Infinium MethylationEPIC Array Research Articles

IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load.

Currently, no molecular biomarker indices are used in standard care to make treatment decisions at diagnosis of chronic lymphocytic leukemia (CLL). We used Infinium MethylationEPIC array data from diagnostic blood samples of 114 CLL patients and developed a procedure to stratify patients based on methylation signatures associated with mutation load of the IGHV gene. This procedure allowed us to predict the time to treatment with a hazard ratio (HR) of 8.34 (95% confidence interval [CI]: 4.54-15.30), as opposed to a HR of 4.35 (95% CI: 2.60-7.28) using IGHV mutation status. Detailed evaluation of 17 cases for which the two classification procedures gave discrepant results showed that these cases were incorrectly classified using IGHV status. Moreover, methylation-based classification stratified patients with different overall survival (HR=1.82; 95% CI: 1.07-3.09), which was not possible using IGHV status. Furthermore, we assessed the performance of the developed classification procedure using published HumanMethylation450 array data for 159 patients for whom information on time to treatment, overall survival and relapse was available. Despite 450K array methylation data not containing all the biomarkers used in our classification procedure, methylation signatures again stratified patients with significantly better accuracy than did IGHV mutation load regarding all available clinical outcomes. Thus, stratification using IGHV-associated methylation signatures may provide better prognostic power than IGHV mutation status.

1135-P: Type 2 Diabetes Modulates DNA Methylation in Human Sperm

Paternal obesity and diabetes are associated with cardiometabolic risk in offspring. To test the hypothesis that paternal metabolism could exert these effects via modulation of the sperm epigenome, we collected motile sperm at two study visits 3 months apart in men with and without T2D (NCT03860558). Sperm DNA methylation was quantified in 32 samples using the Infinium MethylationEPIC array. HbA1c was higher in men with T2D vs. controls (7.6±1.1% vs. 5.2±0.2%, n=9 vs. 7, p<0.0001). Age (49.6±7.5 vs. 40.9±12.3 years, p=0.1), BMI (34.4±6.7 vs. 30.3±4.0 kg/m2, p=0.17), waist circumference and fat % were similar. There were no differences in sperm concentration or motility, testosterone, LH, estradiol, or prolactin levels. Methylation data were pre-processed using Partek Genomics Suite 7.19. After filtering cross-reactive probes and probes overlapping with SNP, 790508 probes were analyzed. Two-way ANOVA (disease group/time as factors) revealed 7 CpG sites differentially methylated between control and T2D (FDR q<0.05, differences in beta>0.2), including sites annotated to SLFN5, MMAA, and LOC101927829. All 7 sites were hypermethylated in T2D, with mean difference in beta of 26.4%. Paired analysis between study visits for individual participants revealed no significant CpG, indicating stability of sperm methylation over time. Genes annotated to differentially methylated CpG at both study visits (n=89, nominal p<0.01) were enriched for genes involved in morphogenesis and neuron development; the majority of these CpG also had higher methylation in T2D. In a linear regression model, 10 CpG sites showed positive and 2 sites showed negative association with HbA1c (FDR q<0.05). In summary, DNA methylation is altered in motile sperm from men with T2D, with hypermethylation at significant CpG sites. These alterations may reflect differential transcriptional regulation at developmentally important loci, and should be investigated as potential contributors to the impact of paternal metabolism on offspring. Disclosure L. Su: None. D. Wolfs: None. M. Hivert: None. J. Patel: None. L. Richardson: None. C. O. Charmant: None. E. M. Isganaitis: None. M. Patti: Consultant; Self; Cello Health, Fractyl Laboratories, Inc., MBX, Poxel SA, WGBH, Other Relationship; Self; Xeris Pharmaceuticals, Inc., Research Support; Self; Dexcom, Inc. Funding National Institutes of Health (R21HD091974)

Distinct Associations of BMI and Fatty Acids With DNA Methylation in Fasting and Postprandial States in Men.

We have previously shown that blood global DNA methylation (DNAm) differs between postprandial state (PS) and fasting state (FS) and is associated with BMI and polyunsaturated fatty acid (PUFA) (negatively and positively, respectively) in 12 metabolically healthy adult Mexican men (AMM cohort) equally distributed among conventional BMI classes. Here, we detailed those associations at CpG dinucleotide level by exploiting the Infinium methylation EPIC array (Illumina). We sought differentially methylated CpG (dmCpG) that were (1) associated with BMI (BMI-dmCpG) and/or fatty acids (FA) (FA-dmCpG) in FS or PS and (2) different across FS and PS within a BMI class. BMI-dmCpG and FA-dmCpG were more numerous in FS compared to PS and largely prandial state-specific. For saturated and monounsaturated FA, dmCpG overlap was higher across than within the respective saturation group. Several BMI- and FA-dmCpG mapped to genes involved in metabolic disease and in some cases matched published experimental data sets. Notably, SETDB1 and MTHFS promoter dmCpG could explain the previously observed associations between global DNAm, PUFA content, and BMI in FS. Surprisingly, overlap between BMI-dmCpG and FA-dmCpG was limited and the respective dmCpG were differentially distributed across functional genomic elements. BMI-dmCpG showed the highest overlap with dmCpG of the saturated FA palmitate, monounsaturated C20:1 and PUFA C20:2. Of these, selected promoter BMI-dmCpG showed opposite associations with palmitate compared to C20:1 and C20:2. As for the comparison between FS and PS within BMI classes, dmCpG were strikingly more abundant and variably methylated in overweight relative to normoweight or obese subjects (∼70–139-fold, respectively). Overweight-associated dmCpG-hosting genes were significantly enriched in targets for E47, SREBP1, and RREB1 transcription factors, which are known players in obesity and lipid homeostasis, but none overlapped with BMI-dmCpG. We show for the first time that the association of BMI and FA with methylation of disease-related genes is distinct in FS and PS and that limited overlap exists between BMI- and FA-dmCpG within and across prandial states. Our study also identifies a transcriptional regulation circuitry in overweight that might contribute to adaptation to that condition or to transition to obesity. Further work is necessary to define the pathophysiological implications of these findings.

Individuals Diagnosed with Binge-Eating Disorder Have DNA Hypomethylated Sites in Genes of the Metabolic System: A Pilot Study.

Binge-eating disorder, recently accepted as a diagnostic category, is differentiated from bulimia nervosa in that the former shows the presence of binge-eating episodes and the absence of compensatory behavior. Epigenetics is a conjunct of mechanisms (like DNA methylation) that regulate gene expression, which are dependent on environmental changes. Analysis of DNA methylation in eating disorders shows that it is reduced. The present study aimed to analyze the genome-wide DNA methylation differences between individuals diagnosed with BED and BN. A total of 46 individuals were analyzed using the Infinium Methylation EPIC array. We found 11 differentially methylated sites between BED- and BN-diagnosed individuals, with genome-wide significance. Most of the associations were found in genes related to metabolic processes (ST3GAL4, PRKAG2, and FRK), which are hypomethylated genes in BED. Cg04781532, located in the body of the PRKAG2 gene (protein kinase AMP-activated non-catalytic subunit gamma 2), was hypomethylated in individuals with BED. Agonists of PRKAG2, which is the subunit of AMPK (AMP-activated protein kinase), are proposed to treat obesity, BED, and BN. The present study contributes important insights into the effect that BED could have on PRKAG2 activation.

Epigenome-wide association study of level and change in cognitive abilities from midlife through late life

BackgroundEpigenetic mechanisms are important in aging and may be involved in late-life changes in cognitive abilities. We conducted an epigenome-wide association study of leukocyte DNA methylation in relation to level and change in cognitive abilities, from midlife through late life in 535 Swedish twins.ResultsMethylation levels were measured with the Infinium Human Methylation 450 K or Infinium MethylationEPIC array, and all sites passing quality control on both arrays were selected for analysis (n = 250,816). Empirical Bayes estimates of individual intercept (age 65), linear, and quadratic change were obtained from latent growth curve models of cognitive traits and used as outcomes in linear regression models. Significant sites (p < 2.4 × 10–7) were followed up in between-within twin pair models adjusting for familial confounding and full-growth modeling. We identified six significant associations between DNA methylation and level of cognitive abilities at age 65: cg18064256 (PPP1R13L) with processing speed and spatial ability; cg04549090 (NRXN3) with spatial ability; cg09988380 (POGZ), cg25651129 (-), and cg08011941 (ENTPD8) with working memory. The genes are involved in neuroinflammation, neuropsychiatric disorders, and ATP metabolism. Within-pair associations were approximately half that of between-pair associations across all sites. In full-growth curve models, associations between DNA methylation and cognitive level at age 65 were of small effect sizes, and associations between DNA methylation and longitudinal change in cognitive abilities of very small effect sizes.ConclusionsLeukocyte DNA methylation was associated with level, but not change in cognitive abilities. The associations were substantially attenuated in within-pair analyses, indicating they are influenced in part by genetic factors.

Genome-Wide DNA Methylation Profiling of Esophageal Squamous Cell Carcinoma from Global High-Incidence Regions Identifies Crucial Genes and Potential Cancer Markers.

Epigenetic mechanisms such as aberrant DNA methylation (DNAme) are known to drive esophageal squamous cell carcinoma (ESCC), yet they remain poorly understood. Here, we studied tumor-specific DNAme in ESCC cases from nine high-incidence countries of Africa, Asia, and South America. Infinium MethylationEPIC array was performed on 108 tumors and 51 normal tissues adjacent to the tumors (NAT) in the discovery phase, and targeted pyrosequencing was performed on 132 tumors and 36 NAT in the replication phase. Top genes for replication were prioritized by weighting methylation results using RNA-sequencing data from The Cancer Genome Atlas and GTEx and validated by qPCR. Methylome analysis comparing tumor and NAT identified 6,796 differentially methylated positions (DMP) and 866 differential methylated regions (DMR), with a 30% methylation (Δβ) difference. The majority of identified DMPs and DMRs were hypermethylated in tumors, particularly in promoters and gene-body regions of genes involved in transcription activation. The top three prioritized genes for replication, PAX9, SIM2, and THSD4, had similar methylation differences in the discovery and replication sets. These genes were exclusively expressed in normal esophageal tissues in GTEx and downregulated in tumors. The specificity and sensitivity of these DNAme events in discriminating tumors from NAT were assessed. Our study identified novel, robust, and crucial tumor-specific DNAme events in ESCC tumors across several high-incidence populations of the world. Methylome changes identified in this study may serve as potential targets for biomarker discovery and warrant further functional characterization. SIGNIFICANCE: This largest genome-wide DNA methylation study on ESCC from high-incidence populations of the world identifies functionally relevant and robust DNAme events that could serve as potential tumor-specific markers. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/10/2612/F1.large.jpg.

DNA methylation and cancer incidence: lymphatic\u2013hematopoietic versus solid cancers in the Strong Heart Study

BackgroundEpigenetic alterations may contribute to early detection of cancer. We evaluated the association of blood DNA methylation with lymphatic–hematopoietic cancers and, for comparison, with solid cancers. We also evaluated the predictive ability of DNA methylation for lymphatic–hematopoietic cancers.MethodsBlood DNA methylation was measured using the Illumina Infinium methylationEPIC array in 2324 Strong Heart Study participants (41.4% men, mean age 56 years). 788,368 CpG sites were available for differential DNA methylation analysis for lymphatic–hematopoietic, solid and overall cancers using elastic-net and Cox regression models. We conducted replication in an independent population: the Framingham Heart Study. We also analyzed differential variability and conducted bioinformatic analyses to assess for potential biological mechanisms.ResultsOver a follow-up of up to 28 years (mean 15), we identified 41 lymphatic–hematopoietic and 394 solid cancer cases. A total of 126 CpGs for lymphatic–hematopoietic cancers, 396 for solid cancers, and 414 for overall cancers were selected as predictors by the elastic-net model. For lymphatic–hematopoietic cancers, the predictive ability (C index) increased from 0.58 to 0.87 when adding these 126 CpGs to the risk factor model in the discovery set. The association was replicated with hazard ratios in the same direction in 28 CpGs in the Framingham Heart Study. When considering the association of variability, rather than mean differences, we found 432 differentially variable regions for lymphatic–hematopoietic cancers.ConclusionsThis study suggests that differential methylation and differential variability in blood DNA methylation are associated with lymphatic–hematopoietic cancer risk. DNA methylation data may contribute to early detection of lymphatic–hematopoietic cancers.

Accelerated epigenetic aging in adolescents living with HIV is associated with altered development of brain structures.

We recently demonstrated that adolescents perinatally infected with HIV-1 (PHIV+) have accelerated aging as measured by a highly accurate epigenetic biomarker of aging known as the epigenetic clock. However, whether epigenetic age acceleration in PHIV+ impacts brain development at the macro- and microstructural levels of brain anatomy has not been studied. We report on a cross-sectional study of PHIV+ enrolled in the Cape Town Adolescent Antiretroviral Cohort (CTAAC). The Illumina Infinium Methylation EPIC array was used to generate DNA methylation data from the blood samples of 180 PHIV+ aged 9 to 12years. The epigenetic clock software and method was used to estimate two measures, epigenetic age acceleration (AgeAccelerationResidual) and extrinsic epigenetic age acceleration (EEAA). Each participant underwent T1 structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). In order to investigate the associations of chronological age, sex, epigenetic age acceleration and treatment variables (CNS penetration effectiveness score (CPE)) of antiretroviral regimen on brain structure in PHIV+, we developed stepwise multiple regression models in R (version 3.4.3, 2017) including grey and white matter volumes, cortical thickness, cortical surface area and DTI measures of white matter microstructural integrity. The mean DNAm age (16.01years) of the participants was higher than their mean chronological age (10.77years). Epigenetic age acceleration contributed more to regional alterations of brain volumes, cortical thickness, cortical surface areas and neuronal microstructure than chronological age, in a range of regions. CPE positively contributed to volume of the brain stem. Understanding the drivers of epigenetic age acceleration could lead to valuable insights into structural brain alterations, and the persistence of neurocognitive disorders in seen in PHIV+ .

Maternal haemoglobin levels in pregnancy and child DNA methylation: a study in the pregnancy and childhood epigenetics consortium

ABSTRACT Altered maternal haemoglobin levels during pregnancy are associated with pre-clinical and clinical conditions affecting the fetus. Evidence from animal models suggests that these associations may be partially explained by differential DNA methylation in the newborn with possible long-term consequences. To test this in humans, we meta-analyzed the epigenome-wide associations of maternal haemoglobin levels during pregnancy with offspring DNA methylation in 3,967 newborn cord blood and 1,534 children and 1,962 adolescent whole-blood samples derived from 10 cohorts. DNA methylation was measured using Illumina Infinium Methylation 450K or MethylationEPIC arrays covering 450,000 and 850,000 methylation sites, respectively. There was no statistical support for the association of maternal haemoglobin levels with offspring DNA methylation either at individual methylation sites or clustered in regions. For most participants, maternal haemoglobin levels were within the normal range in the current study, whereas adverse perinatal outcomes often arise at the extremes. Thus, this study does not rule out the possibility that associations with offspring DNA methylation might be seen in studies with more extreme maternal haemoglobin levels.

Methylomic Landscapes of Ovarian Cancer Precursor Lesions.

The current paradigm in the development of high-grade serous ovarian carcinoma (HGSC) proposes that the majority of HGSCs arise from precursor serous tubal intraepithelial carcinoma (STIC) lesions of the fallopian tube. Here we survey genome-wide methylation in HGSC precursor lesions to identify genomic regions that exhibit high-specificity differential hypermethylation for potential use as biomarkers for detecting STIC and HGSC at stages when curative intervention likely remains feasible. We first identified quality control criteria for performing reliable methylomic analysis of DNA-limited tubal precursor lesions with the Illumina Infinium MethylationEPIC array. We then used this platform to compare genome-wide methylation among 12 STICs with paired adjacent-normal epithelia, one p53 signature lesion and two samples of concurrent HGSC. The resulting methylomic data were analyzed by unsupervised hierarchical clustering and multidimensional analysis. Regions of high-confidence STIC-specific differential hypermethylation were identified using selective bioinformatic criteria and compared with published MethylationEPIC data from 23 HGSC tumors and 11 healthy fallopian tube mucosae. Unsupervised analysis showed that STICs largely clustered with HGSCs, but were clearly distinct from adjacent-normal fallopian tube epithelia. Forty-two genomic regions exhibited high-confidence STIC-specific differential hypermethylation, of which 17 (40.5%) directly overlapped with HGSC-specific differentially methylated regions. Methylation at these shared loci was able to completely distinguish STIC and HGSC samples from normal and adjacent-normal specimens. Our results suggest that most STICs are epigenetically similar to HGSCs and share regions of differential hypermethylation that warrant further evaluation for potential use as biomarkers for early detection of ovarian HGSC.See related commentary by Ishak and De Carvalho, p. 6083.

Comparison of methylation capture sequencing and Infinium MethylationEPIC array in peripheral blood mononuclear cells

BackgroundEpigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium MethylationEPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price.MethodsEpigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000 ng), medium (300–1000 ng), and low (150 ng–300 ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array.ResultsAfter quality control, an average of 3,708,550 CpG sites per sample were detected by MC-seq with DNA quantity > 1000 ng. Reproducibility of DNA methylation in MC-seq-detected CpG sites was high among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98–0.99). However, methylation for a small proportion of CpGs (N = 235) differed significantly between the two platforms, with differences in beta values of greater than 0.5.ConclusionsOur results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.

PATH-33. EPIGENOMIC ANALYSIS OF SPINAL EPENDYMOMA

Abstract BACKGROUND Ependymomas commonly occur in the fourth ventricle and the spinal cord. Gross total resection, age and WHO grade are known prognostic factors. Ependymomas are currently classified into 9 distinct subgroups by DNA methylation profile analysis. Spinal cord ependymoma is distinct from other subgroups. To investigate heterogeneity within spinal cord ependymoma, we examined DNA methylation profiles. MATERIALS AND METHODS We used Infinium MethylationEPIC array (illumina) to obtain DNA methylation data from frozen specimens of spinal ependymoma resected at the University of Tokyo, Osaka City University, and Tokyo Metropolitan Neurological Hospital. Japan Pediatric Molecular Neuro-Oncology Group provided methylation data for 11 reported cases. Cluster analysis was performed using Cluster3.0. RESULTS We analyzed 34 patients, 21 male and 13 female, aged from 18 to 76 years (median 50.5 years), including 2 cases with neurofibromatosis type 2. WHO grade was grade_3 in 2 cases and grade_2 in others. Clustering of the DNA methylation data showed that WHO grade_3 cases tended to be classified into a subgroup distinct from other cases. CONCLUSION This is the largest DNA methylation profiling study on spinal cord ependymoma to date. The study may suggest a new subgroup correlated with higher WHO grade.

PATH-11. PROGNOSTIC SIGNIFICANCE OF EPIGENETIC SUBTYPES AND CpGs ASSOCIATED WITH PROGRESSION TO G-CIMP LOW IN THE EORTC RANDOMIZED PHASE III INTERGROUP CATNON

Abstract BACKGROUND Uncontrolled studies have suggested that methylation-based epigenetic subtypes can be used for prognostication of glioma. We used the prospective randomized CATNON trial to validate the clinical relevance of these epigenetic subtypes. METHODS The phase III CATNON trial randomized 751 adult patients with newly diagnosed 1p/19q non-codeleted anaplastic glioma to 59.4 Gy radiotherapy +/- concurrent and/or adjuvant TMZ. CNV data and methylation data were derived from Infinium MethylationEPIC arrays. Epigenetic subtyping and risk of progression to G-CIMP low were determined from random forest models and 7 specific CpGs (PMID: 29642018). IDH1/2 status was determined with a glioma-tailored NGS panel. Overall survival (OS) was measured from date of randomization. RESULTS Methylation analysis was performed on 654 tumors: 440 were IDH1/2mt, 204 IDH1/2wt and of 10 IDH1/2 status was unknown; 8 IDH1/2mt were 1p/19q codeleted. Based on methylation, tumors were classified as G-CIMP high (n=409), G-CIMP low (n=19), codel-like (n=18), mesenchymal-like (n=107), classic-like (n=48), and PA-like tumors (n=53). Median OS between these epigenetic subtypes varied considerably: codel-like 9.1 yrs, G-CIMP high 9.5 yrs, G-CIMP low 2.8 yrs, mesenchymal-like 1.3 yrs, classic-like 1.6 yrs, and PA-like 2.8 yrs. The difference in OS of the IDH1/2mt astrocytoma subgroup patients was prominent [G-CIMP low vs G-CIMP high: HR 4.12, 95% CI 2.37-7.19, p &amp;lt; 0.001]. Within the IDH1/2mt G-CIMP high astrocytoma patients, 115 tumors were predicted to have risk of progression to G-CIMP low and patients with such tumors indeed had poorer survival [risk vs no-risk: HR 1.59, 95% CI 1.10-2.31, p = 0.02]. Median OS in G-CIMP high tumors with (n=37) and without (n=366) CDKN2A/B HD was 3.3 yrs versus not reached [p&amp;lt; 0.001], in G-CIMP low tumors it was 1.2 yrs (n=6) versus 4.4 yrs (n=12) [p=0.008]. CONCLUSIONS In IDH1/2mt anaplastic astrocytoma, G-CIMP status and CDKN2A/B HD are of independent prognostic value.

An integrative analysis of genome-wide methylation and expression in ameloblastoma: A pilot study.

DNA methylation regulates the expression of various genes involved in tumorigenesis. Ameloblastoma is a benign odontogenic jaw tumor. It is locally aggressive with a high level of recurrence. A delay in treatment can lead to severe facial disfigurement. To the best of our knowledge, this is the first integrated analysis of DNA methylation and gene expression in ameloblastoma with the aim to identify genes that may be regulated by DNA methylation. We used an Infinium MethylationEPIC array to measure genome-wide methylation and the Illumina HiSeq platform to obtain gene expression data in ameloblastoma tissues from five patients and dental follicles from three healthy subjects. An integration analysis was performed using City of Hope CpG Island Analysis Pipeline software. We identified 25,255 differentially methylated CpG sites and 17 differentially methylated CpG islands; six of the islands were negatively correlated with the expression of BAIAP2, DUSP6, FGFR2, FOXF2, NID2, and PAK6. Pyrosequencing and immunostaining techniques were further used to validate FGFR2, NID2, and PAK6. This analysis identifies a group of novel genes that may be regulated by DNA methylation and will possibly lead to new insights into the pathology and invasion mechanism of ameloblastoma.

Arsenic Exposure and Human Blood DNA Methylation and Hydroxymethylation Profiles in Two Diverse Populations from Bangladesh and Spain

Background: Dysregulations in DNA methylation (5mC) associated to arsenic (As) have been reported, however, DNA hydroxymethylation (5hmC) changes associated to high or low-dose As exposures have rarely been studied.Methods: In this study, 30 healthy men aged 43-55 from the Aragon Workers Health Study (AWHS)(Spain) and 31 men aged 31-50 from the Folic Acid and Creatinine Trial (FACT) (Bangladesh) donated blood in 2011-13 and 2009-10, respectively, for DNA 5mC and 5hmC profiling using the InfiniumMethylation EPIC array. Oxidative bisulfite conversion in AWHS and TET-assisted bisulfite conversion in FACT were used to distinguish 5mC from 5hmC. We used established R packages (MLML2R, minfi, sva) for data processing, batch effects and cell heterogeneity corrections. ICPMS was used to measure total blood As in both populations and total urinary As in AWHS. Graphite furnace-AAS was used to measure total urinary As in FACT. Arsenic speciation (inorganic As, MMA, DMA and arsenobetaine) was conducted by HPLC-ICPMS in urine for FACT and AWHS. We ran linear regression models on the logit2-transformed 5mC and 5hmC proportions as outcomes, and log-transformed As variables as predictors, to identify differentially methylated or hydroxymethylated positions (DMPs, DHPs).Results: The median (IQR) of urinary sum of inorganic As (μg/L) was 12.5 (6.8, 22.2) for AWHS and 89.6 (62.0, 161.2) for FACT. At a 0.01 nominal p-value cut-off, there were 20 and 60 common DMPs between the two populations for total urine and blood As, respectively. The corresponding overlap of DHPs was 76 and 36 for urine and blood As, respectively. The top DMP and DHP were found for urinary sum of inorganic arsenic (cg24299306, FDR=0.01) and urinary total As (cg05912299, FDR=0.33), respectively, in AWHS (not statistically significant in FACT).Conclusions: Common epigenetic signatures, both for 5hmC and 5mC, emerged in two populations exposed to very different As doses.

Genome-wide identification of differentially methylated promoters and enhancers associated with response to anti-PD-1 therapy in non-small cell lung cancer

Although approved programmed cell death protein (PD)-1 inhibitors show durable responses, clinical benefits to these agents are only seen in one-third of patients in most cancer types. Therefore, strategies for improving the response to PD-1 inhibitor for treating various cancers including non-small cell lung cancer (NSCLC) are urgently needed. Compared with genome and transcriptome, tumor DNA methylome in anti-PD-1 response was relatively unexplored. We compared the pre-treatment methylation status of cis-regulatory elements between responders and non-responders to treatment with nivolumab or pembrolizumab using the Infinium Methylation EPIC Array, which can profile ~850,000 CpG sites, including ~350,000 CpG sites located in enhancer regions. Then, we analyzed differentially methylated regions overlapping promoters (pDMRs) or enhancers (eDMRs) between responders and non-responders to PD-1 inhibitors. We identified 1007 pDMRs and 607 eDMRs associated with the anti-PD-1 response. We also identified 1109 and 1173 target genes putatively regulated by these pDMRs and eDMRs, respectively. We found that eDMRs contribute to the epigenetic regulation of the anti-PD-1 response more than pDMRs. Hypomethylated pDMRs of Cytohesin 1 Interacting Protein (CYTIP) and TNF superfamily member 8 (TNFSF8) were more predictive than programmed cell death protein ligand 1 (PD-L1) expression for anti-PD-1 response and progression-free survival (PFS) and overall survival (OS) in a validation cohort, suggesting their potential as predictive biomarkers for anti-PD-1 immunotherapy. The catalog of promoters and enhancers differentially methylated between responders and non-responders to PD-1 inhibitors presented herein will guide the development of biomarkers and therapeutic strategies for improving anti-PD-1 immunotherapy in NSCLC.

Neonatal Lead (Pb) Exposure and DNA Methylation Profiles in Dried Bloodspots.

Lead (Pb) exposure remains a major concern in the United States (US) and around the world, even following the removal of Pb from gasoline and other products. Environmental Pb exposures from aging infrastructure and housing stock are of particular concern to pregnant women, children, and other vulnerable populations. Exposures during sensitive periods of development are known to influence epigenetic modifications which are thought to be one mechanism of the Developmental Origins of Health and Disease (DOHaD) paradigm. To gain insights into early life Pb exposure-induced health risks, we leveraged neonatal dried bloodspots in a cohort of children from Michigan, US to examine associations between blood Pb levels and concomitant DNA methylation profiles (n = 96). DNA methylation analysis was conducted via the Infinium MethylationEPIC array and Pb levels were assessed via high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS). While at-birth Pb exposure levels were relatively low (average 0.78 µg/dL, maximum of 5.27 ug/dL), we identified associations between DNA methylation and Pb at 33 CpG sites, with the majority (82%) exhibiting reduced methylation with increasing Pb exposure (q < 0.2). Biological pathways related to development and neurological function were enriched amongst top differentially methylated genes by p-value. In addition to increases/decreases in methylation, we also demonstrate that Pb exposure is related to increased variability in DNA methylation at 16 CpG sites. More work is needed to assess the accuracy and precision of metals assessment using bloodspots, but this study highlights the utility of this unique resource to enhance environmental epigenetics research around the world.

Abstract 5784: Integration of multiple omics underlying extreme phenotype strategy identify non-invasive prognostic biomarkers specific to early-stage lung cancer

Abstract Background Emerging studies have reported that approximately 30% of patients in stage I/II die within 5 years due to the progression and recurrence. There is a great need to identify sensitive and specific non-invasive biomarkers for the prognosis and survival prediction in early-stage lung cancer. Methods The strategy of extreme phenotype was applied for the quick identification of biomarkers associated with early-stage lung cancer survival in Boston Lung Cancer Study (BLCS) cohort. Multiple omics platforms, including SOMAscan and Infinium MethylationEPIC Array, were carried out to recognize biomarkers from the circulating (blood or serum) and solid (tissue) in different molecular levels. Public databases (e.g., TCGA, HPA and GEO) were used to be external validations. Differential analysis was performed by t-test with normalization data. Kaplan-Meier curves with the log-rank test were used to plot and compare the survival between candidate groups. Results Among the lung cancer patients in stage I registered in BLCS, we selected randomly 77 samples for omics detection, of which 37 had long time survival (mean = 157.36 mos) and 40 had short survival (mean = 19.79 mos). At the protein level, we found 120 circulating differentially expressed proteins (C-DEPs) between two extreme groups (P &amp;lt; 0.05), and six of them were beyond the fold change (FC) &amp;gt; 2 [i.e., ApoB (APOB), CK-MB (CKB CKM) and CK-MM (CKM) are up in the long; GAPDH (GAPDH), RAN (RAN) and SPHK1 (SPHK1) are up in the short]. As for their lung cancer tissues, both ApoB (APOB) and CK-MM (CKM) rarely expressed at the RNA and protein levels. Thus, we considered both ApoB and CK-MM as serum-specific proteins and the others as widespread biomarkers. At the DNA methylation level, 19,084 CpGs were identified in circulating differentially methylated positions (C-DMPs) and 80,342 in tumor DMPs (T-DMPs) with P &amp;lt; 0.05. Next, we integrated C-DEPs, C-DMPs and T-DMPs to interpret the origin and expression pattern of specific biomarkers. Intriguingly, several T-DMPs and C-DMPs existed only in genes of serum-specific proteins (ApoB and CK-MM) along with high correlation, but not in the widespread biomarkers. These findings indicate two separate origins where the proteins specific to serum skipped the products of RNA and protein and were directly released from the solid tissue into the circulatory system, while the widespread proteins left RNA and protein behind in situ. Furthermore, among four widespread biomarkers, we observed that the RNA of SPHK1 highly expressed in lung cancer tumors and this higher expression was associated with worse survival (Plog-rank = 1.20 × 10−6), especially in stage I (Plog-rank = 1.20 × 10−5). Similar results were found with the SPHK1 protein in tumors. These findings reveal that the prognostic effect of SPHK1 at both RNA and protein levels was particularly limited to the patients in stage I, but not in advanced stages. Conclusion This is the first study to our knowledge using extreme a phenotype strategy to identify non-invasive prognostic biomarkers for early-stage lung cancer. Utilizing integration of multiple omic platform, it is plausible to recognize and evaluate the circulating biomarkers for prognosis assessment of lung cancer. Citation Format: Mulong Du, Qianyu Yuan, Li Su, Feng Chen, David C. Christiani. Integration of multiple omics underlying extreme phenotype strategy identify non-invasive prognostic biomarkers specific to early-stage lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5784.

Correlative study of epigenetic regulation of tumor microenvironment in spindle cell melanomas and cutaneous malignant peripheral nerve sheath tumors

The tumor microenvironment (TME) plays critical roles in tumor growth and progression, however key regulators of gene expression in the TME of cutaneous malignant peripheral nerve sheath tumor (C-MPNST) and spindle cell melanoma (SCM) have not been well elucidated. Herein, we investigate the epigenetic regulation of promoters and gene bodies and their effect on the TME composition of C-MPNSTs and SCMs. A cohort of 30 patients was analyzed using differential gene expression (DGE) and gene set enrichment analysis (GSEA) using the Nanostring platform. Methylation analysis was carried out utilizing an Infinium Methylation EPIC array targeting 866,562 methylation site (CpG) islands. DGE revealed overexpression of genes related to mast cells in the TME of SCMs, and a predominance of exhausted CD8+ T cells and macrophages in the TME of C-MPNSTs. Interestingly, we further observed promoter hypermethylation in key overexpressed genes and corresponding gene body hypomethylation. Analysis using ENCODE ChIP-sequencing data identified CTCF as the common transcription factor at the site of the hypomethylated probe. These findings support that the TME composition of C-MPNSTs and SCMs is at least partially independent on promoter methylation status, suggesting a possible relationship between gene body enhancers and expression of key TME genes in both entities.

Genome-Wide DNA Methylation Profiles in Community Members Exposed to the World Trade Center Disaster

The primary goal of this pilot study was to assess feasibility of studies among local community members to address the hypothesis that complex exposures to the World Trade Center (WTC) dust and fumes resulted in long-term epigenetic changes. We enrolled 18 WTC-exposed cancer-free women from the WTC Environmental Health Center (WTC EHC) who agreed to donate blood samples during their standard clinical visits. As a reference WTC unexposed group, we randomly selected 24 age-matched cancer-free women from an existing prospective cohort who donated blood samples before 11 September 2001. The global DNA methylation analyses were performed using Illumina Infinium MethylationEpic arrays. Statistical analyses were performed using R Bioconductor package. Functional genomic analyses were done by mapping the top 5000 differentially expressed CpG sites to the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway database. Among cancer-free subjects, we observed substantial methylation differences between WTC-exposed and unexposed women. The top 15 differentially methylated gene probes included BCAS2, OSGIN1, BMI1, EEF1A2, SPTBN5, CHD8, CDCA7L, AIDA, DDN, SNORD45C, ZFAND6, ARHGEF7, UBXN8, USF1, and USP12. Several cancer-related pathways were enriched in the WTC-exposed subjects, including endocytosis, mitogen-activated protein kinase (MAPK), viral carcinogenesis, as well as Ras-associated protein-1 (Rap1) and mammalian target of rapamycin (mTOR) signaling. The study provides preliminary data on substantial differences in DNA methylation between WTC-exposed and unexposed populations that require validation in further studies.