel is a global health burden linked to lung cancer. In Xuanwei, China, lung cancer rate for nonsmoking women is among the highest in the world and largely attributed to high levels of polycyclic aromatic hydrocarbons (PAHs) that are produced from combustion of smoky (bituminous) coal used for cooking and heating. Epigenetic age acceleration (EAA), a DNA methylation-based biomarker of aging, has been shown to be highly correlated with biological processes underlying the susceptibility of age-related diseases. We aim to assess the association between HAP exposure and EAA.

METHODS

We analyzed data from 106 never-smoking women from Xuanwei, China. Information on fuel type was collected using a questionnaire, and validated exposure models were used to predict levels of 43 HAP constituents. Exposure clusters were identified using hierarchical clustering. EAA was derived for five epigenetic clocks defined as the residuals resulting from regressing each clock on chronological age. We used generalized estimating equations to test associations between exposure clusters derived from predicted levels of HAP exposure, ambient 5-methylchrysene (5-MC), a PAH previously found to be associated with risk of lung cancer, and EAA, while accounting for repeated-measurements and confounders.

RESULTS

We observed an increase in GrimAge EAA for clusters with 31 and 33 PAHs reflecting current (β = 0.77 y per standard deviation (SD) increase, 95 % CI:0.36,1.19) and childhood (β = 0.92 y per SD, 95 % CI:0.40,1.45) exposure, respectively. 5-MC (ng/m3-year) was found to be associated with GrimAge EAA for current (β = 0.15 y, 95 % CI:0.05,0.25) and childhood (β = 0.30 y, 95 % CI:0.13,0.47) exposure.

CONCLUSIONS

Our findings suggest that exposure to PAHs from indoor smoky coal combustion, particularly 5-MC, is associated with GrimAge EAA, a biomarker of mortality.

Changing Smoking Behavior and Epigenetics: A Longitudinal Study of 4,432 Individuals From the General Population

BACKGROUND

Hypomethylation of the aryl hydrocarbon receptor repressor (AHRR) gene indicates long-term smoking exposure and might therefore be a monitor for smoking-induced disease risk. However, studies of individual longitudinal changes in AHRR methylation are sparse.

RESEARCH QUESTION

How does the recovery of AHRR methylation depend on change in smoking behaviors and demographic variables?

STUDY DESIGN AND METHODS

This study included 4,432 individuals from the Copenhagen City Heart Study, with baseline and follow-up blood samples and smoking information collected approximately 10 years apart. AHRR methylation at the cg05575921 site was measured in bisulfite-treated leukocyte DNA. Four smoking groups were defined: participants who never smoked (Never-Never), participants who formerly smoked (Former-Former), participants who quit during the study period (Current-Former), and individuals who smoked at both baseline and follow-up (Current-Current). Methylation recovery was defined as the increase in AHRR methylation between baseline and follow-up examination.

RESULTS

Methylation recovery was highest among participants who quit, with a median methylation recovery of 5.58% (interquartile range, 1.79; 9.15) vs 1.64% (interquartile range, -1.88; 4.96) in the Current-Current group (P < .0001). In individuals who quit smoking, older age was associated with lower methylation recovery (P < .0001). In participants who quit aged > 65 years, methylation recovery was 5.9% at 5.6 years after quitting; methylation recovery was 8.5% after 2.8 years for participants who quit aged < 55 years.

INTERPRETATION

AHRR methylation recovered after individuals quit smoking, and recovery was more pronounced and occurred faster in younger compared with older interim quitters.

Unraveling the Post-Translational Modifications and therapeutical approach in NSCLC pathogenesis

Non-Small Cell Lung Cancer (NSCLC) is the most prevalent kind of lung cancer with around 85% of total lung cancer cases. Despite vast therapies being available, the survival rate is low (5 year survival rate is 15%) making it essential to comprehend the mechanism for NSCLC cell survival and progression. The plethora of evidences suggests that the Post Translational Modification (PTM) such as phosphorylation, methylation, acetylation, glycosylation, ubiquitination and SUMOylation are involved in various types of cancer progression and metastasis including NSCLC. Indeed, an in-depth understanding of PTM associated with NSCLC biology will provide novel therapeutic targets and insight into the current sophisticated therapeutic paradigm. Herein, we reviewed the key PTMs, epigenetic modulation, PTMs crosstalk along with proteogenomics to analyze PTMs in NSCLC and also, highlighted how epi‑miRNA, miRNA and PTM inhibitors are key modulators and serve as promising therapeutics.

Possible regulation of ganglioside GD3 synthase gene expression with DNA methylation in human glioma cells

Gangliosides are expressed in nervous systems and some neuroectoderm-derived tumors at high levels and play pivotal roles. However, mechanisms for the regulation of glycosyltransferase genes responsible for the ganglioside synthesis are not well understood. In this study, we analyzed DNA methylation patterns of promoter regions of GD3 synthase (ST8SIA1) as well as mRNA levels and ganglioside expression using human glioma cell lines. Among 5 cell lines examined, 4 lines showed changes in the expression levels of related genes after treatment with 5-aza-dC. LN319 showed up-regulation of St8sia1 and increased b-series gangliosides after 5-aza-dC treatment, and an astrocytoma cell line, AS showed high expression of ST8SIA1 and b-series gangliosides persistently before and after 5-Aza-2'-deoxycytidine treatment. Using these 2 cell lines, DNA methylation patterns of the promoter regions of the gene were analyzed by bisulfite-sequencing. Consequently, 2 regions that were methylated before 5-Aza-2'-deoxycytidine treatment were demethylated in LN319 after the treatment, while those regions were persistently demethylated in AS. These 2 regions corresponded with sites defined as promoter regions by Luciferase assay. Taken together, it was suggested that ST8SIA1 gene is regulated by DNA methylation at the promoter regions, leading to the regulation of tumor phenotypes.

Prognostic prediction of lung adenocarcinoma by integrative analysis of RHOH expression and methylation

BACKGROUND AND OBJECTIVE

The development of epigenetics holds great promise for diagnosis and treatment of lung adenocarcinoma (LUAD). The purpose of this work was to analyze the correlation between Ras Homolog Gene Family Member H (RHOH) expression and methylation in patients with LUAD and its association with survival.

METHODS

Data related to gene expression, DNA methylation, and clinical features of LUAD from The Cancer Genome Atlas (TCGA) database were analyzed. A total of 50 patients were included in verification group. The methylation level of RHOH in verification group was detected by bisulfite amplicon sequencing.

RESULTS

The RHOH methylation level in TCGA cohort was significantly and negatively correlated with its expression level (Cor = -0.5, p = 2.687e-33). Patients with hypermethylation and low expression of RHOH had significantly worse prognosis than patients with hypomethylation and low expression of RHOH (TCGA: p = 0.004; validation cohort: p = 0.006, HR: 4.740, 95% CI: 1.567-14.340).

CONCLUSION

Our research revealed that RHOH may prove to be a new potential prognostic predictor for LUAD patients.

DNA-Methylation Signatures of Tobacco Smoking in a High Cardiovascular Risk Population: Modulation by the Mediterranean Diet

Biomarkers based on DNA methylation are relevant in the field of environmental health for precision health. Although tobacco smoking is one of the factors with a strong and consistent impact on DNA methylation, there are very few studies analyzing its methylation signature in southern European populations and none examining its modulation by the Mediterranean diet at the epigenome-wide level. We examined blood methylation smoking signatures on the EPIC 850 K array in this population (n = 414 high cardiovascular risk subjects). Epigenome-wide methylation studies (EWASs) were performed analyzing differential methylation CpG sites by smoking status (never, former, and current smokers) and the modulation by adherence to a Mediterranean diet score was explored. Gene-set enrichment analysis was performed for biological and functional interpretation. The predictive value of the top differentially methylated CpGs was analyzed using receiver operative curves. We characterized the DNA methylation signature of smoking in this Mediterranean population by identifying 46 differentially methylated CpGs at the EWAS level in the whole population. The strongest association was observed at the cg21566642 (p = 2.2 × 10-32) in the 2q37.1 region. We also detected other CpGs that have been consistently reported in prior research and discovered some novel differentially methylated CpG sites in subgroup analyses. In addition, we found distinct methylation profiles based on the adherence to the Mediterranean diet. Particularly, we obtained a significant interaction between smoking and diet modulating the cg5575921 methylation in the AHRR gene. In conclusion, we have characterized biomarkers of the methylation signature of tobacco smoking in this population, and suggest that the Mediterranean diet can increase methylation of certain hypomethylated sites.

Epigenetic age and lung cancer risk in the CLUE II prospective cohort study

BACKGROUND

Epigenetic age, a robust marker of biological aging, has been associated with obesity, low-grade inflammation and metabolic diseases. However, few studies have examined associations between different epigenetic age measures and risk of lung cancer, despite great interest in finding biomarkers to assist in risk stratification for lung cancer screening.

METHODS

A nested case-control study of lung cancer from the CLUE II cohort study was conducted using incidence density sampling with 1:1 matching of controls to lung cancer cases (n = 208 matched pairs). Prediagnostic blood samples were collected in 1989 (CLUE II study baseline) and stored at -70°C. DNA was extracted from buffy coat and DNA methylation levels were measured using Illumina MethylationEPIC BeadChip Arrays. Three epigenetic age acceleration (i.e., biological age is greater than chronological age) measurements (Horvath, Hannum and PhenoAge) were examined in relation to lung cancer risk using conditional logistic regression.

RESULTS

We did not observe associations between the three epigenetic age acceleration measurements and risk of lung cancer overall; however, inverse associations for the two Hannum age acceleration measures (intrinsic and extrinsic) were observed in men and among younger participants, but not in women or older participants. We did not observe effect modification by time from blood draw to diagnosis.

CONCLUSION

Findings from this study do not support a positive association between three different biological age acceleration measures and risk of lung cancer. Additional studies are needed to address whether epigenetic age is associated with lung cancer in never smokers.

Genetic differences between smokers and never-smokers with lung cancer

Smoking is a major risk factor for lung cancer, therefore lung cancer epidemiological trends reflect the past trends of cigarette smoking to a great extent. The geographic patterns in mortality closely follow those in incidence. Although lung cancer is strongly associated with cigarette smoking, only about 15% of smokers get lung cancer, and also some never-smokers develop this malignancy. Although less frequent, lung cancer in never smokers is the seventh leading cause of cancer deaths in both sexes worldwide. Lung cancer in smokers and never-smokers differs in many aspects: in histological types, environmental factors representing a risk, and in genes associated with this disease. In this review, we will focus on the genetic differences between lung cancer in smokers versus never-smokers: gene expression, germ-line polymorphisms, gene mutations, as well as ethnic and gender differences. Finally, treatment options for smokers and never-smokers will be briefly reviewed.

DNA and histone modifications as potent diagnostic and therapeutic targets to advance non-small cell lung cancer management from the perspective of 3P medicine

Lung cancer has a very high mortality in females and males. Most (~ 85%) of lung cancers are non-small cell lung cancers (NSCLC). When lung cancer is diagnosed, most of them have either local or distant metastasis, with a poor prognosis. In order to achieve better outcomes, it is imperative to identify the molecular signature based on genetic and epigenetic variations for different NSCLC subgroups. We hypothesize that DNA and histone modifications play significant roles in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine). Epigenetics has a significant impact on tumorigenicity, tumor heterogeneity, and tumor resistance to chemotherapy, targeted therapy, and immunotherapy. An increasing interest is that epigenomic regulation is recognized as a potential treatment option for NSCLC. Most attention has been paid to the epigenetic alteration patterns of DNA and histones. This article aims to review the roles DNA and histone modifications play in tumorigenesis, early detection and diagnosis, and advancements and therapies of NSCLC, and also explore the connection between DNA and histone modifications and PPPM, which may provide an important contribution to improve the prognosis of NSCLC. We found that the success of targeting DNA and histone modifications is limited in the clinic, and how to combine the therapies to improve patient outcomes is necessary in further studies, especially for predictive diagnostics, targeted prevention, and personalization of medical services in the 3P medicine approach. It is concluded that DNA and histone modifications are potent diagnostic and therapeutic targets to advance non-small cell lung cancer management from the perspective of 3P medicine.

Intake of vegetables and fruits rich in provitamin A is positively associated with aryl hydrocarbon receptor repressor DNA methylation in a Japanese population

DNA methylation can be affected by numerous lifestyle factors, including diet. Tobacco smoking induces aryl hydrocarbon receptor repressor (AHRR) DNA hypomethylation, which increases the risk of lung and other cancers. However, no lifestyle habits that might increase or restore percentage of AHRR DNA methylation have been identified. We hypothesized that dietary intakes of vegetables/fruits and serum carotenoid concentrations are related to AHRR DNA methylation. A total of 813 individuals participated in this cross-sectional study. A food frequency questionnaire was used to assess dietary intake of vegetables and fruits. AHRR DNA methylation in peripheral blood mononuclear cells were measured using pyrosequencing method. In men, dietary fruit intake was significantly and positively associated with AHRR DNA methylation among current smokers (P for trend = .034). A significant positive association of serum provitamin A with AHRR DNA methylation was observed among current smokers (men: standardized β = 0.141 [0.045 to 0.237], women: standardized β = 0.570 [0.153 to 0.990]). However, compared with never smokers with low provitamin A concentrations, percentages of AHRR DNA methylation were much lower among current smokers, even those with high provitamin A concentrations (men: β = -19.1% [-33.8 to -19.8], women: β = -6.0% [-10.2 to -1.7]). Dietary intake of vegetables and fruits rich in provitamin A may increase percentage of AHRR DNA methylation in current smokers. However, although we found a beneficial effect of provitamin A on AHRR DNA methylation, this beneficial effect could not completely remove the effect of smoking on AHRR DNA demethylation.

Identification of NHLRC1 as a Novel AKT Activator from a Lung Cancer Epigenome-Wide Association Study (EWAS)

Changes in DNA methylation identified by epigenome-wide association studies (EWAS) have been recently linked to increased lung cancer risk. However, the cellular effects of these differentially methylated positions (DMPs) are often unclear. Therefore, we investigated top differentially methylated positions identified from an EWAS study. This included a putative regulatory region of NHLRC1. Hypomethylation of this gene was recently linked with decreased survival rates in lung cancer patients. HumanMethylation450 BeadChip array (450K) analysis was performed on 66 lung cancer case-control pairs from the European Prospective Investigation into Cancer and Nutrition Heidelberg lung cancer EWAS (EPIC HD) cohort. DMPs identified in these pre-diagnostic blood samples were then investigated for differential DNA methylation in lung tumor versus adjacent normal lung tissue from The Cancer Genome Atlas (TCGA) and replicated in two independent lung tumor versus adjacent normal tissue replication sets with MassARRAY. The EPIC HD top hypermethylated DMP cg06646708 was found to be a hypomethylated region in multiple data sets of lung tumor versus adjacent normal tissue. Hypomethylation within this region caused increased mRNA transcription of the closest gene NHLRC1 in lung tumors. In functional assays, we demonstrate attenuated proliferation, viability, migration, and invasion upon NHLRC1 knock-down in lung cancer cells. Furthermore, diminished AKT phosphorylation at serine 473 causing expression of pro-apoptotic AKT-repressed genes was detected in these knock-down experiments. In conclusion, this study demonstrates the powerful potential for discovery of novel functional mechanisms in oncogenesis based on EWAS DNA methylation data. NHLRC1 holds promise as a new prognostic biomarker for lung cancer survival and prognosis, as well as a target for novel treatment strategies in lung cancer patients.

Epigenome-wide DNA methylation signature of plasma zinc and their mediation roles in the association of zinc with lung cancer risk

Essential trace element zinc is associated with decreased lung cancer risk, but underlying mechanisms remain unclear. This study aimed to investigate role of DNA methylation in zinc-lung cancer association. We conducted a case-cohort study within prospective Dongfeng-Tongji cohort, including 359 incident lung cancer cases and a randomly selected sub-cohort of 1399 participants. Epigenome-wide association study (EWAS) was used to examine association of plasma zinc with DNA methylation in peripheral blood. For the zinc-related CpGs, their mediation effects on zinc-lung cancer association were assessed; their diagnostic performance for lung cancer was testified in the case-cohort study and further validated in another 126 pairs of lung cancer case-control study. We identified 28 CpGs associated with plasma zinc at P < 1.0 × 10^-5 and seven of them (cg07077080, cg01077808, cg17749033, cg15554270, cg26125625, cg10669424, and cg15409013 annotated to GSR, CALR3, SLC16A3, PHLPP2, SLC12A8, VGLL4, and ADAMTS16, respectively) were associated with incident risk of lung cancer. Moreover, the above seven CpGs were differently methylated between 126 pairs of lung cancer and adjacent normal lung tissues and had the same directions with EWAS of zinc. They could mediate a separate 7.05%∼22.65% and a joint 29.42% of zinc-lung cancer association. Compared to using traditional factors, addition of methylation risk score exerted improved discriminations for lung cancer both in case-cohort study [area under the curve (AUC) = 0.818 vs. 0.738] and in case-control study (AUC = 0.816 vs. 0.646). Our results provide new insights for the biological role of DNA methylation in the inverse association of zinc with incident lung cancer.

Epigenetic mechanisms of lung carcinogenesis involve differentially methylated CpG sites beyond those associated with smoking

Smoking-related epigenetic changes have been linked to lung cancer, but the contribution of epigenetic alterations unrelated to smoking remains unclear. We sought for a sparse set of CpG sites predicting lung cancer and explored the role of smoking in these associations. We analysed CpGs in relation to lung cancer in participants from two nested case-control studies, using (LASSO)-penalised regression. We accounted for the effects of smoking using known smoking-related CpGs, and through conditional-independence network. We identified 29 CpGs (8 smoking-related, 21 smoking-unrelated) associated with lung cancer. Models additionally adjusted for Comprehensive Smoking Index-(CSI) selected 1 smoking-related and 49 smoking-unrelated CpGs. Selected CpGs yielded excellent discriminatory performances, outperforming information provided by CSI only. Of the 8 selected smoking-related CpGs, two captured lung cancer-relevant effects of smoking that were missed by CSI. Further, the 50 CpGs identified in the CSI-adjusted model complementarily explained lung cancer risk. These markers may provide further insight into lung cancer carcinogenesis and help improving early identification of high-risk patients.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

DNA Methylation in Lung Cancer: Mechanisms and Associations with Histological Subtypes, Molecular Alterations, and Major Epidemiological Factors

Lung cancer is the major leading cause of cancer-related mortality worldwide. Multiple epigenetic factors-in particular, DNA methylation-have been associated with the development of lung cancer. In this review, we summarize the current knowledge on DNA methylation alterations in lung tumorigenesis, as well as their associations with different histological subtypes, common cancer driver gene mutations (e.g., KRAS, EGFR, and TP53), and major epidemiological risk factors (e.g., sex, smoking status, race/ethnicity). Understanding the mechanisms of DNA methylation regulation and their associations with various risk factors can provide further insights into carcinogenesis, and create future avenues for prevention and personalized treatments. In addition, we also highlight outstanding questions regarding DNA methylation in lung cancer to be elucidated in future studies.

Epigenetic Regulation of F2RL3 Associates With Myocardial Infarction and Platelet Function

BACKGROUND

DNA hypomethylation at the F2RL3 (F2R like thrombin or trypsin receptor 3) locus has been associated with both smoking and atherosclerotic cardiovascular disease; whether these smoking-related associations form a pathway to disease is unknown. F2RL3 encodes protease-activated receptor 4, a potent thrombin receptor expressed on platelets. Given the role of thrombin in platelet activation and the role of thrombus formation in myocardial infarction, alterations to this biological pathway could be important for ischemic cardiovascular disease.

METHODS

We conducted multiple independent experiments to assess whether DNA hypomethylation at F2RL3 in response to smoking is associated with risk of myocardial infarction via changes to platelet reactivity. Using cohort data (N=3205), we explored the relationship between smoking, DNA hypomethylation at F2RL3, and myocardial infarction. We compared platelet reactivity in individuals with low versus high DNA methylation at F2RL3 (N=41). We used an in vitro model to explore the biological response of F2RL3 to cigarette smoke extract. Finally, a series of reporter constructs were used to investigate how differential methylation could impact F2RL3 gene expression.

RESULTS

Observationally, DNA methylation at F2RL3 mediated an estimated 34% of the smoking effect on increased risk of myocardial infarction. An association between methylation group (low/high) and platelet reactivity was observed in response to PAR4 (protease-activated receptor 4) stimulation. In cells, cigarette smoke extract exposure was associated with a 4.9% to 9.3% reduction in DNA methylation at F2RL3 and a corresponding 1.7-(95% CI, 1.2-2.4, P=0.04) fold increase in F2RL3 mRNA. Results from reporter assays suggest the exon 2 region of F2RL3 may help control gene expression.

CONCLUSIONS

Smoking-induced epigenetic DNA hypomethylation at F2RL3 appears to increase PAR4 expression with potential downstream consequences for platelet reactivity. Combined evidence here not only identifies F2RL3 DNA methylation as a possible contributory pathway from smoking to cardiovascular disease risk but from any feature potentially influencing F2RL3 regulation in a similar manner.

Systemic Immune Dysregulation Correlates With Clinical Features of Early Non-Small Cell Lung Cancer

Background

Systemic immune dysregulation correlates with cancer progression. However, the clinical implications of systemic immune dysregulation in early non-small cell lung cancer (NSCLC) remain unclear.

Methods

Using a panel of 9 markers to identify 12 parameters in the peripheral blood of 326 patients (34 in the discovery group and 292 in the validation group), we investigated systemic immune dysregulation in early NSCLC. Then, we analyzed the impact of surgery on the systemic immune state of these patients. Finally, we analyzed correlations between systemic immune dysregulation and the clinical features of early NSCLC.

Results

We found striking systemic immune dysregulation in the peripheral blood of early NSCLC patients. This dysregulation was characterized by a significant decrease in total lymphocytes, T cells, quiescent T cells, CD4+ T cells, and NKT cells. We also observed increased proportions of activated lymphocytes and activated T cells. Systemic immune dysregulation was increased after surgery. Furthermore, systemic immune dysregulation was correlated with multiple clinical features, such as sex, age, smoking history, pathological type, tumor stage, surgical approach, tumor differentiation, and epidermal growth factor receptor (EGFR) mutation. Finally, we observed that systemic immune dysregulation was correlated with complications and systemic inflammatory response syndrome (SIRS) in early NSCLC patients.

Conclusions

Our results reveal systemic immune dysregulation occurring in early NSCLC and demonstrate the correlation between these dysregulations and clinical features. Our findings suggest that systemic immune dysregulation is involved in cancer development and may be a promising candidate for high-risk screening and treatment strategies for early NSCLC.

DNA Methylation in Peripheral Blood: Providing Novel Biomarkers of Exposure and Immunity to Examine Cancer Risk

DNA methylation is an epigenetic phenomenon that can alter and control gene expression. Because methylation plays a key role in cell differentiation, methylation markers have been identified that are unique to a given cell type; these markers are stable and can be measured in tissue or whole blood. The article by Katzke and colleagues, published in this issue, uses methylation markers to estimate proportions of immune cell subtypes in peripheral blood samples that were collected prior to diagnosis, thus allowing them to directly examine associations with pancreatic cancer risk. Given that immune-cell counts cannot be measured from archived blood, and that retrospective case-control studies rely on blood that is collected after cancer diagnosis, few studies have been able to examine the role of the systemic immune response in cancer risk. Measurement of DNA methylation in peripheral blood, primarily through development of whole-genome approaches, has also opened new doors to examining cancer etiology.See related article by Katzke et al., p. 2179.

Novel blood-based hypomethylation of SH3BP5 is associated with very early-stage lung adenocarcinoma

BACKGROUND

Early detection is essential to improve the survival of lung cancer (LC). The quantitative measurement of specific DNA methylation changes in the peripheral blood could provide an efficient strategy for the detection of early cancer.

OBJECTIVE

We applied a candidate approach and assess the association between blood-based SH3BP5 methylation and the risk of lung adenocarcinoma (LUAD) in a case-control cohort.

METHODS

The methylation level of four CpG sites in the promoter of SH3BP5 gene was quantitatively determined by mass spectrometry in 171 very early-stage LUAD patients (93.6% LUAD at stage I) and 190 age and gender-matched controls. The logistic regression and non-parametric tests were used for the statistical analyses.

RESULTS

We observed a significant association between decreased methylation of SH3BP5_CpG_4 in the peripheral blood and increased risk of LUAD (odds ratio (OR) per-10% methylation = 1.51, P = 0.006, FDR = 0.024), and even for the LUAD at stage I (OR per-10% methylation = 1.53, P = 0.006, FDR = 0.024). Moreover, the lower quartile of SH3BP5_CpG_4 methylation was correlated with increased risk for LUAD with a P trend of 0.011. Further investigation disclosed that the hypomethylation of SH3BP5_CpG_4 was mostly associated with LUAD in younger subjects (OR per-10% methylation = 2.02, P = 0.010, age < 55 years old) and probably could be enhanced by advance stage.

CONCLUSION

Our study revealed an association between blood-based SH3BP5 hypomethylation and very early-stage LUAD, which provides a novel support for the blood-based methylation signatures as a potential marker for the evaluation of cancer risk.

Assessing the role of genome-wide DNA methylation between smoking and risk of lung cancer using repeated measurements: the HUNT study

BACKGROUND

It is unclear if smoking-related DNA methylation represents a causal pathway between smoking and risk of lung cancer. We sought to identify novel smoking-related DNA methylation sites in blood, with repeated measurements, and to appraise the putative role of DNA methylation in the pathway between smoking and lung cancer development.

METHODS

We derived a nested case-control study from the Trøndelag Health Study (HUNT), including 140 incident patients who developed lung cancer during 2009-13 and 140 controls. We profiled 850 K DNA methylation sites (Illumina Infinium EPIC array) in DNA extracted from blood that was collected in HUNT2 (1995-97) and HUNT3 (2006-08) for the same individuals. Epigenome-wide association studies (EWAS) were performed for a detailed smoking phenotype and for lung cancer. Two-step Mendelian randomization (MR) analyses were performed to assess the potential causal effect of smoking on DNA methylation as well as of DNA methylation (13 sites as putative mediators) on risk of lung cancer.

RESULTS

The EWAS for smoking in HUNT2 identified associations at 76 DNA methylation sites (P < 5 × 10-8), including 16 novel sites. Smoking was associated with DNA hypomethylation in a dose-response relationship among 83% of the 76 sites, which was confirmed by analyses using repeated measurements from blood that was collected at 11 years apart for the same individuals. Two-step MR analyses showed evidence for a causal effect of smoking on DNA methylation but no evidence for a causal link between DNA methylation and the risk of lung cancer.

CONCLUSIONS

DNA methylation modifications in blood did not seem to represent a causal pathway linking smoking and the lung cancer risk.

Genetics of substance use disorders in the era of big data

Substance use disorders (SUDs) are conditions in which the use of legal or illegal substances, such as nicotine, alcohol or opioids, results in clinical and functional impairment. SUDs and, more generally, substance use are genetically complex traits that are enormously costly on an individual and societal basis. The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies - including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples - have revealed multiple risk loci for these common traits. A key emerging insight from this work establishes a biological and genetic distinction between quantity and/or frequency measures of substance use (which may involve low levels of use without dependence), versus symptoms related to physical dependence.

The Association Between PNPLA2 Methylation in Peripheral Blood and Early-Stage Lung Cancer in a Case-Control Study

Purpose

Lung cancer (LC) brings great burden to the society worldwide. Exploring novel biomarkers in vitro for the early detection of LC would be of great importance.

Patients and Methods

We measured DNA methylation levels of 21 CpG sites within Patatin-like phospholipase domain containing 2 (PNPLA2) gene in the peripheral blood of 168 early-stage LC cases (94.0% LC at stage I) and 187 age- and gender-matched cancer-free controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression adjusted for covariates. Non-parametric tests were applied for the comparisons of stratified groups.

Results

Hypomethylation of PNPLA2_CpG_8,10 and hypermethylation of PNPLA2_CpG_9 were correlated to the early-stage LC with the ORs of 1.44 (95% CI: 1.06–1.96, P = 0.018) and 0.82 (95% CI: 0.69–0.98, P = 0.029), respectively. The associations were still significant for the very early-stage LC patients (stage I). Further gender- and age-stratified analyses indicated that the association between hypomethylation of PNPLA2_CpG_8,10 and LC existed only in females and in subjects younger than 55 years. In addition, the association between LC and hypermethylation of PNPLA2_CpG_6 and PNPLA2_CpG_9 was also observed in the younger population.

Conclusion

Taken together, our study has proved the hypothesis that the altered methylation in the peripheral blood may be correlated with the burden of cancer at an early stage. Here, we find a novel association between blood-based aberrant PNPLA2 methylation and LC at a very early stage and particularly for women at a younger age.

Repeatability of methylation measures using a QIAseq targeted methyl panel and comparison with the Illumina HumanMethylation450 assay

OBJECTIVE

In previous studies using Illumina Infinium methylation arrays, we have identified DNA methylation marks associated with cancer predisposition and progression. In the present study, we have sought to find appropriate technology to both technically validate our data and expand our understanding of DNA methylation in these genomic regions. Here, we aimed to assess the repeatability of methylation measures made using QIAseq targeted methyl panel and to compare them with those obtained from the Illumina HumanMethylation450 (HM450K) assay. We included in the analysis high molecular weight DNA extracted from whole blood (WB) and DNA extracted from formalin-fixed paraffin-embedded tissues (FFPE).

RESULTS

The repeatability of QIAseq-methylation measures was assessed at 40 CpGs, using the Intraclass Correlation Coefficient (ICC). The mean ICCs and 95% confidence intervals (CI) were 0.72 (0.62-0.81), 0.59 (0.47-0.71) and 0.80 (0.73-0.88) for WB, FFPE and both sample types combined, respectively. For technical replicates measured using QIAseq and HM450K, the mean ICCs (95% CI) were 0.53 (0.39-0.68), 0.43 (0.31-0.56) and 0.70 (0.59-0.80), respectively. Bland-Altman plots indicated good agreement between QIAseq and HM450K measurements. These results demonstrate that the QIAseq targeted methyl panel produces reliable and reproducible methylation measurements across the 40 CpGs that were examined.

DNA methylation in lung cancer patients: Opening a "window of life" under precision medicine

DNA methylation is a work of adding a methyl group to the 5th carbon atom of cytosine in DNA sequence under the catalysis of DNA methyltransferase (DNMT) to produce 5-methyl cytosine. Some current studies have elucidated the mechanism of lung cancer occurrence and causes of lung cancer progression and metastasis from the perspective of DNA methylation. Moreover, many studies have shown that smoking can change the methylation status of some gene loci, leading to the occurrence of lung cancer, especially central lung cancer. This review mainly introduces the role of DNA methylation in the pathogenesis, early diagnosis and screening, progression and metastasis, treatment, and prognosis of lung cancer, as well as the latest progress. We point out that methylation markers, sample tests, and methylation detection limit the clinical application of DNA methylation. If the liquid biopsy is to become the main force in lung cancer diagnosis, it must make efficient use of limited samples and improve the sensitivity and specificity of the tests. In addition, we also put forward our views on the future development direction of DNA methylation.

Smoking Methylation Marks for Prediction of Urothelial Cancer Risk

BACKGROUND

Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction.

METHODS

Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case-control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC).

RESULTS

The meta-analysis identified associations (P < 4.7 × 10^-5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00-1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91-1.30).

CONCLUSIONS

Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets.

IMPACT

DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.

Disease-related blood-based differential methylation in cystic fibrosis and its representation in lung cancer revealed a regulatory locus in PKP3 in lung epithelial cells

Cystic fibrosis (CF) is a monogenic disease, characterized by massive chronic lung inflammation. The observed variability in clinical phenotypes in monozygotic CF twins is likely associated with the extent of inflammation. This study sought to investigate inflammation-related aberrant DNA methylation in CF twins and to determine to what extent acquired methylation changes may be associated with lung cancer.

Blood-based genome-wide DNA methylation analysis was performed to compare the DNA methylomes of monozygotic twins, from the European CF Twin and Sibling Study with various degrees of disease severity. Putatively inflammation-related and differentially methylated positions were selected from a large lung cancer case-control study and investigated in blood by targeted bisulphite next-generation-sequencing. An inflammation-related locus located in the Plakophilin-3 (PKP3) gene was functionally analysed regarding promoter and enhancer activity in presence and absence of methylation using luciferase reporter assays.

We confirmed in a unique cohort that monozygotic twins, even if clinically discordant, have only minor differences in global DNA methylation patterns and blood cell composition. Further, we determined the most differentially methylated positions, a high proportion of which are blood cell-type-specific, whereas others may be acquired and thus have potential relevance in the context of inflammation as lung cancer risk factors. We identified a sequence in the gene body of PKP3 which is hypermethylated in blood from CF twins with severe phenotype and highly variably methylated in lung cancer patients and controls, independent of known clinical parameters, and showed that this region exhibits methylation-dependent promoter activity in lung epithelial cells.

Epigenome-wide DNA methylation signature of benzo[a]pyrene exposure and their mediation roles in benzo[a]pyrene-associated lung cancer development

Benzo[a]pyrene (B[a]P) is a typical carcinogen associated with increased lung cancer risk, but the underlying mechanisms remain unclear. This study aimed to investigate epigenome-wide DNA methylation associated with B[a]P exposure and their mediation effects on B[a]P-lung cancer association in two lung cancer case-control studies of 462 subjects. Their plasma levels of benzo[a]pyrene diol epoxide-albumin (BPDE-Alb) adducts and genome-wide DNA methylations were separately detected in peripheral blood by using enzyme-linked immunosorbent assay (ELISA) and genome-wide methylation arrays. The epigenome-wide meta-analysis was performed to analyze the associations between BPDE-Alb adducts and DNA methylations. Mediation analysis was applied to assess effect of DNA methylation on the B[a]P-lung cancer association. We identified 15 CpGs associated with BPDE-Alb adducts (P_-meta < 1.0 × 10^-5), among which the methylation levels at five loci (cg06245338, cg24256211, cg15107887, cg02211741, and cg04354393 annotated to UBE2O, SAMD4A, ACBD6, DGKZ, and SLFN13, respectively) mediated a separate 38.5%, 29.2%, 41.5%, 47.7%, 56.5%, and a joint 58.2% of the association between BPDE-Alb adducts and lung cancer risk. Compared to the traditional factors [area under the curve (AUC) = 0.788], addition of these CpGs exerted improved discriminations for lung cancer, with AUC ranging 0.828-0.861. Our results highlight DNA methylation alterations as potential mediators in lung tumorigenesis induced by B[a]P exposure.

Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer

Background

Cancer genomic studies often include data collected from several omics platforms. Each omics data source contributes to the understanding of the underlying biological process via source specific (“individual”) patterns of variability. At the same time, statistical associations and potential interactions among the different data sources can reveal signals from common biological processes that might not be identified by single source analyses. These common patterns of variability are referred to as “shared” or “joint”. In this work, we show how the use of joint and individual components can lead to better predictive models, and to a deeper understanding of the biological process at hand. We identify joint and individual contributions of DNA methylation, miRNA and mRNA expression collected from blood samples in a lung cancer case–control study nested within the Norwegian Women and Cancer (NOWAC) cohort study, and we use such components to build prediction models for case–control and metastatic status. To assess the quality of predictions, we compare models based on simultaneous, integrative analysis of multi-source omics data to a standard non-integrative analysis of each single omics dataset, and to penalized regression models. Additionally, we apply the proposed approach to a breast cancer dataset from The Cancer Genome Atlas.

Results

Our results show how an integrative analysis that preserves both components of variation is more appropriate than standard multi-omics analyses that are not based on such a distinction. Both joint and individual components are shown to contribute to a better quality of model predictions, and facilitate the interpretation of the underlying biological processes in lung cancer development.

Conclusions

In the presence of multiple omics data sources, we recommend the use of data integration techniques that preserve the joint and individual components across the omics sources. We show how the inclusion of such components increases the quality of model predictions of clinical outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04296-0.

Prediagnostic breast milk DNA methylation alterations in women who develop breast cancer

Prior candidate gene studies have shown tumor suppressor DNA methylation in breast milk related with history of breast biopsy, an established risk factor for breast cancer. To further establish the utility of breast milk as a tissue-specific biospecimen for investigations of breast carcinogenesis, we measured genome-wide DNA methylation in breast milk from women with and without a diagnosis of breast cancer in two independent cohorts. DNA methylation was assessed using Illumina HumanMethylation450k in 87 breast milk samples. Through an epigenome-wide association study we explored CpG sites associated with a breast cancer diagnosis in the prospectively collected milk samples from the breast that would develop cancer compared with women without a diagnosis of breast cancer using linear mixed effects models adjusted for history of breast biopsy, age, RefFreeCellMix cell estimates, time of delivery, array chip and subject as random effect. We identified 58 differentially methylated CpG sites associated with a subsequent breast cancer diagnosis (q-value <0.05). Nearly all CpG sites associated with a breast cancer diagnosis were hypomethylated in cases compared with controls and were enriched for CpG islands. In addition, inferred repeat element methylation was lower in breast milk DNA from cases compared to controls, and cases exhibited increased estimated epigenetic mitotic tick rate as well as DNA methylation age compared with controls. Breast milk has utility as a biospecimen for prospective assessment of disease risk, for understanding the underlying molecular basis of breast cancer risk factors and improving primary and secondary prevention of breast cancer.

Methylation marks of prenatal exposure to maternal smoking and risk of cancer in adulthood

BACKGROUND

Prenatal exposure to maternal smoking is detrimental to child health but its association with risk of cancer has seldom been investigated. Maternal smoking induces widespread and long-lasting DNA methylation changes, which we study here for association with risk of cancer in adulthood.

METHODS

Eight prospective case-control studies nested within the Melbourne Collaborative Cohort Study were used to assess associations between maternal-smoking-associated methylation marks in blood and risk of several cancers: breast (n = 406 cases), colorectal (n = 814), gastric (n = 166), kidney (n = 139), lung (n = 327), prostate (n = 847) and urothelial (n = 404) cancer and B-cell lymphoma (n = 426). We used conditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between cancer and five methylation scores calculated as weighted averages for 568, 19, 15, 28 and 17 CpG sites. Models were adjusted for confounders, including personal smoking history (smoking status, pack-years, age at starting and quitting) and methylation scores for personal smoking.

RESULTS

All methylation scores for maternal smoking were strongly positively associated with risk of urothelial cancer. Risk estimates were only slightly attenuated after adjustment for smoking history, other potential confounders and methylation scores for personal smoking. Potential negative associations were observed with risk of lung cancer and B-cell lymphoma. No associations were observed for other cancers.

CONCLUSIONS

We found that methylation marks of prenatal exposure to maternal smoking are associated with increased risk of urothelial cancer. Our study demonstrates the potential for using DNA methylation to investigate the impact of early-life, unmeasured exposures on later-life cancer risk.

Epigenome-wide scan identifies differentially methylated regions for lung cancer using pre-diagnostic peripheral blood

BACKGROUND

DNA methylation markers have been associated with lung cancer risk and may identify aetiologically relevant genomic regions, or alternatively, be markers of disease risk factors or biological processes associated with disease development.

METHODS

In a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 participants (208 cases; 222 controls) in the 1989 CLUE II cohort. We compared DNA methylation levels with case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years-based smoking methylation score. Stratification analyses were conducted over time from blood draw to diagnosis, histology, and smoking status.

RESULTS

We identified 16 single CpG sites and 40 DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA3/HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10-7). We found that CpG sites in the HOXA3/HOXA4 region were hypermethylated in cases compared to controls.

CONCLUSION

The single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing potential biomarkers for lung cancer risk stratification. Future studies will need to examine whether these regions are causally related to lung cancer.

Third-hand smoke exposure is associated with abnormal serum melatonin level via hypomethylation of CYP1A2 promoter: Evidence from human and animal studies

This study aimed to examine whether and how third-hand smoke (THS) exposure would influence serum melatonin level. 1083 participants with or without exposure to THS were enrolled. Serum ROS, SOD, GSH-Px, and melatonin were measured by ELISA. Methylation microarrays detection and WGCNA were performed to identify hub methylated-sites. The methylation levels of hub-sites were validated in addtional samples. Moreover, mice were exposed to THS for 6 months mimicking exposure of human and the serum, liver, and pineal were collected. Oxidative stress-related indicators in serum, pineal, and liver were measured by ELISA. The expressions of mRNA and protein and methylation levels of hub-gene discovered in human data were further explored by RT-PCR, western-blot, and TBS. The results showed the participants exposed to THS had lower melatonin-level. 820 differentially methylated sites associated with THS were identified. And the hub-site located on the CYP1A2 promoter was identified, which mediated the association between THS and decreased melatonin-level. Decreased peak of serum melatonin, increased ROS and reduced SOD and GSH-Px in pineal and liver, and elevated CYP1A2 expression in liver was also found in the THS-exposed mice. Hypo-methylation of 7 CPG sites on the CYP1A2 promoter was identified, which accelerated the catabolism of melatonin. Overall, THS exposure is associated with abnormal melatonin catabolism through hypo-methylation of CYP1A2-promoter.

Transcriptomic signals in blood prior to lung cancer focusing on time to diagnosis and metastasis

Recent studies have indicated that there are functional genomic signals that can be detected in blood years before cancer diagnosis. This study aimed to assess gene expression in prospective blood samples from the Norwegian Women and Cancer cohort focusing on time to lung cancer diagnosis and metastatic cancer using a nested case–control design. We employed several approaches to statistically analyze the data and the methods indicated that the case–control differences were subtle but most distinguishable in metastatic case–control pairs in the period 0–3 years prior to diagnosis. The genes of interest along with estimated blood cell populations could indicate disruption of immunological processes in blood. The genes identified from approaches focusing on alterations with time to diagnosis were distinct from those focusing on the case–control differences. Our results support that explorative analyses of prospective blood samples could indicate circulating signals of disease-related processes.

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Background

We previously investigated the association between 5 "first-generation" measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length.

Methods

We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity.

Results

We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively).

Conclusions

The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

Alcohol consumption is associated with widespread changes in blood DNA methylation: Analysis of cross-sectional and longitudinal data

DNA methylation may be one of the mechanisms by which alcohol consumption is associated with the risk of disease. We conducted a large-scale, cross-sectional, genome-wide DNA methylation association study of alcohol consumption and a longitudinal analysis of repeated measurements taken several years apart. Using the Illumina HumanMethylation450 BeadChip, DNA methylation was measured in blood samples from 5606 Melbourne Collaborative Cohort Study (MCCS) participants. For 1088 of them, these measures were repeated using blood samples collected a median of 11 years later. Associations between alcohol intake and blood DNA methylation were assessed using linear mixed-effects regression models. Independent data from the London Life Sciences Prospective Population (LOLIPOP) (N = 4042) and Cooperative Health Research in the Augsburg Region (KORA) (N = 1662) cohorts were used to replicate associations discovered in the MCCS. Cross-sectional analyses identified 1414 CpGs associated with alcohol intake at P < 10-7 , 1243 of which had not been reported previously. Of these novel associations, 1078 were replicated (P < .05) using LOLIPOP and KORA data. Using the MCCS data, we also replicated 403 of 518 previously reported associations. Interaction analyses suggested that associations were stronger for women, non-smokers, and participants genetically predisposed to consume less alcohol. Of the 1414 CpGs, 530 were differentially methylated (P < .05) in former compared with current drinkers. Longitudinal associations between the change in alcohol intake and the change in methylation were observed for 513 of the 1414 cross-sectional associations. Our study indicates that alcohol intake is associated with widespread changes in DNA methylation across the genome. Longitudinal analyses showed that the methylation status of alcohol-associated CpGs may change with alcohol consumption changes in adulthood.

Peripheral Blood Leukocyte N6-methyladenosine is a Noninvasive Biomarker for Non-small-cell Lung Carcinoma

Background

N6-methyladenosine (m6A) triggers a new layer of epi-transcription. However, the potential noninvasive screening and diagnostic value of peripheral blood m6A for cancer are still unknown. Here, we intend to investigate whether leukocyte m6A can be a novel biomarker for non-small-cell lung cancer (NSCLC).

Materials and Methods

Peripheral blood was collected from 119 NSCLC patients and 74 age-matched healthy controls. Total RNA was isolated from leukocytes for m6A measurement, and clinical information of participants was reviewed. The sensitivity, specificity, and area under the curve (AUC) of m6A for cancer diagnosis were evaluated by the receiver-operating characteristic (ROC) curve analysis. Flow cytometry and the Human Protein Atlas (HPA) database were used to characterize m6A in leukocyte differentials. Pearson's correlation was applied to indicate the relationship between m6A level and hematology variables. qPCR and bioinformatic analysis were used to identity the expression of m6A regulators in leukocyte.

Results

Leukocyte m6A was significantly elevated in 119 NSCLC patients compared with 74 healthy controls (P<0.001). We did not find significant association between m6A and age or gender. Elevated m6A level in NSCLC was associated with tumor stage (P<0.05) and tumor differentiation (P<0.05), and was significantly reduced after surgery (P<0.01). ROC curve analysis revealed that leukocyte m6A could significantly discriminate patients with lung adenocarcinoma (LUAD) (AUC=0.736, P<0.001) and lung squamous cell carcinoma (LUSC) (AUC=0.963, P<0.001) from healthy individuals. m6A displayed superior sensitivity (100%) and specificity (85.7%) for LUSC than squamous cell carcinoma (SCC) antigen and cytokeratin fragment 211 (Cyfra211). Flow cytometry analysis showed m6A modification was mainly localized on T cells and monocytes among leukocyte differentials. Leukocyte m6A was positively correlated with the number of lymphocytes and negatively correlated with monocytes in NSCLC but not in healthy controls. qPCR and bioinformatic analysis showed that elevated leukocyte m6A in NSCLC was caused by upregulated methyltransferase complex and downregulated FTO and ALKBH5.

Conclusion

Leukocyte m6A represents a potential noninvasive biomarker for NSCLC screening, monitoring and diagnosis.

AHRR methylation in heavy smokers: associations with smoking, lung cancer risk, and lung cancer mortality

BACKGROUND

A low level of methylation at cg05575921 in the aryl-hydrocarbon receptor repressor (AHRR) gene is robustly associated with smoking, and some studies have observed associations between cg05575921 methylation and increased lung cancer risk and mortality. To prospectively examine whether decreased methylation at cg05575921 may identify high risk subpopulations for lung cancer screening among heavy smokers, and mortality in cases, we evaluated associations between cg05575921 methylation and lung cancer risk and mortality, by histotype, in heavy smokers.

METHODS

The β-Carotene and Retinol Efficacy Trial (CARET) included enrollees ages 45-69 with ≥ 20 pack-year smoking histories and/or occupational asbestos exposure. A subset of CARET participants had cg05575921 methylation available from HumanMethylationEPIC assays of blood collected on average 4.3 years prior to lung cancer diagnosis in cases. Cg05575921 methylation β-values were treated continuously for a 10% methylation decrease and as quintiles, where quintile 1 (Q1, referent) represents high methylation and Q5, low methylation. We used conditional logistic regression models to examine lung cancer risk overall and by histotype in a nested case-control study including 316 lung cancer cases (diagnosed through 2005) and 316 lung cancer-free controls matched on age (±5 years), sex, race/ethnicity, enrollment year, current/former smoking, asbestos exposure, and follow-up time. Mortality analyses included 372 lung cancer cases diagnosed between 1985 and 2013 with available methylation data. We used Cox proportional hazards models to examine mortality overall and by histotype.

RESULTS

Decreased cg05575921 methylation was strongly associated with smoking, even in our population of heavy smokers. We did not observe associations between decreased pre-diagnosis cg05575921 methylation and increased lung cancer risk, overall or by histotype. We observed linear increasing trends for lung cancer-specific mortality across decreasing cg05575921 methylation quintiles for adenocarcinoma and small cell carcinoma (P-trends = 0.01 and 0.04, respectively).

CONCLUSIONS

In our study of heavy smokers, decreased cg05575921 methylation was strongly associated with smoking but not increased lung cancer risk. The observed association between cg05575921 methylation and increased mortality in adenocarcinoma and small cell histotypes requires further examination. Our results do not support using decreased cg05575921 methylation as a biomarker for lung cancer screening risk stratification.

A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes

Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases.

Smoking-associated DNA methylation changes in whole blood have been reported by many EWAS. Here, the authors use a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven EWAS, identifying lineage-specific smoking-associated DNA methylation changes.

From tobacco smoking to cancer mutational signature: a mediation analysis strategy to explore the role of epigenetic changes

Background

Tobacco smoking is associated with a unique mutational signature in the human cancer genome. It is unclear whether tobacco smoking-altered DNA methylations and gene expressions affect smoking-related mutational signature.

Methods

We systematically analyzed the smoking-related DNA methylation sites reported from five previous casecontrol studies in peripheral blood cells to identify possible target genes. Using the mediation analysis approach, we evaluated whether the association of tobacco smoking with mutational signature is mediated through altered DNA methylation and expression of these target genes in lung adenocarcinoma tumor tissues.

Results

Based on data obtained from 21,108 blood samples, we identified 374 smoking-related DNA methylation sites, annotated to 248 target genes. Using data from DNA methylations, gene expressions and smoking-related mutational signature generated from ~ 7700 tumor tissue samples across 26 cancer types from The Cancer Genome Atlas (TCGA), we found 11 of the 248 target genes whose expressions were associated with smoking-related mutational signature at a Bonferroni-correction P < 0.001. This included four for head and neck cancer, and seven for lung adenocarcinoma. In lung adenocarcinoma, our results showed that smoking increased the expression of three genes, AHRR, GPR15, and HDGF, and decreased the expression of two genes, CAPN8, and RPS6KA1, which were consequently associated with increased smoking-related mutational signature. Additional evidence showed that the elevated expression of AHRR and GPR15 were associated with smoking-altered hypomethylations at cg14817490 and cg19859270, respectively, in lung adenocarcinoma tumor tissues. Lastly, we showed that decreased expression of RPS6KA1, were associated with poor survival of lung cancer patients.

Conclusions

Our findings provide novel insight into the contributions of tobacco smoking to carcinogenesis through the underlying mechanisms of the elevated mutational signature by altered DNA methylations and gene expressions.

A comparative analysis of cell-type adjustment methods for epigenome-wide association studies based on simulated and real data sets

Technological advances and reduced costs of high-density methylation arrays have led to an increasing number of association studies on the possible relationship between human disease and epigenetic variability. DNA samples from peripheral blood or other tissue types are analyzed in epigenome-wide association studies (EWAS) to detect methylation differences related to a particular phenotype. Since information on the cell-type composition of the sample is generally not available and methylation profiles are cell-type specific, statistical methods have been developed for adjustment of cell-type heterogeneity in EWAS. In this study we systematically compared five popular adjustment methods: the factored spectrally transformed linear mixed model (FaST-LMM-EWASher), the sparse principal component analysis algorithm ReFACTor, surrogate variable analysis (SVA), independent SVA (ISVA) and an optimized version of SVA (SmartSVA). We used real data and applied a multilayered simulation framework to assess the type I error rate, the statistical power and the quality of estimated methylation differences according to major study characteristics. While all five adjustment methods improved false-positive rates compared with unadjusted analyses, FaST-LMM-EWASher resulted in the lowest type I error rate at the expense of low statistical power. SVA efficiently corrected for cell-type heterogeneity in EWAS up to 200 cases and 200 controls, but did not control type I error rates in larger studies. Results based on real data sets confirmed simulation findings with the strongest control of type I error rates by FaST-LMM-EWASher and SmartSVA. Overall, ReFACTor, ISVA and SmartSVA showed the best comparable statistical power, quality of estimated methylation differences and runtime.

Stochastic Epigenetic Mutations Are Associated with Risk of Breast Cancer, Lung Cancer, and Mature B-cell Neoplasms

BACKGROUND

Age-related epigenetic dysregulations are associated with several diseases, including cancer. The number of stochastic epigenetic mutations (SEM) has been suggested as a biomarker of life-course accumulation of exposure-related DNA damage; however, the predictive role of SEMs in cancer has seldom been investigated.

METHODS

A SEM, at a given CpG site, was defined as an extreme outlier of DNA methylation value distribution across individuals. We investigated the association of the total number of SEMs with the risk of eight cancers in 4,497 case-control pairs nested in three prospective cohorts. Furthermore, we investigated whether SEMs were randomly distributed across the genome or enriched in functional genomic regions.

RESULTS

In the three-study meta-analysis, the estimated ORs per one-unit increase in log(SEM) from logistic regression models adjusted for age and cancer risk factors were 1.25; 95% confidence interval (CI), 1.11-1.41 for breast cancer, and 1.23; 95% CI, 1.07-1.42 for lung cancer. In the Melbourne Collaborative Cohort Study, the OR for mature B-cell neoplasm was 1.46; 95% CI, 1.25-1.71. Enrichment analyses indicated that SEMs frequently occur in silenced genomic regions and in transcription factor binding sites regulated by EZH2 and SUZ12 (P < 0.0001 and P = 0.0005, respectively): two components of the polycomb repressive complex 2 (PCR2). Finally, we showed that PCR2-specific SEMs are generally more stable over time compared with SEMs occurring in the whole genome.

CONCLUSIONS

The number of SEMs is associated with a higher risk of different cancers in prediagnostic blood samples.

IMPACT

We identified a candidate biomarker for cancer early detection, and we described a carcinogenesis mechanism involving PCR2 complex proteins worthy of further investigations.