Epigenetic Modules Research Articles

Integrated Analysis of DNA methylation and transcriptome profile to identify key features of age-related macular degeneration

ABSTRACT Age-related macular degeneration (AMD) is a common vision-threatening disease. The current study sought to integrate DNA methylation with transcriptome profile to explore key features in AMD. Gene expression data were obtained from the Gene Expression Omnibus (GEO, accession ID: GSE135092) and DNA methylation data were obtained from the ArrayExpress repository (E-MTAB-7183). A total of 456 differentially expressed genes (DEGs) and 4827 intragenic differentially methylated CpGs (DMCs) were identified between AMD and controls. DEGs and DMCs were intersected and 19 epigenetically induced (EI) genes and 15 epigenetically suppressed (ES) genes were identified. Immune cell infiltration analysis was performed to estimate the abundance of different types of immune cell in each sample. Enrichment scores of inflammatory response and tumor necrosis factor-alpha (TNFα) signaling via nuclear factor kappa B (NF-κb) were positively correlated with abundance of activated memory CD4 T cells and M1 macrophages. Subsequently, two significant random forest classifiers were constructed based on DNA methylation and transcriptome data. SMAD2 and NGFR were selected as key genes through functional epigenetic modules (FEM) analysis. Expression level of SMAD2, NGFR and their integrating proteins was validated in hydrogen peroxide (H2O2) and TNFα co-treated retinal pigment epithelium (RPE) in vitro. The findings of the current study showed that local inflammation and systemic inflammatory host response play key roles in pathogenesis of AMD. SMAD2 and NGFR provide new insight in understanding the molecular mechanism and are potential therapeutic targets for development of AMD therapy.

Integration of gene expression and DNA methylation identifies epigenetically controlled modules related to PM2.5 exposure

Air pollution has been associated with adverse health effects across the life-course. Although underlying mechanisms are unclear, several studies suggested pollutant-induced changes in transcriptomic profiles. In this meta-analysis of transcriptome-wide association studies of 656 children and adolescents from three European cohorts participating in the MeDALL Consortium, we found two differentially expressed transcript clusters (FDR p < 0.05) associated with exposure to particulate matter < 2.5 µm in diameter (PM2.5) at birth, one of them mapping to the MIR1296 gene. Further, by integrating gene expression with DNA methylation using Functional Epigenetic Modules algorithms, we identified 9 and 6 modules in relation to PM2.5 exposure at birth and at current address, respectively (including NR1I2, MAPK6, TAF8 and SCARA3). In conclusion, PM2.5 exposure at birth was linked to differential gene expression in children and adolescents. Importantly, we identified several significant interactome hotspots of gene modules of relevance for complex diseases in relation to PM2.5 exposure.

Genome-wide DNA methylation analysis of Hashimoto's thyroiditis during pregnancy.

Hashimoto's thyroiditis (HT) during pregnancy is usually accompanied by an elevation of thyroid-stimulating hormone and a reduction of serum-free thyroxine during gestation, which may lead to abortion, preterm delivery, and reduced intellectual function of the offspring. Epigenetic alterations may provide important insights into genetic-environmental interactions in HT. Here, we examined global DNA methylation patterns in patients with HT during pregnancy. DNA was extracted from 13 women with HT during pregnancy (HTDP) and eight healthy pregnant women as a control group. Genome-wide methylation was detected with the use of an Illumina Human Methylation 850K Beadchip. A total of 652 differentially methylated positions (DMPs) and 27 differentially methylated regions (DMRs) were identified between the HTDP and control groups. GO analysis revealed that DMPs were significantly enriched in 540 GO terms, which included regulation of the differentiation of keratinocytes, T helper cell differentiation, and alpha-beta T-cell differentiation. Moreover, significant enrichment of KEGG pathways of the DMPs included mucin-type O-glycan biosynthesis, focal adhesion, and the insulin signaling pathway. The GO items associated with DMRs included muscle cell proliferation, response to biotic stimulus, anatomical structure formation involved in morphogenesis, and genes primarily involved in the FoxO signaling pathway. Finally, the DTNA gene was identified as the seed gene of functional epigenetic modules. In summary, the DNA methylation pattern of the HTDP group was distinct from that of the control group, and thus, changes in DNA methylation may influence the development of HT by regulation of the autoimmunity process.

Study of miRNA interactome in active rheumatoid arthritis patients reveals key pathogenic roles of dysbiosis in the infection-immune network.

ObjectivesTo characterize serum microRNA (miR) and the miR interactome of active RA patients in RA aetiology and pathogenesis.MethodsThe differentially expressed miRs (DEmiRs) in serum of naïve active RA patients (NARAPs, n = 9, into three pools) vs healthy controls (HCs, n = 15, into five pools) were identified with Agilent human miR microarray analysis. Candidate driver genes in epigenetic and pathogenic signalling pathway modules for RA were analysed using miRTarBase and a molecular complex detection algorithm. The interactome of these DEmiRs in RA pathogenesis were further characterized with gene ontology and Kyoto Encyclopaedia of Genes and Genomes.ResultsThree upregulated DEmiRs (hsa-miR-187-5p, -4532, -4516) and eight downregulated DEmiRs (hsa-miR-125a-3p, -575, -191-3p, -6865-3p, -197-3p, -6886-3p, -1237-3p, -4436b-5p) were identified in NARAPs. Interactomic analysis from heterogeneous experimentally validated sources yielded 1719 miR–target interactions containing 5.67% strong and 94.33% less strong experimental evidence. Gene ontology and Kyoto Encyclopaedia of Genes and Genomes analyses allocated the upregulated DEmiRs in the infection modules and the downregulated DEmiRs in the immune signalling pathways. Specifically, these DEmiRs revealed the significant contributions of the intestinal microbiome dysbiosis in the infection–inflammation–immune network for activation of T cells, immune pathways of IL-17, Toll-like receptor, TNF, Janus kinase-signal transducer and activator of transcription, osteoclast cell differentiation pathway and IgA production to the active RA pathogenesis.ConclusionsOur experiment-based interactomic study of DEmiRs in serum of NARAPs revealed novel clinically relevant miRs interactomes in the infection–inflammation–immune network of RA. These results provide valuable resources for understanding the integrated function of the miR network in RA pathogenesis and the application of circulating miRs as biomarkers for early aetiologic RA diagnosis.

Alteration of DNA methylation induced by PM2.5 in human bronchial epithelial cells.

This current study explored the effects of fine particulate matter (PM2.5) on deoxyribonucleic acid methylation in human bronchial epithelial cells. Human bronchial epithelial cells were exposed to PM2.5 for 24h after which, deoxyribonucleic acid samples were extracted, and the differences between methylation sites were detected using methylation chips. Subsequent gene ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the differential methylation sites. Functional epigenetic modules analysis of the overall differential methylation site interactions was also conducted. A total of 127 differential methylation sites in 89 genes were screened in the PM2.5 10μg/ml group, of which 55 sites demonstrated increased methylation, with methylation levels decreasing in a further 72 sites. Following an exposure of 50μg/ml PM2.5, a total of 238 differentially methylated sites were screened in 168 genes, of which methylation levels increased in 127 sites, and decreased in 111. KEGG analysis showed that the top 10 enrichment pathways predominantly involve hepatocellular carcinoma pathways and endometrial cancer pathways, whereas functional epigenetic modules analysis screened eight genes (A2M, IL23A, TPIP6, IL27, MYD88, ILE2B, NLRC4, TNF) with the most interactions. Our results indicate that exposure to PM2.5 for 24h in human bronchial epithelial cells induces marked changes in deoxyribonucleic acid methylation of multiple genes involved in apoptosis and carcinogenesis pathways, these findings can provide a new direction for further study of PM2.5 carcinogenic biomarkers.

Epigenetic Regulation Mediated by Methylation in the Pathogenesis and Precision Medicine of Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a complex disease triggered by the interaction between genetics and the environment, especially through the shared epitope (SE) and cell surface calreticulin (CSC) theory. However, the available evidence shows that genetic diversity and environmental exposure cannot explain all the clinical characteristics and heterogeneity of RA. In contrast, recent studies demonstrate that epigenetics play important roles in the pathogenesis of RA, especially DNA methylation and histone modification. DNA methylation and histone methylation are involved in innate and adaptive immune cell differentiation and migration, proliferation, apoptosis, and mesenchymal characteristics of fibroblast-like synoviocytes (FLS). Epigenetic-mediated regulation of immune-related genes and inflammation pathways explains the dynamic expression network of RA. In this review, we summarize the comprehensive evidence to show that methylation of DNA and histones is significantly involved in the pathogenesis of RA and could be applied as a promising biomarker in the disease progression and drug-response prediction. We also explain the advantages and challenges of the current epigenetics research in RA. In summary, epigenetic modules provide a possible interface through which genetic and environmental risk factors connect to contribute to the susceptibility and pathogenesis of RA. Additionally, epigenetic regulators provide promising drug targets to develop novel therapeutic drugs for RA. Finally, DNA methylation and histone modifications could be important features for providing a better RA subtype identification to accelerate personalized treatment and precision medicine.

Zika Virus Changes Methylation of Genes Involved in Immune Response and Neural Development in Brazilian Babies Born With Congenital Microcephaly.

The recent increase in babies born with brain and eye malformations in Brazil is associated with Zika virus (ZIKV) infection in utero. ZIKV alters host DNA methylation in vitro. Using genome-wide DNA methylation profiling we compared 18 babies born with congenital ZIKV microcephaly with 20 controls. We found ZIKV-associated alteration of host methylation patterns, notably at RABGAP1L which is important in brain development, at viral host immunity genes MX1 and ISG15, and in an epigenetic module containing the causal microcephaly gene MCPH1. Our data support the hypothesis that clinical signs of congenital ZIKV are associated with changes in DNA methylation.

Co-occurrence and Mutual Exclusivity Analysis of DNA Methylation Reveals Distinct Subtypes in Multiple Cancers.

Co-occurrence and mutual exclusivity (COME) of DNA methylation refer to two or more genes that tend to be positively or negatively correlated in DNA methylation among different samples. Although COME of gene mutations in pan-cancer have been well explored, little is known about the COME of DNA methylation in pan-cancer. Here, we systematically explored the COME of DNA methylation profile in diverse human cancer. A total of 5,128,332 COME events were identified in 14 main cancers types in The Cancer Genome Atlas (TCGA). We also identified functional epigenetic modules of the zinc finger gene family in six cancer types by integrating the gene expression and DNA methylation data and the frequently occurred COME network. Interestingly, most of the genes in those functional epigenetic modules are epigenetically repressed. Strikingly, those frequently occurred COME events could be used to classify the patients into several subtypes with significant different clinical outcomes in six cancers as well as pan-cancer (p-value ≤ = 0.05). Moreover, we observed significant associations between different COME subtypes and clinical features (e.g., age, gender, histological type, neoplasm histologic grade, and pathologic stage) in distinct cancers. Taken together, we identified millions of COME events of DNA methylation in pan-cancer and detected functional epigenetic COME events that could separate tumor patients into different subtypes, which may benefit the diagnosis and prognosis of pan-cancer.

Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” data

The brain is a highly complex organ consisting of numerous types of cells with ample diversity at the epigenetic level to achieve distinct gene expression profiles. During neuronal cell specification, transcription factors (TFs) form regulatory modules with chromatin remodeling proteins to initiate the cascade of epigenetic changes. Currently, little is known about brain epigenetic regulatory modules and how they regulate gene expression in a cell-type specific manner. To infer TFs involved in neuronal specification, we applied a recursive motif search approach on the differentially methylated regions identified from single-cell methylomes. The epigenetic transcription regulatory modules (ETRM), including EGR1 and MEF2C, were predicted and the co-expression of TFs in ETRMs were examined with RNA-seq data from single or sorted brain cells using a conditional probability matrix. Lastly, computational predications were validated with EGR1 ChIP-seq data. In addition, methylome and RNA-seq data generated from Egr1 knockout mice supported the essential role of EGR1 in brain epigenome programming, in particular for excitatory neurons. In summary, we demonstrated that brain single cell methylome and RNA-seq data can be integrated to gain a better understanding of how ETRMs control cell specification. The analytical pipeline implemented in this study is freely accessible in the Github repository (https://github.com/Gavin-Yinld/brain_TF).

Comprehensive analysis of gene expression and DNA methylation data identifies potential biomarkers and functional epigenetic modules for lung adenocarcinoma.

Lung cancer has one of the highest mortality rates of malignant neoplasms. Lung adenocarcinoma (LUAD) is one of the most common types of lung cancer. DNA methylation is more stable than gene expression and could be used as a biomarker for early tumor diagnosis. This study is aimed to screen potential DNA methylation signatures to facilitate the diagnosis and prognosis of LUAD and integrate gene expression and DNA methylation data of LUAD to identify functional epigenetic modules. We systematically integrated gene expression and DNA methylation data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), bioinformatic models and algorithms were implemented to identify signatures and functional modules for LUAD. Three promising diagnostic and five potential prognostic signatures for LUAD were screened by rigorous filtration, and our tumor-normal classifier and prognostic model were validated in two separate data sets. Additionally, we identified functional epigenetic modules in the TCGA LUAD dataset and GEO independent validation data set. Interestingly, the MUC1 module was identified in both datasets. The potential biomarkers for the diagnosis and prognosis of LUAD are expected to be further verified in clinical practice to aid in the diagnosis and treatment of LUAD.

EPIGENETIC PROFILES OF BIOLOGICAL AGING HALLMARKS

Investigation into the hallmarks of aging point to the existence of shared mechanisms that underlie the biological aging process. While there is a general consensus that hallmarks of aging rarely occur in isolation, little is known in regards to their overlapping networks or how interactions contribute to manifestations at the clinical level. Here, we examine whether shared epigenetic alterations—one of the proposed hallmark of aging—underlies diverse conditions characterized by other hallmarks, including cellular senescence, loss of proteostasis, genomic instability, mitochondrial dysfunction, and inflammation. Using weighted network analysis, we identified consistent overlaps in the methylation profiles across the different traits. For instance, epigenetic modules that were distinct in senescence were also affected in progeroid syndromes (Hutchinson-Gilford Progeria Syndrome and Werner’s Syndrome) and smokers. These CpGs tended to be located in CpG islands, which are notable for their strong association with transcriptional regulation. Overall, our results suggest that epigenetic alterations intersect with various hallmarks of aging. In moving forward, incorporation of this understanding may lead to the development of biomarkers that better capture the biological (rather than chronological) aging process.

DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure

BackgroundEpigenome-wide association studies using DNA methylation have the potential to uncover novel biomarkers and mechanisms of cardiovascular disease (CVD) risk. However, the direction of causation for these associations is not always clear, and investigations to-date have often failed to replicate at the level of individual loci.MethodsHere, we undertook module- and region-based DNA methylation analyses of incident CVD in the Women’s Health Initiative (WHI) and Framingham Heart Study Offspring Cohort (FHS) in order to find more robust epigenetic biomarkers for cardiovascular risk. We applied weighted gene correlation network analysis (WGCNA) and the Comb-p algorithm to find methylation modules and regions associated with incident CVD in the WHI dataset.ResultsWe discovered two modules whose activation correlated with CVD risk and replicated across cohorts. One of these modules was enriched for development-related processes and overlaps strongly with epigenetic aging sites. For the other, we showed preliminary evidence for monocyte-specific effects and statistical links to cumulative exposure to traditional cardiovascular risk factors. Additionally, we found three regions (associated with the genes SLC9A1, SLC1A5, and TNRC6C) whose methylation associates with CVD risk.ConclusionsIn sum, we present several epigenetic associations with incident CVD which reveal disease mechanisms related to development and monocyte biology. Furthermore, we show that epigenetic modules may act as a molecular readout of cumulative cardiovascular risk factor exposure, with implications for the improvement of clinical risk prediction.

DNMIVD: DNA methylation interactive visualization database.

Aberrant DNA methylation plays an important role in cancer progression. However, no resource has been available that comprehensively provides DNA methylation-based diagnostic and prognostic models, expression–methylation quantitative trait loci (emQTL), pathway activity-methylation quantitative trait loci (pathway-meQTL), differentially variable and differentially methylated CpGs, and survival analysis, as well as functional epigenetic modules for different cancers. These provide valuable information for researchers to explore DNA methylation profiles from different aspects in cancer. To this end, we constructed a user-friendly database named DNA Methylation Interactive Visualization Database (DNMIVD), which comprehensively provides the following important resources: (i) diagnostic and prognostic models based on DNA methylation for multiple cancer types of The Cancer Genome Atlas (TCGA); (ii) meQTL, emQTL and pathway-meQTL for diverse cancers; (iii) Functional Epigenetic Modules (FEM) constructed from Protein-Protein Interactions (PPI) and Co-Occurrence and Mutual Exclusive (COME) network by integrating DNA methylation and gene expression data of TCGA cancers; (iv) differentially variable and differentially methylated CpGs and differentially methylated genes as well as related enhancer information; (v) correlations between methylation of gene promoter and corresponding gene expression and (vi) patient survival-associated CpGs and genes with different endpoints. DNMIVD is freely available at http://www.unimd.org/dnmivd/. We believe that DNMIVD can facilitate research of diverse cancers.

Evaluation of the Common Molecular Basis in Alzheimer's and Parkinson's Diseases.

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (HLA-DRB5) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD.

Identification of Methylation Markers and Differentially Expressed Genes with Prognostic Value in Breast Cancer.

Breast cancer is one of the most common cancers causing a high mortality worldwide. This study aimed to identify differential methylation and expression genes with prognostic value in breast cancer. DNA methylation and gene expression profiles (GSE60185, GSE42568, GSE21653, GSE58812, and GSE52865) were downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) databases. The differentially expressed genes (DEGs) and differential methylation genes were identified between breast cancer samples and normal samples. Functional analysis was performed using DAVID (Database for Annotation, Visualization, and Integrated Discovery) tool. Furthermore, functional epigenetic modules (FEM) were analyzed to identify critical genes with prognostic values. A large amount of DEGs and aberrant methylation genes were identified between breast cancer samples and normal samples. These genes were mainly associated with several GO (Gene Ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, such as neuroactive ligand-receptor interaction, alcoholism, gamma-aminobutyric acid signaling pathway, and G-protein-coupled receptor signaling pathway. Additionally, 10 DEGs with differential methylation levels were significantly correlated with survival outcomes in breast cancer patients. FEM analysis revealed that several DEGs (e.g., GABRA4, GABRG1, and GABRA1) in module GABRA4 were identified as potential biomarkers in breast cancer patients. Several DEGs identified were associated with breast cancer prognosis. These DEGs might act as prognostic and diagnostic markers in breast cancer.

Epigenetic Co-Deregulation of EZH2/TET1 is a Senescence-Countering, Actionable Vulnerability in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) cells lack the expression of ER, PR and HER2. Thus, TNBC patients cannot benefit from hormone receptor-targeted therapy as non-TNBC patients, but can only receive chemotherapy as the systemic treatment and have a worse overall outcome. More effective therapeutic targets and combination therapy strategies are urgently needed to improve the treatment effectiveness.Methods: We analyzed the expression levels of EZH2 and TET1 in TCGA and our own breast cancer patient cohort, and tested their correlation with patient survival. We used TNBC and non-TNBC cell lines and mouse xenograft tumor model to unveil novel EZH2 targets and investigated the effect of EZH2 inhibition or TET1 overexpression in cell proliferation and viability of TNBC cells.Results: In TNBC cells, EZH2 decreases TET1 expression by H3K27me3 epigenetic regulation and subsequently suppresses anti-tumor p53 signaling pathway. Patients with high EZH2 and low TET1 presented the poorest survival outcome. Experimentally, targeting EZH2 in TNBC cells with specific inhibitor GSK343 or shRNA genetic approach could induce cell cycle arrest and senescence by elevating TET1 expression and p53 pathway activation. Using mouse xenograft model, we have tested a novel therapy strategy to combine GSK343 and chemotherapy drug Adriamycin and could show drastic and robust inhibition of TNBC tumor growth by synergistic induction of senescence and apoptosis.Conclusions: We postulate that the well-controlled dynamic pathway EZH2-H3K27me3-TET1 is a novel epigenetic co-regulator module and provide evidence regarding how to exploit it as a novel therapeutic target via its pivotal role in senescence and apoptosis control. Of clinical and therapeutic significance, the present study opens a new avenue for TNBC treatment by targeting the EZH2-H3K27me3-TET1 pathway that can modulate the epigenetic landscape.

Recursive Motif Analyses Identify Brain Epigenetic Transcription Regulatory Modules

DNA methylation is an epigenetic modification modulating the structure of DNA molecule and the interactions with its binding proteins. Accumulating large-scale methylation data motivates the development of analytic tools to facilitate methylome data mining. One critical phenomenon associated with dynamic DNA methylation is the altered DNA binding affinity of transcription factors, which plays key roles in gene expression regulation. In this study, we conceived an algorithm to predict epigenetic regulatory modules through recursive motif analyses on differentially methylated loci. A two-step procedure was implemented to first group differentially methylated loci into clusters according to their correlations in methylation profiles and then to repeatedly identify the transcription factor binding motifs significantly enriched in each cluster. We applied this tool on methylome datasets generated for mouse brains which have a lack of DNA demethylation enzymes TET1 or TET2. Compared with wild type control, the differentially methylated CpG sites identified in TET1 knockout mouse brains differed significantly from those determined for TET2 knockout. Transcription factors with zinc finger DNA binding domains including Egr1, Zic3, and Zeb1 were predicted to be associated with TET1 mediated brain methylome programming, while Lhx family members with Homeobox domains were predicted to be associated with TET2 function. Interestingly, genomic loci from a co-methylated cluster often host motifs for transcription factors sharing the same DNA binding domains. Altogether, our study provided a systematic approach for epigenetic regulatory module identification and will help throw light on the interplay of DNA methylation and transcription factors.

A DNA-Methylated Sight on Autoimmune Inflammation Network across RA, pSS, and SLE.

Methylation variabilities of inflammatory cytokines play important roles in the development of systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and primary Sjögren's syndrome (pSS). With heightened focus on personalized and precise medicine, it is necessary to compare and contrast the difference and similarity of cytokine methylation status between the 3 most classic autoimmune diseases (AIDs). In this study, we integrated 5 Cytokine-Chips from genome-wide DNA methylation datasets of the 3 kind of AIDs, delta-beta value was calculated for intergroup difference, and comprehensive bioinformatics analyses of cytokine genes with aberrant methylations were performed. 125 shared differential methylation variabilities (DMVs) were identified. There were 102 shared DMVs with similar methylation status; 3 hypomethylated differential methylation regions (DMRs) across the AIDs were found, and all 3 DMRs were hypomethylated. DMRs (AZU1, LTBR, and RTEL1) were likely to serve as activator in the inflammatory process. Particularly, AZU1 and LTBR with hypomethylated TSS and first exon located in the promoter regions were able to trigger inflammation signaling cascades and play critical roles in autoimmune tautology. Moreover, functional epigenetic module (FEM) algorithm showed that different inflammatory networks are involved in different AIDs; 5 hotspots were identified as biologically plausible pathways in inducing or perpetuating of inflammation which are epigenetically deregulated in AIDs. We concluded methylation variabilities among the same cytokines can greatly impact the perpetuation of inflammatory process or signal pathway of AIDs. Differentiating the cytokine methylation status will serve as valuable resource for researchers alike to gain better understanding of the epigenetic mechanisms of the three AIDs. Even more importantly, better understanding of cytokine methylation variability existing between the three classic AIDs will aid in identification of potential epigenetic biomarkers and therapeutic targets. This trial is registered with ChiCTR-INR-16010290, a clinical trial for the treatment of rheumatoid arthritis with Warming yang and Smoothening Meridians.

Abstract 3431: Evaluation of genetic mutations and copy number alterations in biliary tract cancer using targeted exome sequencing

Abstract Background: Biliary tract cancer (BTC) is a heterogeneous group of cancers anatomically divided into the gallbladder cancer (GBC), intrahepatic cholangiocarcinoma (ICC) and extrahepatic cholangiocarcinoma (ECC). None of molecular target agents has been proven to improve the prognosis of BTC yet. To gain a deeper understanding of BTC's pathophysiology and find its new potential therapeutic targets, this study is aimed to investigate genetic profiles of BTC and their clinical implications. Methods: A total of 69 patients who had been pathologically diagnosed as adenocarcinoma of biliary tract from January 2014 to November 2016 and had available surgical or biopsy specimen were enrolled for this study. With the DNA specimen extracted from previously-collected tumor tissue, somatic mutations and copy number variation (CNV) analyses were performed using targeted exome sequencing. Data regarding the baseline patient characteristics and treatment outcomes were retrospectively obtained by reviewing the patients' medical records. Results: Nineteen patients with GBC (28%), 24 patients with ICC (35%) and 26 patients with ECC (37%) were included in this analysis. Genetic mutation and copy number alteration (CAN) were observed in 59 (85%) and 35 (51%) patients, respectively while 5 patients (7%) did not have any genetic alterations. The most commonly mutated gene was TP53 (n=33, 47.8%), followed by KRAS (n=18, 26.1%), ARID1A (n=10, 14.5%) and IDH1 (n=9, 13.0%). IDH1 mutation appeared more frequently in patients with ICC (n=7, 29.2%, P=0.015) compared to those with GBC (n=1, 5.3%) or ECC (n=1, 3.8%) while ERBB2 and ERBB3 mutation were found only in GBC and ECC. HER2 amplification was observed in 7 patients (4 with GBC and 3 with ICC). Among those, one patient showed 3+ for HER2 test by immunohistochemistry (IHC) while four patients were 2+. All somatic mutations and CNVs documented in the present study were classified into five pathway modules which were identified by Nakamura et al. (Nature Genetics 2015). Majority of genetic alterations (n=45, 65.2%) belonged to Kinase-RAS module, followed by TP53 (n=41, 59.4%), TGF-β-SWI/SNF-MYC (n=22, 31.9%), Epigenetic (n=16, 23.2%) and RB-cell cycle (n=10, 14.5%) modules. Alterations in Epigenetic module were most common in ICC (vs. GB vs. ECC, 50.0% vs. 15.8% vs. 3.8%, P=0.002) while alterations in TGF-β-SWI/SNF-MYC module were most frequent in ECC (vs. GB vs. ICC, 46.2% vs. 3.6% vs. 31.6%, P=0.031). Conclusion: Genetic profile of BTC is heterogeneous according to its anatomic location. Our results indicate that subgroup of BTC patients may have benefit from targeted therapy such anti-IDH and anti-HER2 inhibitors. Citation Format: Heejung Chae, Changhoon Yoo, Deokhoon Kim, Seonmin Lee, Kim Dan Bi, Jae Ho Jeong, Heung-Moon Chang, Baek-Yeol Ryoo, Kyu-pyo Kim. Evaluation of genetic mutations and copy number alterations in biliary tract cancer using targeted exome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3431.

De novo mutations in the SET nuclear proto-oncogene, encoding a component of the inhibitor of histone acetyltransferases (INHAT) complex in patients with nonsyndromic intellectual disability.

The role of disturbed chromatin remodeling in the pathogenesis of intellectual disability (ID) is well established and illustrated by de novo mutations found in a plethora of genes encoding for proteins of the epigenetic regulatory machinery. We describe mutations in the "SET nuclear proto-oncogene" (SET), encoding a component of the "inhibitor of histone acetyltransferases" (INHAT) complex, involved in transcriptional silencing. Using whole exome sequencing, four patients were identified with de novo mutations in the SET gene. Additionally, an affected mother and child were detected who carried a frameshift variant in SET. Four patients were found in literature. The de novo mutations in patients affected all four known SET mRNA transcripts. LoF mutations in SET are exceedingly rare in the normal population and, if present, affect only one transcript. The pivotal role of SET in neurogenesis is evident from in vitro and animal models. SET interacts with numerous proteins involved in histone modification, including proteins encoded by known autosomal dominant ID genes, that is, EP300, CREBBP, SETBP1, KMT2A, RAC1, and CTCF. Our study identifies SET as a new component of epigenetic regulatory modules underlying human cognitive disorders, and as a first member of the Nucleosome Assembly Protein (NAP) family implicated in ID.