• Biomolecules & Therapeutics
• /
• 제20권1호
• /
• pp.43-49
• /
• 2012

Stimulation of mast cells through the high affinity IgE receptor (Fc${\varepsilon}$RI) induces degranulation, lipid mediator release, and cytokine secretion leading to allergic reactions. Although various signaling pathways have been characterized to be involved in the Fc${\varepsilon}$RI-mediated responses, little is known about the precious mechanism for the expression of tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$) in mast cells. Here, we report that rapamycin, a specific inhibitor of mammalian target of rapamycin (mTOR), reduces the expression of TNF-${\alpha}$ in rat basophilic leukemia (RBL-2H3) cells. IgE or specific antigen stimulation of RBL-2H3 cells increases the expression of TNF-${\alpha}$ and activates various signaling molecules including S6K1, Akt and p38 MAPK. Rapamycin specifically inhibits antigeninduced TNF-${\alpha}$ mRNA level, while other kinase inhibitors have no effect on TNF-${\alpha}$ mRNA level. These data indicate that mTOR signaling pathway is the main regulation mechanism for antigen-induced TNF-${\alpha}$ expression. TNF-${\alpha}$ mRNA stability analysis using reporter construct containing TNF-${\alpha}$ adenylate/uridylate-rich elements (AREs) shows that rapamycin destabilizes TNF-${\alpha}$ mRNA via regulating the AU-rich element of TNF-${\alpha}$ mRNA. The antigen-induced activation of S6K1 is inhibited by specific kinase inhibitors including mTOR, PI3K, PKC and $Ca^{2+}$chelator inhibitor, while TNF-${\alpha}$ mRNA level is reduced only by rapamycin treatment. These data suggest that the effects of rapamycin on the expression of TNF-${\alpha}$ mRNA are not mediated by S6K1 but regulated by mTOR. Taken together, our results reveal that mTOR signaling pathway is a novel regulation mechanism for antigen-induced TNF-${\alpha}$ expression in RBL-2H3 cells.

• Genomics & Informatics
• /
• 제13권3호
• /
• pp.70-75
• /
• 2015

MicroRNAs (miRNAs) have been demonstrated to play an important role in carcinogenesis. Previous studies revealed that miRNAs are present in human plasma in a remarkably stable form that is protected from endogenous RNase activity. In this study, we measured the plasma expression levels of three miRNAs (miR-21, miR-27a, and miR-155) to investigate the usefulness of miRNAs for gastric cancer detection. We initially examined plasma miRNA expression levels in a screening cohort consisting of 15 patients with gastric cancer and 15 healthy controls from Korean population, using TaqMan quantitative real-time polymerase chain reaction. We observed that the expression level of miR-27a was significantly higher in patients with gastric cancer than in healthy controls, whereas the miR-21 and miR-155a expression levels were not significantly higher in the patients with gastric cancer. Therefore, we further validated the miR-27a expression level in 73 paired gastric cancer tissues and in a validation plasma cohort from 35 patients with gastric cancer and 35 healthy controls. In both the gastric cancer tissues and the validation plasma cohort, the miR-27a expression levels were significantly higher in patients with gastric cancer. Receiver-operator characteristic (ROC) analysis of the validation cohort, revealed an area under the ROC curve value of 0.70 with 75% sensitivity and 56% specificity in discriminating gastric cancer. Thus, the miR-27a expression level in plasma could be a useful biomarker for the diagnosis and/or prognosis of gastric cancer.

• Molecules and Cells
• /
• 제45권5호
• /
• pp.343-352
• /
• 2022

The advent of the assay for transposase-accessible chromatin using sequencing (ATAC-seq) has shown great potential as a leading method for analyzing the genome-wide profiling of chromatin accessibility. A comprehensive reference to the ATAC-seq dataset for disease progression is important for understanding the regulatory specificity caused by genetic or epigenetic changes. In this study, we present a genome-wide chromatin accessibility profile of 44 liver samples spanning the full histological spectrum of nonalcoholic fatty liver disease (NAFLD). We analyzed the ATAC-seq signal enrichment, fragment size distribution, and correlation coefficients according to the histological severity of NAFLD (healthy control vs steatosis vs fibrotic nonalcoholic steatohepatitis), demonstrating the high quality of the dataset. Consequently, 112,303 merged regions (genomic regions containing one or multiple overlapping peak regions) were identified. Additionally, we found differentially accessible regions (DARs) and performed transcription factor binding motif enrichment analysis and de novo motif analysis to determine new biomarker candidates. These data revealed the gene-regulatory interactions and noncoding factors that can affect NAFLD progression. In summary, our study provides a valuable resource for the human epigenome by applying an advanced approach to facilitate diagnosis and treatment by understanding the non-coding genome of NAFLD.

• Molecules and Cells
• /
• 제46권2호
• /
• pp.120-129
• /
• 2023

Recent technical advances have enabled unbiased transcriptomic and epigenetic analysis of each cell, known as "single-cell analysis". Single-cell analysis has a variety of technical approaches to investigate the state of each cell, including mRNA levels (transcriptome), the immune repertoire (immune repertoire analysis), cell surface proteins (surface proteome analysis), chromatin accessibility (epigenome), and accordance with genome variants (eQTLs; expression quantitative trait loci). As an effective tool for investigating robust immune responses in coronavirus disease 2019 (COVID-19), many researchers performed single-cell analysis to capture the diverse, unbiased immune cell activation and differentiation. Despite challenges elucidating the complicated immune microenvironments of chronic inflammatory diseases using existing experimental methods, it is now possible to capture the simultaneous immune features of different cell types across inflamed tissues using various single-cell tools. In this review, we introduce patient-based and experimental mouse model research utilizing single-cell analyses in the field of chronic inflammatory diseases, as well as multi-organ atlas targeting immune cells.

• Genomics & Informatics
• /
• 제11권2호
• /
• pp.60-67
• /
• 2013

A decade-long project, led by several international research groups, called the Encyclopedia of DNA Elements (ENCODE), recently released an unprecedented amount of data. The ambitious project covers transcriptome, cistrome, epigenome, and interactome data from more than 1,600 sets of experiments in human. To make use of this valuable resource, it is important to understand the information it represents and the techniques that were used to generate these data. In this review, we introduce the data that ENCODE generated, summarize the observations from the data analysis, and revisit a computational approach that ENCODE used to predict gene expression, with a focus on the human transcriptome and its association with chromatin modifications.

• Genomics & Informatics
• /
• 제19권1호
• /
• pp.3.1-3.12
• /
• 2021

Functional interpretation of noncoding genetic variants associated with complex human diseases and traits remains a challenge. In an effort to enhance our understanding of common germline variants associated with lung cancer, we categorize regulatory elements based on eight major cell types of human lung tissue. Our results show that 21.68% of lung cancer-associated risk variants are linked to noncoding regulatory elements, nearly half of which are cell type-specific. Integrative analysis of high-resolution long-range chromatin interactome maps and single-cell RNA-sequencing data of lung tumors uncovers number of putative target genes of these variants and functionally relevant cell types, which display a potential biological link to cancer susceptibility. The present study greatly expands the scope of functional annotation of lung cancer-associated genetic risk factors and dictates probable cell types involved in lung carcinogenesis.

• Genomics & Informatics
• /
• 제16권4호
• /
• pp.17.1-17.6
• /
• 2018

Tumor heterogeneity, the cellular mosaic of multiple lineages arising from the process of clonal evolution, has continued to thwart multi-omics analyses using traditional bulk sequencing methods. The application of single-cell sequencing, in concert with existing genomics methods, has enabled high-resolution interrogation of the genome, transcriptome, epigenome, and proteome. Applied to cancers, these single-cell multi-omics methods bypass previous limitations on data resolution and have enabled a more nuanced understanding of the evolutionary dynamics of tumor progression, immune evasion, metastasis, and treatment resistance. This review details the growing number of novel single-cell multi-omics methods applied to tumors and further discusses recent discoveries emerging from these approaches, especially in regard to immunotherapy.

• Genomics & Informatics
• /
• 제14권1호
• /
• pp.34-40
• /
• 2016

Due to advances in omics technologies, numerous genome-wide studies on human samples have been published, and most of the omics data with the associated clinical information are available in public repositories, such as Gene Expression Omnibus and ArrayExpress. While analyzing several public datasets, we observed that errors in gender information occur quite often in public datasets. When we analyzed the gender description and the methylation patterns of gender-specific probes (glucose-6-phosphate dehydrogenase [G6PD], ephrin-B1 [EFNB1], and testis specific protein, Y-linked 2 [TSPY2]) in 5,611 samples produced using Infinium 450K HumanMethylation arrays, we found that 19 samples from 7 datasets were erroneously described. We also analyzed 1,819 samples produced using the Affymetrix U133Plus2 array using several gender-specific genes (X (inactive)-specific transcript [XIST], eukaryotic translation initiation factor 1A, Y-linked [EIF1AY], and DEAD [Asp-Glu-Ala-Asp] box polypeptide 3, Y-linked [DDDX3Y]) and found that 40 samples from 3 datasets were erroneously described. We suggest that the users of public datasets should not expect that the data are error-free and, whenever possible, that they should check the consistency of the data.

• Journal of Korean Neurosurgical Society
• /
• 제65권1호
• /
• pp.4-12
• /
• 2022

Objective : We reported the differentially methylated genes in patients with subarachnoid hemorrhage (SAH) using bioinformatics analyses to explore the biological characteristics of the development of delayed cerebral ischemia (DCI). Methods : DNA methylation profiles obtained from 40 SAH patients from an epigenome-wide association study were analyzed. Functional enrichment analysis, protein-protein interaction (PPI) network, and module analyses were carried out. Results : A total of 13 patients (32.5%) experienced DCI during the follow-up. In total, we categorized the genes into the two groups of hypermethylation (n=910) and hypomethylation (n=870). The hypermethylated genes referred to biological processes of organic cyclic compound biosynthesis, nucleobase-containing compound biosynthesis, heterocycle biosynthesis, aromatic compound biosynthesis and cellular nitrogen compound biosynthesis. The hypomethylated genes referred to biological processes of carbohydrate metabolism, the regulation of cell size, and the detection of a stimulus, and molecular functions of amylase activity, and hydrolase activity. Based on PPI network and module analysis, three hypermethylation modules were mainly associated with antigen-processing, Golgi-to-ER retrograde transport, and G alpha (i) signaling events, and two hypomethylation modules were associated with post-translational protein phosphorylation and the regulation of natural killer cell chemotaxis. VHL, KIF3A, KIFAP3, RACGAP1, and OPRM1 were identified as hub genes for hypermethylation, and ALB and IL5 as hub genes for hypomethylation. Conclusion : This study provided novel insights into DCI pathogenesis following SAH. Differently methylated hub genes can be useful biomarkers for the accurate DCI diagnosis.

• Tuberculosis and Respiratory Diseases
• /
• 제82권2호
• /
• pp.126-132
• /
• 2019

Background: The development of lung cancer results from the interaction between genetic mutations and dynamic epigenetic alterations, although the exact mechanisms are not completely understood. Changes in DNA methylation may be a promising biomarker for early detection and prognosis of lung cancer. We evaluated the serial changes in genome-wide DNA methylation patterns in blood samples of lung cancer patients. Methods: Blood samples were obtained for three consecutive years from three patients (2 years before, 1 year before, and after lung cancer detection) and from three control subjects (without lung cancer). We used the MethylationEPIC BeadChip method, which covers the 850,000 bp cytosine-phosphate-guanine (CpG) site, to conduct an epigenome-wide analysis. Significant differentially methylated regions (DMRs) were identified using p-values <0.05 in a correlation test identifying serial methylation changes and serial increase or decrease in ${\beta}$ value above 0.1 for three consecutive years. Results: We found three significant CpG sites with differentially methylated ${\beta}$ values and 7,105 CpG sites with significant correlation from control patients without lung cancer. However, there were no significant DMRs. In contrast, we found 11 significant CpG sites with differentially methylated ${\beta}$ values and 10,562 CpG sites with significant correlation from patients with lung cancer. There were two significant DMRs: cg21126229 (RNF212) and cg27098574 (BCAR1). Conclusion: This study revealed DNA methylation changes that might be implicated in lung cancer development. The DNA methylation changes may be the possible candidate target regions for the early detection and prevention of lung cancer.