Genome-wide DNA Methylation Profiles Research Articles

Novel genome-wide DNA methylation profiling reveals distinct epigenetic landscape, prognostic model and cellular composition of early-stage lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) has been a leading cause of cancer-related mortality worldwide. Early intervention can significantly improve prognosis. DNA methylation could occur in the early stage of tumor. Comprehensive understanding the epigenetic landscape of early-stage LUAD is crucial in understanding tumorigenesis.MethodsEnzymatic methyl sequencing (EM-seq) was performed on 23 tumors and paired normal tissue to reveal distinct epigenetic landscape, for compared with The Cancer Genome Atlas (TCGA) 450K methylation microarray data. Then, an integrative analysis was performed combined with TCGA LUAD RNA-seq data to identify significant differential methylated and expressed genes. Subsequently, the prognostic risk model was constructed and cellular composition was analyzed.ResultsMethylome analysis of EM-seq comparing tumor and normal tissues identified 25 million cytosine-phosphate-guanine (CpG) sites and 30,187 differentially methylated regions (DMR) with a greater number of untraditional types. EM-seq identified a significantly higher number of CpG sites and DMRs compared to the 450K microarray. By integrating the differentially methylated genes (DMGs) with LUAD-related differentially expressed genes (DEGs) from the TCGA database, we constructed prognostic model based on six differentially methylated-expressed genes (MEGs) and verified our prognostic model in GSE13213 and GSE42127 dataset. Finally, cell deconvolution based on the in-house EM-seq methylation profile was used to estimate cellular composition of early-stage LUAD.ConclusionsThis study firstly delves into novel pattern of epigenomic DNA methylation and provides a multidimensional analysis of the role of DNA methylation revealed by EM-seq in early-stage LUAD, providing distinctive insights into its potential epigenetic mechanisms.

Identification of Susceptibility Genes Underlying Bovine Respiratory Disease in Xinjiang Brown Cattle Based on DNA Methylation.

DNA methylation is a form of epigenetic regulation, having pivotal parts in controlling cellular expansion and expression levels within genes. Although blood DNA methylation has been studied in humans and other species, its prominence in cattle is largely unknown. This study aimed to methodically probe the genomic methylation map of Xinjiang brown (XJB) cattle suffering from bovine respiratory disease (BRD), consequently widening cattle blood methylome ranges. Genome-wide DNA methylation profiling of the XJB blood was investigated through whole-genome bisulfite sequencing (WGBS). Many differentially methylated regions (DMRs) obtained by comparing the cases and controls groups were found within the CG, CHG, and CHH (where H is A, T, or C) sequences (16,765, 7502, and 2656, respectively), encompassing 4334 differentially methylated genes (DMGs). Furthermore, GO/KEGG analyses showed that some DMGs were involved within immune response pathways. Combining WGBS-Seq data and existing RNA-Seq data, we identified 71 significantly differentially methylated (DMGs) and expressed (DEGs) genes (p < 0.05). Next, complementary analyses identified nine DMGs (LTA, STAT3, IKBKG, IRAK1, NOD2, TLR2, TNFRSF1A, and IKBKB) that might be involved in the immune response of XJB cattle infected with respiratory diseases. Although further investigations are needed to confirm their exact implication in the involved immune processes, these genes could potentially be used for a marker-assisted selection of animals resistant to BRD. This study also provides new knowledge regarding epigenetic control for the bovine respiratory immune process.

Stimulatory effects of smoke solution and biogas digestate slurry application on photosynthesis, growth, and methylation profiling of solanum tuberosum

ABSTRACT Biostimulants are obtained from various sources like plants, animals, microorganisms, and industrial by-products as well as waste material. Their utilization in agriculture practices is being increased that is giving positive results. The purpose of the current study was to use plant-derived smoke (SMK) solution and biogas digestate (BGD) slurry as biostimulant to elucidate their impact on potato (Solanum tuberosum) performance. The experiment was conducted in lab as well as field conditions, and SMK and BGD solutions were prepared in varying concentrations such as SMK 1:500, SMK 1:250, BGD 50:50, and BGD 75:25. Foliar applications were performed thrice during experiments and data were collected related to photosynthesis, growth, pigments, and genome-wide methylation profiling. Net photosynthesis rate (A) and water use efficiency (WUE) were found higher in SMK- and BGD-treated lab and field grown plants. Among pigments, BGD-treated plants depicted higher levels of Chl a and Chl b while SMK-treated plants showed higher carotenoid levels. Alongside, enhancement in growth-related parameters like leaf number and dry weight was also observed in both lab- and field-treated plants. Furthermore, DNA methylation profile of SMK- and BGD-treated plants depicted variation compared to control. DNA methylation events increased in all the treatments compared to control except for SMK 1:500. These results indicate that smoke and slurry both act as efficient biostimulants which result in better performance of plants. Biostimulants also affected the genome-wide DNA methylation profile that resultantly might have changed the plant gene expression profiling and played its role in plant responsiveness to these biostimulants. However, there is need to elucidate a possible synergistic effect of SMK and BGD on plant growth along with gene expression profiling.

(378) - Genome-Wide DNA Methylation Profiling in Human Dilated Cardiomyopathy

(378) - Genome-Wide DNA Methylation Profiling in Human Dilated Cardiomyopathy

1242 Metabologenomic Characterization Uncovers Heterogeneity Amongst IDH Mutant Gliomas

INTRODUCTION: Mutations in isocitrate dehydrogenase (IDH) enzymes are recognised to drive the molecular footprint of diffuse gliomas through the accumulation of oncometabolite R-2-hydroxyglutarate which drives the widespread restructuring of the DNA methylome; however, beyond R-2-hydroxyglutarate, a comprehensive metabologenomic characterization of IDH-mutant gliomas has yet to be performed. METHODS: Glioma samples from a cohort of 154 patients underwent multiplatform molecular analysis, including metabolomic studies, genome-wide DNA methylation profiling and bulk RNA sequencing. A integrative analysis was performed, including hierarchical clustering and principal component analysis of identified metabolites, differentially methylated probes, copy number alteration and bulk mRNA data. Survival analysis as well as multivariable hazard ratios for clinical variables were calculated by fitting Cox Proportional Hazards Models. RESULTS: We discovered a group of IDH-mutant gliomas whose metabolic profile highly resembled IDH wildtype tumors. Notably, these IDH-mutant gliomas with dysregulated metabolism were distinguished from their IDH-mutant counterparts by significantly shorter overall survival (median OS 118.9 months vs 173.6 months, p=0.048). The IDH-mutant tumors with dysregulated metabolism harbored distinct epigenetic alterations that converged to drive proliferative and stem-like transcriptional profiles. The prognostic relevance of dysregulated metabolism complements, but was not wholly explained by canonically recognized prognostic classifications in IDH-mutant gliomas including 1p/19q codeletion, glioma CpG Island Hypermethylator (GCIMP) status and CDKN2A homozygous deletion. CONCLUSIONS: Utilizing a cross-platform analysis we have uncovered a novel subtyping of IDH-mutant gliomas with dysregulated cellular metabolism with similar survival to IDH-wildtype tumors. The metabolic profile provides unique information on glioma phenotypes, which may facilitate a more comprehensive understanding of glioma biology, and provide a window to target novel dependencies.

Menke-Hennekam syndrome; delineation of domain-specific subtypes with distinct clinical and DNA methylation profiles

CREB-binding protein (CBP, encoded by CREBBP) and its paralog E1A-associated protein (p300, encoded by EP300) are involved in histone acetylation and transcriptional regulation. Variants that produce a null allele or disrupt the catalytic domain of either protein cause Rubinstein-Taybi syndrome (RSTS), while pathogenic missense and in-frame indel variants in parts of exons 30 and 31 cause phenotypes recently described as Menke-Hennekam syndrome (MKHK). To distinguish MKHK subtypes and define their characteristics, molecular and extended clinical data on 82 individuals (54 unpublished) with variants affecting CBP (n=71) or p300 (n=11) (NP_004371.2 residues 1705-1875 and NP_001420.2 residues 1668-1833, respectively) were summarized. Additionally, genome-wide DNA methylation profiles were assessed in DNA extracted from whole peripheral blood from 54 individuals. Most variants clustered closely around the zinc binding residues of two zinc finger domains (ZZ and TAZ2) and within the first α-helix of the fourth intrinsically disordered linker (ID4) of CBP/p300. Domain-specific methylation profiles were discerned for the ZZ domain in CBP/p300 (found in 9/10 tested individuals) and TAZ2 domain in CBP (in 14/20), while a domain-specific diagnostic episignature was refined for the ID4 domain in CBP/p300 (in 21/21). Phenotypes including intellectual disability of varying degree, and distinct physical features were defined for each of the regions. These findings demonstrate existence of at least three MKHK subtypes, which are domain-specific (MKHK-ZZ, MKHK-TAZ2, and MKHK-ID4) rather than gene-specific (CREBBP/EP300). DNA methylation episignatures enable stratification of molecular pathophysiologic entities within a gene or across a family of paralogous genes.

NAB2::STAT6 fusions and genome-wide DNA methylation profiling: Predictors of patient outcomes in meningeal solitary fibrous tumors.

Meningeal solitary fibrous tumors (SFT) are rare and have a high frequency of local recurrence and distant metastasis. In a cohort of 126 patients (57 female, 69 male; mean age at surgery 53.0 years) with pathologically confirmed meningeal SFTs with extended clinical follow-up (median 9.9 years; range 15 days-43 years), we performed extensive molecular characterization including genome-wide DNA methylation profiling (n = 80) and targeted TERT promoter mutation testing (n = 98). Associations were examined with NAB2::STAT6 fusion status (n = 101 cases; 51 = ex5-7::ex16-17, 26 = ex4::ex2-3; 12 = ex2-3::exANY/other and 12 = no fusion) and placed in the context of 2021 Central Nervous System (CNS) WHO grade. NAB2::STAT6 fusion breakpoints (fusion type) were significantly associated with metastasis-free survival (MFS) (p = 0.03) and, on multivariate analysis, disease-specific survival (DSS) when adjusting for CNS WHO grade (p = 0.03). DNA methylation profiling revealed three distinct clusters: Cluster 1 (n = 38), Cluster 2 (n = 22), and Cluster 3 (n = 20). Methylation clusters were significantly associated with fusion type (p < 0.001), with Cluster 2 harboring ex4::ex2-3 fusion in 16 (of 20; 80.0%), nearly all TERT promoter mutations (7 of 8; 87.5%), and predominantly an "SFT" histologic phenotype (15 of 22; 68.2%). Clusters 1 and 3 were less distinct, both dominated by tumors having ex5-7::ex16-17 fusion (respectively, 25 of 33; 75.8%, and 12 of 18; 66.7%) and with variable histological phenotypes. Methylation clusters were significantly associated with MFS (p = 0.027), but not overall survival (OS). In summary, NAB2::STAT6 fusion type was significantly associated with MFS and DSS, suggesting that tumors with an ex5::ex16-17 fusion may have inferior patient outcomes. Methylation clusters were significantly associated with fusion type, TERT promoter mutation status, histologic phenotype, and MFS.

Abstract 7017: Increased epigenetic age acceleration in young adult and early onset colorectal cancer patients post-treatment: A ColoCare Pilot Study

Abstract Introduction: Advanced biological age relative to chronological age has been observed in individuals with colorectal cancer (CRC), and there is growing evidence that cancer treatments can further accelerate biological aging. However, the influence of age at diagnosis on these relationships has yet to be examined in detail. This pilot study used data from the ColoCare Study to explore pre- and post-treatment differences in age acceleration by chronological age at CRC diagnosis. Methods: The ColoCare Study is a prospective cohort study of newly-diagnosed CRC patients enrolled across seven U.S. and European sites. Participants in this pilot study were from the ColoCare site in Tampa, Florida who had available pre-treatment blood DNA. Young adult (YA, aged 18-39) and early onset (EO, aged 40-49) participants were matched with average onset (AO, aged 50-64) and late onset (LO, aged &amp;gt;64) participants on stage, sex, race and microsatellite instability status. Genome-wide DNA methylation profiles were assayed on buffy coat DNA using MethylationEPIC v2 BeadChips. PhenoAgeAccel and GrimAgeAccel were calculated on all samples to quantify the difference between DNA methylation-predicted biological age and chronological age (i.e., age acceleration). Linear regression models were used to estimate the associations of age at diagnosis and treatment with PhenoAgeAccel and GrimAgeAccel, adjusted for sex, race, and site (rectal, colon). Results: The sample (n=60) included n=19 YA, n=15 EO, n=11 AO, and n=15 LO participants with pre-treatment blood DNA. Over half (n=15 YA/EO, n=20 AO/LO) had a paired post-treatment blood sample available. Half of participants were female and had colon tumors, and 76% were diagnosed with stage I-III disease. Pre-treatment, PhenoAgeAccel and GrimAgeAccel were similar across age groups (P &amp;gt; 0.05). In the subset of participants with pre- and post-treatment samples, age acceleration appeared to increase post-treatment (pre- and post-treatment differences, PhenoAgeAccel: 1.44, SD: 5.55, P= 0.13; GrimAgeAccel: 0.92, SD: 2.80, P= 0.06). Increases were largest among YA/EO participants. In adjusted models, the predicted differences in pre-to post-treatment PhenoAgeAccel were 2.89 (95% CI: -0.13, 5.90) in YA/EO and 0.36 (95% CI: -2.25, 2.96) in AO/LO (P-difference= 0.20). The predicted differences in GrimAgeAccel were 1.75 (95% CI: 0.25, 3.25) in YA/EO and 0.30 (95% CI: -1.00, 1.60) in AO/LO (P-difference= 0.15). Conclusions: In this pilot study of CRC patients, pre-treatment age acceleration did not vary by age at diagnosis. Post-treatment, patients diagnosed at age 49 or younger had larger increases in age acceleration than patients diagnosed at age 50 or older. These findings warrant further investigation in larger samples and to determine if increases in post-treatment age acceleration as associated with patient outcomes and treatment response. Citation Format: Erin M. Siegel, Jacob K. Kresovich, Amanda M. Bloomer, Anders Berglund, Esther Jean-Baptiste, Gillian Trujillo, Rachel Carmella, Julaxis Love, Seth Felder, Jennifer Ose, Biljana Gigic, Christopher I. Li, Jane C. Figueiredo, Adetunji T. Toriola, Cornelia M. Ulrich, David Shibata, Laura B. Oswald. Increased epigenetic age acceleration in young adult and early onset colorectal cancer patients post-treatment: A ColoCare Pilot Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7017.

DNA methylation profiling identifies epigenetic signatures of early gastric cancer.

Research on the DNA methylation status of gastric cancer (GC) has primarily focused on identifying invasive GC to develop biomarkers for diagnostic. However, DNA methylation in noninvasive GC remains unclear. We conducted a comprehensive DNA methylation profiling study of differentiated-type intramucosal GCs (IMCs). Illumina 850K microarrays were utilized to assess the DNA methylation profiles of formalin-fixed paraffin-embedded tissues from eight patients who were Epstein-Barr virus-negative and DNA mismatch repair proficient, including IMCs and paired adjacent nontumor mucosa. Gene expression profiling microarray data from the GEO database were analyzed via bioinformatics to identify candidate methylation genes. The final validation was conducted using quantitative real-time PCR, the TCGA methylation database, and single-sample gene set enrichment analysis (GSEA). Genome-wide DNA methylation profiling revealed a global decrease in methylation in IMCs compared with nontumor tissues. Differential methylation analysis between IMCs and nontumor tissues identified 449 differentially methylated probes, with a majority of sites showing hypomethylation in IMCs compared with nontumor tissues (66.1% vs 33.9%). Integrating two RNA-seq microarray datasets, we found one hypomethylation-upregulated gene: eEF1A2, overlapped with our DNA methylation data. The mRNA expression of eEF1A2 was higher in twenty-four IMC tissues than in their paired adjacent nontumor tissues. GSEA indicated that the functions of eEF1A2 were associated with the development of IMCs. Furthermore, TCGA data indicated that eEF1A2 is hypomethylated in advanced GC. Our study illustrates the implications of DNA methylation alterations in IMCs and suggests that aberrant hypomethylation and high mRNA expression of eEF1A2 might play a role in IMCs development.

Genome-Wide DNA Methylation Analysis and Functional Validation of Litter Size Traits in Jining Grey Goats.

DNA methylation (DNAm) is associated with the reproductive system. However, the genetic mechanism through which DNAm regulates gene expression and thus affects litter size in goats is unclear. Therefore, in the present work, genome-wide DNAm profiles of HP and LP Jining Grey goat ovary tissues were comprehensively analyzed via WGBS, and RNA-Seq data were combined to identify candidate genes associated with litter size traits in the Jining Grey goat. Finally, BSP and RT-qPCR were used to verify the sequencing results of the key genes. Notably, the DNMT genes were downregulated at the expression level in the HP group. Both groups exhibited comparable levels of methylation. A total of 976 differentially methylated regions (DMRs) (973 DMRs for CG and 3 DMRs for CHG) and 310 differentially methylated genes (DMGs) were identified in this study. Through integration of WGBS and RNA-Seq data, we identified 59 differentially methylated and differentially expressed genes (DEGs) and ultimately screened 8 key DMGs (9 DMRS) associated with litter size traits in Jining Grey goats (SERPINB2: chr24_62258801_62259000, NDRG4: chr18_27599201_27599400, CFAP43: chr26_27046601_27046800, LRP1B. chr2_79720201_79720400, EPHA6: chr1_40088601_40088800, TTC29: chr17_59385801_59386000, PDE11A: chr2_117418601_117418800 and PGF: chr10_ 16913801_16914000 and chr10_16916401_16916600). In summary, our research comprehensively analyzed the genome-wide DNAm profiles of HP and LP Jining Grey goat ovary tissues. The data findings suggest that DNAm in goat ovaries may play an important role in determining litter size.

Characterisation and reproducibility of the HumanMethylationEPIC v2.0 BeadChip for DNA methylation profiling

BackgroundThe Illumina family of Infinium Methylation BeadChip microarrays has been widely used over the last 15 years for genome-wide DNA methylation profiling, including large-scale and population-based studies, due to their ease of use and cost effectiveness. Succeeding the popular HumanMethylationEPIC BeadChip (EPICv1), the recently released Infinium MethylationEPIC v2.0 BeadChip (EPICv2) claims to extend genomic coverage to more than 935,000 CpG sites. Here, we comprehensively characterise the reproducibility, reliability and annotation of the EPICv2 array, based on bioinformatic analysis of both manifest data and new EPICv2 data from diverse biological samples.ResultsWe find a high degree of reproducibility with EPICv1, evidenced by comparable sensitivity and precision from empirical cross-platform comparison incorporating whole genome bisulphite sequencing (WGBS), and high correlation between technical sample replicates, including between samples with DNA input levels below the manufacturer’s recommendation. We provide a full assessment of probe content, evaluating genomic distribution and changes from previous array versions. We characterise EPICv2’s new feature of replicated probes and provide recommendations as to the superior probes. In silico analysis of probe sequences demonstrates that probe cross-hybridisation remains a significant problem in EPICv2. By mapping the off-target sites at single nucleotide resolution and comparing with WGBS we show empirical evidence for preferential off-target binding.ConclusionsOverall, we find EPICv2 a worthy successor to the previous Infinium methylation microarrays, however some technical issues remain. To support optimal EPICv2 data analysis we provide an expanded version of the EPICv2 manifest to aid researchers in understanding probe design, data processing, choosing appropriate probes for analysis and for integration with methylation datasets from previous versions of the Infinium Methylation BeadChip.

DNA Methylation Analysis Reveals Potential Mechanism in Takifugu rubripes Against Cryptocaryon irritans Infection.

Takifugu rubripes (T. rubripes) is a valuable commercial fish, and Cryptocaryon irritans (C. irritans) has a significant impact on its aquaculture productivity. DNA methylation is one of the earliest discovered ways of gene epigenetic modification and also an important form of modification, as well as an essential type of alteration that regulates gene expression, including immune response. To further explore the anti-infection mechanism of T. rubripes in inhibiting this disease, we determined genome-wide DNA methylation profiles in the gill of T. rubripes using whole-genome bisulfite sequencing (WGBS) and combined with RNA sequence (RNA-seq). A total of 4659 differentially methylated genes (DMGs) in the gene body and 1546 DMGs in the promoter between the infection and control group were identified. And we identified 2501 differentially expressed genes (DEGs), including 1100 upregulated and 1401 downregulated genes. After enrichment analysis, we identified DMGs and DEGs of immune-related pathways including MAPK, Wnt, ErbB, and VEGF signaling pathways, as well as node genes prkcb, myca, tp53, and map2k2a. Based on the RNA-Seq results, we plotted a network graph to demonstrate the relationship between immune pathways and functional related genes, in addition to gene methylation and expression levels. At the same time, we predicted the CpG island and transcription factor of four immune-related key genes prkcb and mapped the gene structure. These unique discoveries could be helpful in the understanding of C. irritans pathogenesis, and the candidate genes screened may serve as optimum methylation-based biomarkers that can be utilized for the correct diagnosis and therapy T. rubripes in the development of the ability to resist C. irritans infection.

Aspirin Challenge-Induced Genome-Wide DNA Methylation Profile of Peripheral Blood Lymphocytes in Aspirin-Exacerbated Respiratory Disease.

Genetic variation and epigenetic factors are thought to contribute to the development of hypersensitivity to aspirin. DNA methylation fluctuates dynamically throughout the day. To discover new CpG methylation in lymphocytes associated with aspirin-exacerbated respiratory disease (AERD), we evaluated changes in global CpG methylation profiles from before to after an oral aspirin challenge in patients with AERD and aspirin-tolerant asthma (ATA). Whole-genome CpG methylation levels of peripheral blood mononuclear cells were quantified with an Illumina 860K Infinium Methylation EPIC BeadChip array and then adjusted for inferred lymphocyte fraction (ILF) with GLINT and Tensor Composition Analysis. Among the 866,091 CpGs in the array, differentially methylated CpGs (DMCs) were found in 6 CpGs in samples from all 12 patients with asthma included in the study (AERD, n = 6; ATA, n = 6). DMCs were found in 3 CpGs in the 6 ATA samples and in 615 CpGs in the 6 AERD samples. A total of 663 DMCs in 415 genes and 214 intergenic regions differed significantly in the AERD compared with the ATA. In promoters, 126 CpG loci were predicted to bind to 38 transcription factors (TFs), many of which were factors already known to be involved in the pathogenesis of asthma and immune responses. In conclusion, we identified 615 new CpGs methylated in peripheral blood lymphocytes by oral aspirin challenge in AERD but not in ATA. These findings indicate that oral aspirin challenge induces epigenetic changes in ILFs, specifically in AERD patients, possibly via changes in TF binding, which may have epigenetic effects on the development of AERD.

Identification of the DNA methylation signature of Mowat-Wilson syndrome.

Mowat-Wilson syndrome (MOWS) is a rare congenital disease caused by haploinsufficiency of ZEB2, encoding a transcription factor required for neurodevelopment. MOWS is characterized by intellectual disability, epilepsy, typical facial phenotype and other anomalies, such as short stature, Hirschsprung disease, brain and heart defects. Despite some recognizable features, MOWS rarity and phenotypic variability may complicate its diagnosis, particularly in the neonatal period. In order to define a novel diagnostic biomarker for MOWS, we determined the genome-wide DNA methylation profile of DNA samples from 29 individuals with confirmed clinical and molecular diagnosis. Through multidimensional scaling and hierarchical clustering analysis, we identified and validated a DNA methylation signature involving 296 differentially methylated probes as part of the broader MOWS DNA methylation profile. The prevalence of hypomethylated CpG sites agrees with the main role of ZEB2 as a transcriptional repressor, while differential methylation within the ZEB2 locus supports the previously proposed autoregulation ability. Correlation studies compared the MOWS cohort with 56 previously described DNA methylation profiles of other neurodevelopmental disorders, further validating the specificity of this biomarker. In conclusion, MOWS DNA methylation signature is highly sensitive and reproducible, providing a useful tool to facilitate diagnosis.

Tissue of origin prediction for cancer of unknown primary using a targeted methylation sequencing panel

RationaleCancer of unknown primary (CUP) is a group of rare malignancies with poor prognosis and unidentifiable tissue-of-origin. Distinct DNA methylation patterns in different tissues and cancer types enable the identification of the tissue of origin in CUP patients, which could help risk assessment and guide site-directed therapy.MethodsUsing genome-wide DNA methylation profile datasets from The Cancer Genome Atlas (TCGA) and machine learning methods, we developed a 200-CpG methylation feature classifier for CUP tissue of origin prediction (MFCUP). MFCUP was further validated with public-available methylation array data of 2977 specimens and targeted methylation sequencing of 78 Formalin‐fixed paraffin‐embedded (FFPE) samples from a single center.ResultsMFCUP achieved an accuracy of 97.2% in a validation cohort (n = 5923) representing 25 cancer types. When applied to an Infinium 450 K array dataset (n = 1052) and an Infinium EPIC (850 K) array dataset (n = 1925), MFCUP achieved an overall accuracy of 93.4% and 84.8%, respectively. Based on MFCUP, we established a targeted bisulfite sequencing panel and validated it with FFPE sections from 78 patients of 20 cancer types. This methylation sequencing panel correctly identified tissue of origin in 88.5% (69/78) of samples. We also found that the methylation levels of specific CpGs can distinguish one cancer type from others, indicating their potential as biomarkers for cancer diagnosis and screening.ConclusionOur methylation-based cancer classifier and targeted methylation sequencing panel can predict tissue of origin in diverse cancer types with high accuracy.

Oxidative stress-induced hypermethylation and low expression of ANXA2R: Novel insights into the dysfunction of melanocytes in vitiligo

BackgroundVitiligo is a skin disorder with melanocyte destruction caused by complex interplay between multiple genetic and environmental factors. Recent studies have suggested DNA methylation is involved in the melanocyte damage, but the underlying mechanism remains unknown. ObjectiveTo explore the abnormal DNA methylation patterns in vitiligo lesional and nonlesional skin, and the mechanism of DNA methylation involved in vitiligo pathogenesis. MethodsInitially, the genome-wide aberrant DNA methylation profiles in lesional and nonlesional skin of vitiligo were detect via Illumina methylation EPIC 850k Beadchip. Subsequently, a comprehensive analysis was conduct to investigate the genomic characteristics of differentially methylated regions (DMRs). Furthermore, the effects of key aberrant methylated genes on cell apoptosis and function of both melanocytes and keratinocytes were further identified and validated by western bloting, ELISA, and immunofluorescence. ResultsCompared with nonlesional skins, we discovered 79 significantly differentially methylated CpG sites in vitiligo lesions. These DMRs were mainly located in the gene body and the TS1500 region. Annexin A2 receptor (ANXA2R), a crucial gene in cell apoptosis, was hypermethylated in vitiligo lesions. Furthermore, we showed that ANXA2R displayed hypermethylation and low expression levels in both keratinocytes and melanocytes of vitiligo patients, and the hypermethylated-triggered downregulation of ANXA2R under oxidative stress induced melanocyte apoptosis, and inhibited the secretion of stem cell factor (SCF) from keratinocytes thus impaired the survival of melanocytes. ConclusionsOur study illustrates the DNA methylation modification in vitiligo, and further demonstrates the molecular mechanism of hypermethylated ANXA2R in the dysfunction of melanocytes under oxidative stress.

Nucleosome profiling at AR binding sites (ARBS) to provide a prognostic tool for metastatic castration-resistant prostate cancer (mCRPC).

42 Background: Prostate cancer is the second leading cause of cancer death for men in the U.S., and metastatic castration-resistant prostate cancer (mCRPC) is the most advanced form. In previous work, we have reported prognostic significance of PTEN-PI3K-AKT pathway and DNA damage response aberrations detected in cell-free DNA (cfDNA) of mCRPC. Here we utilized nucleosome profiling pattern at androgen receptor (AR) binding sites to further investigate AR signaling pathway dysregulation of mCRPC. Methods: Using the next-generation sequencing PredicineScore liquid biopsy assay (low-pass whole genome sequencing, LP-WGS), we profiled cfDNA fragment coverage centered around AR binding sites (ARBS). For 118 mCRPC patient samples, we quantified sample-level ARBS nucleosome profiling abnormality score (ARBS score) by comparing its centric fragment coverage with normal plasma background using standard Z-score. ARBS score was correlated with clinical outcomes including PSA response rate (PSA RR), progression-free survival and overall survival (OS). Results: By comparing ARBS nucleosome profiling and normal plasma background, we found that mCRPC plasma samples had significant ARBS nucleosome depletion, reflective of transcription factor binding and persistent AR signaling. Notably, ARBS nucleosome depletion was prostate cancer specific, and did not occur in other examined cancer types. ARBS score was highly correlated with tumor fraction (R=0.82), indicating that high tumor fraction mCRPC sample had higher AR binding. Importantly, we found that high ARBS score (&gt;2) in pre-treatment samples (n=86) was associated with significantly shorter OS and lower PSA RR compared with low ARBS (≤2) group for patients receiving AR pathway inhibitor (ARPI) or taxane chemotherapy (13.4 vs. 19.4 months, p=7.3×10-3, 45.7% vs. 77.5%, p=5.2×10-3). By integrating genome-wide DNA methylation profiling, we further found that ARBS was hypo-methylated in mCRPC patients, and identified a strong negative correlation between DNA methylation beta value and ARBS score (R=-0.83). Conclusions: ARBS nucleosome profiling abnormality inferred from LP-WGS can serve as a key prognostic tool for mCRPC patients. Patients with high ARBS score had worse clinical outcomes, highlighting the potential clinical utility of cfDNA fragmentomics analysis for mCRPC patient stratification. Integration of mutation, copy number variation and fragmentomics profiling of ARBS may further enhance our understanding of molecular aberrations and treatment outcomes in mCRPC.

Aspirin Challenge–Induced Genome-Wide DNA Methylation Profile of Peripheral Blood Lymphocytes in Aspirin-Exacerbated Respiratory Disease

Aspirin Challenge–Induced Genome-Wide DNA Methylation Profile of Peripheral Blood Lymphocytes in Aspirin-Exacerbated Respiratory Disease

Diagnostic utility and reporting recommendations for clinical DNA methylation episignature testing in genetically undiagnosed rare diseases

PurposeThis study aims to assess the diagnostic utility and provide reporting recommendations for clinical DNA methylation episignature testing based on the cohort of patients tested through the EpiSign Clinical Testing Network. MethodsThe EpiSign assay utilized unsupervised clustering techniques and a support vector machine–based classification algorithm to compare each patient’s genome-wide DNA methylation profile with the EpiSign Knowledge Database, yielding the result that was reported. An international working group, representing distinct EpiSign Clinical Testing Network health jurisdictions, collaborated to establish recommendations for interpretation and reporting of episignature testing. ResultsAmong 2399 cases analyzed, 1667 cases underwent a comprehensive screen of validated episignatures, imprinting, and promoter regions, resulting in 18.7% (312/1667) positive reports. The remaining 732 referrals underwent targeted episignature analysis for assessment of sequence or copy-number variants (CNVs) of uncertain significance or for assessment of clinical diagnoses without confirmed molecular findings, and 32.4% (237/732) were positive. Cases with detailed clinical information were highlighted to describe various utility scenarios for episignature testing. ConclusionClinical DNA methylation testing including episignatures, imprinting, and promoter analysis provided by an integrated network of clinical laboratories enables test standardization and demonstrates significant diagnostic yield and clinical utility beyond DNA sequence analysis in rare diseases.

Methylation profiles at birth linked to early childhood obesity.

Childhood obesity represents a significant global health concern and identifying its risk factors is crucial for developing intervention programs. Many "omics" factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F, and PPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.