Spatial transcriptomic analysis of tumour-immune cell interactions in melanoma arising from congenital melanocytic nevus.

BACKGROUND: Studies on the interaction between tumour-infiltrating immune cells (TIICs) and tumour cells in melanoma arising from congenital melanocytic nevus (CMN) are lacking. OBJECTIVE: The aim of this study was to determine the intratumoral immune landscape of TIICs and tumour cells during invasion and metastasis. METHODS: Tissue specimens were obtained from patients with melanoma originating from CMN. Differential gene expression in melanoma cells and TIICs during invasion and metastasis was determined using spatial transcriptomics. RESULTS: As invasion depth increased, the expression of LGALS3, known to induce tumour-driven immunosuppression, increased in melanoma cells. In T cells, the expression of genes that inhibit T-cell activation increased with increasing invasion depth. In macrophages, the expression of genes related to the anti-inflammatory M2 phenotype was upregulated with increasing invasion depth. Compared to primary tumour cells, melanoma cells in metastatic lesions showed upregulated expression of genes associated with cancer immune evasion, including AXL and EPHA2, which impede T-cell recruitment, and BST2, associated with M2 polarization. Furthermore, T cells showed increased expression of genes related to immunosuppression, and macrophages exhibited increased expression of genes associated with the M2 phenotype. CONCLUSIONS: The interaction between melanomas arising from CMN and TIICs may be important for tumour progression and metastasis.

Systemic Inflammatory Proteomic Biomarkers in Atopic Dermatitis: Exploring Potential Indicators for Disease Severity.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory cutaneous disorder, that emerges from intricate interplays among genetic predisposition, immune dysregulation, environmental factors, and compromised skin barrier. Understanding the inflammatory pathway in AD is important due to its fundamental role in the pathogenesis of AD. This study aimed to explore the diverse spectrum of proteins linked to the inflammation of AD and the relationship between systemic biomarkers and clinical severity in AD. METHODS: We examined the blood samples from 48 patients with AD and 48 healthy controls (HCs) using the Proximity Extension Assay (Olink). Differentially expressed proteins (DEPs) were identified and Pearson correlation analysis was conducted to determine systemic proteomic biomarkers associated with severity of AD. RESULTS: A total of 29 DEPs were significantly up-regulated and 2 DEPs were significantly down-regulated in AD compared with the HC. The MCP-4, IL-18, MCP-3, TNFRSF9, and IL-17C were the top 5 highest DEPs associated with the severity of AD. CONCLUSION: Our study sheds light on the intricate network of inflammatory proteins in AD and their potential implications for disease severity. Our results indicate that these systemic inflammatory proteins could be valuable for assessing AD severity and enhancing our understanding of the disease's complexity and its potential management strategies.

PCTC-Net: A Crack Segmentation Network with Parallel Dual Encoder Network Fusing Pre-Conv-Based Transformers and Convolutional Neural Networks.

Cracks are common defects that occur on the surfaces of objects and structures. Crack detection is a critical maintenance task that traditionally requires manual labor. Large-scale manual inspections are expensive. Research has been conducted to replace expensive human labor with cheaper computing resources. Recently, crack segmentation based on convolutional neural networks (CNNs) and transformers has been actively investigated for local and global information. However, the transformer is data-intensive owing to its weak inductive bias. Existing labeled datasets for crack segmentation are relatively small. Additionally, a limited amount of fine-grained crack data is available. To address this data-intensive problem, we propose a parallel dual encoder network fusing Pre-Conv-based Transformers and convolutional neural networks (PCTC-Net). The Pre-Conv module automatically optimizes each color channel with a small spatial kernel before the input of the transformer. The proposed model, PCTC-Net, was tested with the DeepCrack, Crack500, and Crackseg9k datasets. The experimental results showed that our model achieved higher generalization performance, stability, and F1 scores than the SOTA model DTrC-Net.

The Potential of Campanula takesimana Callus Extract to Enhance Skin Barrier Function.

Atopic dermatitis (AD) is a prevalent inflammatory skin disease characterized by epidermal barrier dysfunction and Th2-skewed inflammation. Campanula takesimana (C. takesimana), a Korean endemic plant grown on Ulleng Island, has long been associated with a traditional alternative medicine for asthma, tonsillitis, and sore throat. In this study, we reported the effect of C. takesimana callus extract on upregulating epidermal barrier-related proteins dysregulated by Th2 cytokines. C. takesimana callus extract induced the expression of skin barrier proteins, such as filaggrin, claudin-1, and zonula occludens-1, in both human primary keratinocytes and Th2-induced AD-like skin-equivalent models. Additionally, RNA sequencing analysis demonstrated that C. takesimana callus extract partially restored Th2 cytokine-induced dysregulation of the epidermal development and lipid metabolic pathways. Considering the advantages of callus as a sustainable eco-friendly source of bioactive substances, and its effect on skin barrier proteins and lipid metabolic pathways, C. takesimana callus extracts can possibly be utilized to improve the integrity of the skin barrier.

Venn-diaNet : venn diagram based network propagation analysis framework for comparing multiple biological experiments.

BACKGROUND: The main research topic in this paper is how to compare multiple biological experiments using transcriptome data, where each experiment is measured and designed to compare control and treated samples. Comparison of multiple biological experiments is usually performed in terms of the number of DEGs in an arbitrary combination of biological experiments. This process is usually facilitated with Venn diagram but there are several issues when Venn diagram is used to compare and analyze multiple experiments in terms of DEGs. First, current Venn diagram tools do not provide systematic analysis to prioritize genes. Because that current tools generally do not fully focus to prioritize genes, genes that are located in the segments in the Venn diagram (especially, intersection) is usually difficult to rank. Second, elucidating the phenotypic difference only with the lists of DEGs and expression values is challenging when the experimental designs have the combination of treatments. Experiment designs that aim to find the synergistic effect of the combination of treatments are very difficult to find without an informative system. RESULTS: We introduce Venn-diaNet, a Venn diagram based analysis framework that uses network propagation upon protein-protein interaction network to prioritizes genes from experiments that have multiple DEG lists. We suggest that the two issues can be effectively handled by ranking or prioritizing genes with segments of a Venn diagram. The user can easily compare multiple DEG lists with gene rankings, which is easy to understand and also can be coupled with additional analysis for their purposes. Our system provides a web-based interface to select seed genes in any of areas in a Venn diagram and then perform network propagation analysis to measure the influence of the selected seed genes in terms of ranked list of DEGs. CONCLUSIONS: We suggest that our system can logically guide to select seed genes without additional prior knowledge that makes us free from the seed selection of network propagation issues. We showed that Venn-diaNet can reproduce the research findings reported in the original papers that have experiments that compare two, three and eight experiments. Venn-diaNet is freely available at: http://biohealth.snu.ac.kr/software/venndianet.

Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways.

MOTIVATION: To understand the dynamic nature of the biological process, it is crucial to identify perturbed pathways in an altered environment and also to infer regulators that trigger the response. Current time-series analysis methods, however, are not powerful enough to identify perturbed pathways and regulators simultaneously. Widely used methods include methods to determine gene sets such as differentially expressed genes or gene clusters and these genes sets need to be further interpreted in terms of biological pathways using other tools. Most pathway analysis methods are not designed for time series data and they do not consider gene-gene influence on the time dimension. RESULTS: In this article, we propose a novel time-series analysis method TimeTP for determining transcription factors (TFs) regulating pathway perturbation, which narrows the focus to perturbed sub-pathways and utilizes the gene regulatory network and protein-protein interaction network to locate TFs triggering the perturbation. TimeTP first identifies perturbed sub-pathways that propagate the expression changes along the time. Starting points of the perturbed sub-pathways are mapped into the network and the most influential TFs are determined by influence maximization technique. The analysis result is visually summarized in TF-PATHWAY MAP IN TIME CLOCK: TimeTP was applied to PIK3CA knock-in dataset and found significant sub-pathways and their regulators relevant to the PIP3 signaling pathway. AVAILABILITY AND IMPLEMENTATION: TimeTP is implemented in Python and available at http://biohealth.snu.ac.kr/software/TimeTP/Supplementary information: Supplementary data are available at Bioinformatics online. CONTACT: sunkim.bioinfo@snu.ac.kr.

The postnatal injection of AAV9-FOXG1 rescues corpus callosum agenesis and other brain deficits in the mouse model of FOXG1 syndrome.

Heterozygous mutations in the FOXG1 gene manifest as FOXG1 syndrome, a severe neurodevelopmental disorder characterized by structural brain anomalies, including agenesis of the corpus callosum, hippocampal reduction, and myelination delays. Despite the well-defined genetic basis of FOXG1 syndrome, therapeutic interventions targeting the underlying cause of the disorder are nonexistent. In this study, we explore the therapeutic potential of adeno-associated virus 9 (AAV9)-mediated delivery of the FOXG1 gene. Remarkably, intracerebroventricular injection of AAV9-FOXG1 to Foxg1 heterozygous mouse model at the postnatal stage rescues a wide range of brain pathologies. This includes the amelioration of corpus callosum deficiencies, the restoration of dentate gyrus morphology in the hippocampus, the normalization of oligodendrocyte lineage cell numbers, and the rectification of myelination anomalies. Our findings highlight the efficacy of AAV9-based gene therapy as a viable treatment strategy for FOXG1 syndrome and potentially other neurodevelopmental disorders with similar brain malformations, asserting its therapeutic relevance in postnatal stages.

Spatial Transcriptomic Signatures of Early Acute T Cell-mediated Rejection in Kidney Transplants.

Background: Kidney transplantation significantly improves the quality of life for those with end-stage renal failure, yet allograft rejection resulting from immune cell interactions remains a persistent challenge. Although T cell-directed immunosuppressive drugs effectively contain graft rejection in most patients, a notable proportion still experiences acute T cell-mediated rejection (TCMR). Despite an emphasis on suppressing T cell-mediated immune responses, successful control over TCMR is not always achieved, suggesting the potential involvement of factors beyond T cells. Methods: Biopsy samples from suspicious (borderline) for acute TCMR (borderline TCMR) and non-TCMR patients were obtained 9 d postsurgery, and spatial transcriptomics profiling was conducted using the GeoMx Digital Spatial Profiler platform. Regions of interest in the glomerulus and interstitium were selected on the basis of immunohistochemistry staining anti-CD3 to identify areas with T-lymphocyte infiltration. Differential gene expression analysis was performed using unpaired t tests. Results: Unbiased clustering of transcriptional profiles across all regions of interest showed distinct transcriptional profiles between glomeruli and interstitium in non-TCMR samples, whereas borderline TCMR samples displayed no distinct transcriptional profiles between these regions. Contrary to the prevailing T cell-centric view, we observed pathways and genes associated with innate immunity-related inflammatory conditions expressed in glomerular regions of borderline TCMR biopsies. Immunofluorescence staining for CD68 confirmed the presence of macrophages in the glomeruli of the post-TCMR sample in a validation cohort, indicating macrophage involvement in the glomerular response after TCMR. Conclusions: Activation of the innate immune response in borderline TCMR appears to impact not only the interstitium but also the glomerulus. Glomerulus-specific immune signatures suggest the role of the innate immune system in rejection. This nuanced understanding proposes the necessity for tailored therapeutic interventions targeting both innate and adaptive immune pathways to enhance transplant outcomes.

Proteomic analysis of cardiovascular disease-associated proteins in Korean patients with moderate-to-severe atopic dermatitis.

Background: Cardiovascular diseases (CVDs) have been associated with atopic dermatitis (AD), including in Korean patients. Previous studies on AD have primarily focused on patients of European ancestry, while the Asian endotype exhibits distinct characteristics. This study aimed to characterize the blood proteomic signature of Korean patients with moderate-to-severe AD, with an emphasis on proteins related to CVDs. Methods: A total of 78 participants, including 39 patients with moderate-to-severe AD and 39 age- and sex-matched healthy controls, were enrolled. Blood proteomics analysis was performed using the Olink CVD II panel, which measures the expression levels of 92 proteins associated with CVDs. Results: Unsupervised hierarchical clustering revealed 44 upregulated and 5 downregulated proteins in AD patients compared to healthy controls. Principal component analysis (PCA) effectively distinguished AD patients from healthy subjects based on the complete set of proteins or the subset of upregulated proteins. A multiple linear regression model comprising CCL17 and FGF21 showed a strong correlation with disease severity (R = 0.619). Correlation analysis identified 25 highly correlated proteins, including STK4, ITGB1BP2, and DECR1, which were newly found to be upregulated in Korean AD patients. Pathway analysis highlighted the involvement of these proteins in vascular system, inflammation, and lipid metabolism pathways. Conclusion: The blood proteomic profile of moderate-to-severe AD patients in Korea differed from healthy controls using the CVD II panel. This study provides potential biomarkers for the AD-CVD association and insights into the pathways contributing to this relationship in the Korean population.

Comprehensive profiling of DNA methylation in Korean patients with colorectal cancer.

Alterations in DNA methylation play an important pathophysiological role in the development and progression of colorectal cancer. We comprehensively profiled DNA methylation alterations in 165 Korean patients with colorectal cancer (CRC), and conducted an in-depth investigation of cancer-specific methylation patterns. Our analysis of the tumor samples revealed a significant presence of hypomethylated probes, primarily within the gene body regions; few hypermethylated sites were observed, which were mostly enriched in promoter-like and CpG island regions. The CpG Island Methylator PhenotypeHigh (CIMP-H) exhibited notable enrichment of microsatellite instability-high (MSI-H). Additionally, our findings indicated a significant correlation between methylation of the MLH1 gene and MSI-H status. Furthermore, we found that the CIMP-H had a higher tendency to affect the right-side of the colon tissues and was slightly more prevalent among older patients. Through our methylome profile analysis, we successfully verified the thylation patterns and clinical characteristics of Korean patients with CRC. This valuable dataset lays a strong foundation for exploring novel molecular insights and potential therapeutic targets for the treatment of CRC. [BMB Reports 2024; 57(2): 110-115].

Environment-Adaptable Rotational Energy Harvesters Based on Nylon-core Coiled Carbon Nanotube Yarns.

Owing to increasing amount of research on energy harvesting, studies on harvesters for practical application and their performance are attracting attention. Therefore, studies on the use of continuous energy as an energy source for energy-harvesting devices are being conducted, and fluid flows, e.g., wind, river flow, and sea wave, are widely used as input energy sources for continuous energy harvesting. A new energy-harvesting technology has emerged based on the mechanical stretch and release of coiled carbon nanotube (CNT) yarns, which generate energy based on the change in the electrochemical double-layer capacitance. First, this CNT yarn-based mechanical energy harvester is demonstrated, which is applicable to various environments where fluid flow exists. This environment-adaptable harvester uses rotational energy as the mechanical energy source and is tested in river and ocean environments. Moreover, an attachable-type harvester for the application of the existing rotational system is devised. In the case of a slow rotational environment, a square-wave strain-applying harvester has been implemented, which can convert sinusoidal strain motion into square-wave strain motion for high output voltages. To achieve high performance of practical harvesting applications, a scale-up method for powering signal-transmitting devices has been implemented.

High-Performance One-Body Electrochemical Torsional Artificial Muscles Built Using Carbon Nanotubes and Ion-Exchange Polymers.

Electrochemical torsional artificial muscles have the potential to replace electric motors in the field of miniaturization. In particular, carbon nanotubes (CNTs) are some of the best materials for electrochemical torsional artificial muscles due to their remarkable mechanical strength and high electrical conductivity. However, previous studies on CNT torsional muscle utilize only half of the whole potential range for torsional actuation because the actuations in the positive and negative voltage ranges offset each other. Here, we used an ion-exchange polymer, poly(sodium 4-styrenesulfonate) (PSS), which leads to the participation of only positive ions in the actuation of CNT muscles so that the whole potential range can be used for torsional actuation. As a result, PSS-coated CNT muscle can provide 1.9 times higher torsional actuation compared to neat CNT torsional muscle. This PSS-coated CNT muscle not only provides high performance but also facilitates a one-body system for electrochemical torsional actuation. From these advantages, we implement a one-body torsional muscle for the realization of the forward motion of a model boat. This high performance and one-body structure for electrochemical torsional muscles can be used for further applications, such as soft robotics and implantable devices.

Electrically Driven Sub-Micrometer Light-Emitting Diode Arrays Using Maskless and Etching-Free Pixelation.

For decades, group-III-nitride-based light-emitting diodes (LEDs) have been regarded as a light emitting source for future displays by virtue of their novel properties such as high efficiency, brightness, and stability. Nevertheless, realization of high pixel density displays is still challenging due to limitations of pixelation methods. Here, a maskless and etching-free micro-LED (µLED) pixelation method is developed via tailored He focused ion beam (FIB) irradiation technique, and electrically driven sub-micrometer-scale µLED pixel arrays are demonstrated. It is confirmed that optical quenching and electrical isolation effects are simultaneously induced at a certain ion dose (≈1014 ions cm-2 ) without surface damage. Furthermore, highly efficient µLED pixel arrays at sub-micrometer scale (square pixel, 0.5 µm side length) are fabricated. Their pixelation and brightness are verified by various optical measurements such as cathodo-, photo-, and electroluminescence. It is expected that the FIB-induced optical quenching and electrical isolation method can pioneer a new defect engineering technology not only for µLED fabrication, but also for sub-micrometer-scale optoelectronic devices.

Mesenchymal stem cell-derived extracellular vesicles subvert Th17 cells by destabilizing RORγt through posttranslational modification.

Mesenchymal stem cell (MSC)-derived small extracellular vesicles (MSC-sEVs) are known to exert immunosuppressive functions. This study showed that MSC-sEVs specifically convert T helper 17 (Th17) cells into IL-17 low-producer (ex-Th17) cells by degrading RAR-related orphan receptor γt (RORγt) at the protein level. In experimental autoimmune encephalomyelitis (EAE)-induced mice, treatment with MSC-sEVs was found to not only ameliorate clinical symptoms but also to reduce the number of Th17 cells in draining lymph nodes and the central nervous system. MSC-sEVs were found to destabilize RORγt by K63 deubiquitination and deacetylation, which was attributed to the EP300-interacting inhibitor of differentiation 3 (Eid3) contained in the MSC-sEVs. Small extracellular vesicles isolated from the Eid3 knockdown MSCs by Eid3-shRNA failed to downregulate RORγt. Moreover, forced expression of Eid3 by gene transfection was found to significantly decrease the protein level of RORγt in Th17 cells. Altogether, this study reveals the novel immunosuppressive mechanisms of MSC-sEVs, which suggests the feasibility of MSC-sEVs as an attractive therapeutic tool for curing Th17-mediated inflammatory diseases.

The patient-specific mouse model with Foxg1 frameshift mutation uncovers the pathophysiology of FOXG1 syndrome.

Single allelic mutations in the gene encoding the forebrain-specific transcription factor FOXG1 lead to FOXG1 syndrome (FS). Patient-specific animal models are needed to understand the etiology of FS, as FS patients show a wide spectrum of symptoms correlated with location and mutation type in the FOXG1 gene. Here we report the first patient-specific FS mouse model, Q84Pfs heterozygous (Q84Pfs-Het) mice, mimicking one of the most predominant single nucleotide variants in FS. Intriguingly, we found that Q84Pfs-Het mice faithfully recapitulate human FS phenotypes at the cellular, brain structural, and behavioral levels. Importantly, Q84Pfs-Het mice exhibited myelination deficits like FS patients. Further, our transcriptome analysis of Q84Pfs-Het cortex revealed a new role for FOXG1 in synapse and oligodendrocyte development. The dysregulated genes in Q84Pfs-Het brains also predicted motor dysfunction and autism-like phenotypes. Correspondingly, Q84Pfs-Het mice showed movement deficits, repetitive behaviors, increased anxiety, and prolonged behavior arrest. Together, our study revealed the crucial postnatal role of FOXG1 in neuronal maturation and myelination and elucidated the essential pathophysiology mechanisms of FS.

MLDEG: A Machine Learning Approach to Identify Differentially Expressed Genes Using Network Property and Network Propagation.

MOTIVATION: Identifying differentially expressed genes (DEGs) in transcriptome data is a very important task. However, performances of existing DEG methods vary significantly for data sets measured in different conditions and no single statistical or machine learning model for DEG detection perform consistently well for data sets of different traits. In addition, setting a cutoff value for the significance of differential expressions is one of confounding factors to determine DEGs. RESULTS: We address these problems by developing an ensemble model that refines the heterogeneous and inconsistent results of the existing methods by taking accounts into network information such as network propagation and network property. DEG candidates that are predicted with weak evidence by the existing tools are re-classified by our proposed ensemble model for the transcriptome data. Tested on 10 RNA-seq datasets downloaded from gene expression omnibus (GEO), our method showed excellent performance of winning the first place in detecting ground truth (GT) genes in eight datasets and find almost all GT genes in six datasets. On the other hand, performances of all existing methods varied significantly for the 10 data sets. Because of the design principle, our method can accommodate any new DEG methods naturally. AVAILABILITY: The source code of our method is available at https://github.com/jihmoon/MLDEG.

A Coiled Carbon Nanotube Yarn-Integrated Surface Electromyography System To Monitor Isotonic and Isometric Movements.

A surface electromyogram (sEMG) electrode collects electrical currents generated by neuromuscular activity by a noninvasive technique on the skin. It is particularly attractive for wearable systems for various human activities and health care monitoring. However, it remains challenging to discriminate EMG signals from isotonic (concentric/eccentric) and isometric movements. By applying nanotechnology, we provide a coiled carbon nanotube (CNT) yarn-integrated sEMG device to overcome sEMG-based motion recognition. When the arm was contracted at different angles, the sEMG-derived root mean square amplitude signals were constant regardless of the angle of the moving arm. However, the coiled CNT yarn-derived open circuit voltage (OCV) signals proportionally increased when the arm's angle increased, and presented negative and positive values depending on the moving direction of the arm. Moreover, isometric contraction is characterized by the onset of EMG signals without an OCV signal, and isotonic contraction is determined by both EMG signals and OCV signals. Taken together, the integration of EMG and coiled CNT yarn electrodes provides complementary information, including the strength, direction, and degree of muscle movement. Therefore, we suggest that our system has high potential as a wearable system to monitor human motions in industrial and human system applications.

More Powerful Twistron Carbon Nanotube Yarn Mechanical Energy Harvesters.

Stretching a coiled carbon nanotube (CNT) yarn can provide large, reversible electrochemical capacitance changes, which convert mechanical energy to electricity. Here, it is shown that the performance of these "twistron" harvesters can be increased by optimizing the alignment of precursor CNT forests, plastically stretching the precursor twisted yarn, applying much higher tensile loads during precoiling twist than for coiling, using electrothermal pulse annealing under tension, and incorporating reduced graphene oxide nanoplates. The peak output power for a 1 and a 30 Hz sinusoidal deformation are 0.73 and 3.19 kW kg-1 , respectively, which are 24- and 13-fold that of previous twistron harvesters at these respective frequencies. This performance at 30 Hz is over 12-fold that of other prior-art mechanical energy harvesters for frequencies between 0.1 and 600 Hz. The maximum energy conversion efficiency is 7.2-fold that for previous twistrons. Twistron anode and cathode yarn arrays are stretched 180° out-of-phase by locating them in the negative and positive compressibility directions of hinged wine-rack frames, thereby doubling the output voltage and reducing the input mechanical energy.

A successfully treated case of primary purulent pericarditis complicated by cardiac tamponade and pneumopericardium.

Acute pericarditis is caused by various factors, but purulent pericarditis is rare. Primary purulent pericarditis in immunocompetent hosts is very rare in the modern antibiotics era. We report a successfully treated case of primary purulent pericarditis complicated with cardiac tamponade and pneumopericardium in an immunocompetent host. A 69-year-old female was referred from another hospital because of pleuritic chest pain with a large amount of pericardial effusion. She was diagnosed with acute pericarditis accompanied by cardiac tamponade. We performed emergency pericardiocentesis, with drainage of 360 ml of bloody pericardial fluid. The culture grew Streptococcus anginosus, confirming the diagnosis of acute purulent pericarditis. We performed pericardiostomy because cardiomegaly and pneumopericardium were aggravated after removal of the pericardial drainage catheter. The patient received antibiotics for a total of 23 days intravenously and was discharged with oral antibiotic therapy. Purulent pericarditis is one of the rare forms of pericarditis and is lifethreatening. A multimodality approach is required for proper diagnosis and treatment of this disease.

Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer.

BACKGROUND: In cancer, mutations of DNA methylation modification genes have crucial roles for epigenetic modifications genome-wide, which lead to the activation or suppression of important genes including tumor suppressor genes. Mutations on the epigenetic modifiers could affect the enzyme activity, which would result in the difference in genome-wide methylation profiles and, activation of downstream genes. Therefore, we investigated the effect of mutations on DNA methylation modification genes such as DNMT1, DNMT3A, MBD1, MBD4, TET1, TET2 and TET3 through a pan-cancer analysis. METHODS: First, we investigated the effect of mutations in DNA methylation modification genes on genome-wide methylation profiles. We collected 3,644 samples that have both of mRNA and methylation data from 12 major cancer types in The Cancer Genome Atlas (TCGA). The samples were divided into two groups according to the mutational signature. Differentially methylated regions (DMR) that overlapped with the promoter region were selected using minfi and differentially expressed genes (DEG) were identified using EBSeq. By integrating the DMR and DEG results, we constructed a comprehensive DNA methylome profiles on a pan-cancer scale. Second, we investigated the effect of DNA methylations in the promoter regions on downstream genes by comparing the two groups of samples in 11 cancer types. To investigate the effects of promoter methylation on downstream gene activations, we performed clustering analysis of DEGs. Among the DEGs, we selected highly correlated gene set that had differentially methylated promoter regions using graph based sub-network clustering methods. RESULTS: We chose an up-regulated DEGs cluster where had hypomethylated promoter in acute myeloid leukemia (LAML) and another down-regulated DEGs cluster where had hypermethylated promoter in colon adenocarcinoma (COAD). To rule out effects of gene regulation by transcription factor (TF), if differentially expressed TFs bound to the promoter of DEGs, that DEGs did not included to the gene set that effected by DNA methylation modifiers. Consequently, we identified 54 hypomethylated promoter DMR up-regulated DEGs in LAML and 45 hypermethylated promoter DMR down-regulated DEGs in COAD. CONCLUSIONS: Our study on DNA methylation modification genes in mutated vs. non-mutated groups could provide useful insight into the epigenetic regulation of DEGs in cancer.