Integrated Analysis of Tissue-Specific Promoter Methylation and Gene Expression Profile in Complex Diseases

Lee, Kibaick; Moon, Sanghoon; Park, Mi Jin; Koh, Insong; Choi, Nak Hyeon; Yu, Ho Yeong; Kim, Young Jin; Kong, Jinhwa; Kang, Hee Gyung; Kim, Song Cheol; Kim, Bong-Jo

doi:10.3390/ijms21145056

Cited by 10 publications

(7 citation statements)

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“…Amongst the 23 papers included in this systematic review, 19 papers reported studies on DNA methylation, 2 papers presented data on histone modifications and 2 papers conducted studies on lncRNAs. Of the 19 papers that reported data on DNA methylation in AT from individuals with MUHO, 8 papers performed targeted epigenome studies (52-59) and 11 papers reported genome-wide studies (60)(61)(62)(63)(64)(65)(66)(67)(68)(69)(70). The main findings on the targeted DNA methylation studies are summarized in Table 1.…”

Section: Literature Searchmentioning

confidence: 99%

Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review

et al. 2021

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BackgroundObesity is a major risk factor for dysglycemic disorders, including type 2 diabetes (T2D). However, there is wide phenotypic variation in metabolic profiles. Tissue-specific epigenetic modifications could be partially accountable for the observed phenotypic variability.ScopeThe aim of this systematic review was to summarize the available data on epigenetic signatures in human adipose tissue (AT) that characterize overweight or obesity-related insulin resistance (IR) and dysglycemia states and to identify potential underlying mechanisms through the use of unbiased bioinformatics approaches.MethodsOriginal data published in the last decade concerning the comparison of epigenetic marks in human AT of individuals with metabolically unhealthy overweight/obesity (MUHO) versus normal weight individuals or individuals with metabolically healthy overweight/obesity (MHO) was assessed. Furthermore, association of these epigenetic marks with IR/dysglycemic traits, including T2D, was compiled.ResultsWe catalogued more than two thousand differentially methylated regions (DMRs; above the cut-off of 5%) in the AT of individuals with MUHO compared to individuals with MHO. These DNA methylation changes were less likely to occur around the promoter regions and were enriched at loci implicated in intracellular signaling (signal transduction mediated by small GTPases, ERK1/2 signaling and intracellular trafficking). We also identified a network of seven transcription factors that may play an important role in targeting DNA methylation changes to specific genes in the AT of subjects with MUHO, contributing to the pathogeny of obesity-related IR/T2D. Furthermore, we found differentially methylated CpG sites at 8 genes that were present in AT and whole blood, suggesting that DMRs in whole blood could be potentially used as accessible biomarkers of MUHO.ConclusionsThe overall evidence linking epigenetic alterations in key tissues such AT to metabolic complications in human obesity is still very limited, highlighting the need for further studies, particularly those focusing on epigenetic marks other than DNA methylation. Our initial analysis suggests that DNA methylation patterns can potentially discriminate between MUHO from MHO and provide new clues into why some people with obesity are less susceptible to dysglycemia. Identifying AT-specific epigenetic targets could also lead to novel approaches to modify the progression of individuals with obesity towards metabolic disease.Systematic Review RegistrationPROSPERO, identifier CRD42021227237.

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Section: Literature Searchmentioning

confidence: 99%

Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review

et al. 2021

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“…As only SOX7 had a significant correlation between CNV and its expression, we continued to explore factors that may affect the expression of SOX17 and SOX18 from other perspectives. It has been reported that the methylation of the promoter region can affect the expression of genes (37). Therefore, we explored the methylation of SOXF family genes.…”

Section: Discussionmentioning

confidence: 99%

“…The expression of SOX17 is more affected by the level of methylation, but the factors affecting the changes in SOX18 expression still need to be explored. It has been reported that the methylation of the promoter region of the RASSF1 gene can be used as an effective biomarker for the early diagnosis of lung cancer (37). To explore whether SOXF family genes have similar capabilities, we compared SOXF family genes with RASSF1.…”

Section: Discussionmentioning

confidence: 99%

“…Gene methylation will also affect gene expression (37), so we further explored the methylation of the SOXF group gene family. The results showed that in people with of pathological stages (Figure 9A-9C), different age groups (Figure 9D-9F), different genders (Figure 9G-9I), and different lymph node metastases (Figure 9J-9L), the promoter methylation level of SOXF family genes in normal samples was very low, while the promoter methylation level in tumor samples was significantly increased.…”

Section: Soxf Group Gene Family Methylation Analysis and Biomarker Ex...mentioning

confidence: 99%

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Bioinformatics analysis of SOXF family genes reveals potential regulatory mechanism and diagnostic value in cancers

Jiang

Zheng

et al. 2022

Ann Transl Med

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Background: SOXF family genes (SOX7, SOX17, SOX18) have been reported to involved in tumorigenesis and development in previous articles, separately. But data sources, analysis contents and criteria are not same. Here, we focused on SOXF genes to analyze the regulatory mechanisms and diagnostic value at the same standards.Methods: This study analyzed functions, expressions, methylations, and mutations of SOXF genes through public databases including Metascape, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, Tumor IMmune Estimation Resource (TIMER), and Kaplan-Meier Plotter. TIMER applies a deconvolution method to infer the abundance of tumor-infiltrating immune cells (TIICs) from gene expression profiles.Metascape combines several biological functions and over 40 independent knowledge bases within one integrated portal. GEPIA analyses RNA sequencing expression data from the The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects. The cBioPortal visualizes and analyses genetic data from cancer studies.Results: This study found that SOXF genes had low expressions in multiple types of cancer, such as lung cancer and breast cancer (ANOVA differential methods, |log2FC| cutoff: 1, q value cutoff: 0.01). The lung adenocarcinoma (LUAD) patients with high expression of SOX7 [HR =0.72 (0.61-0.85), logrank P=8.1e-05) and SOX17 [HR =0.54 (0.45-0.64), logrank P=1.7e-12] had a higher overall survival (OS) rate. Expression of SOX7 was significantly related to the copy number variation (CNV) (P=3.02e-8) and promoter methylation level (P=5.33e-14), while SOX17 was only related to the promoter methylation level (P=3.32e-12). The expression of SOXF genes was positively correlated with CD4 + T cell infiltration (SOX7: P=8.32e-07, SOX17: P=4.93e-06, SOX18: P=1.61e-11). The AUC for cg07660671 site of SOX7, cg15377283 site of SOX17, and cg24199599 site of SOX18 in distinguishing between normal and tumor in LUAD, intestinal cancer, and breast cancer reached 0.9. SOXF genes were mainly involved in transcriptional regulation, and the Wnt signaling pathway and low expression of SOXF genes in tumor tissue had a strong negative correlation with tumor hypoxia (correlation: −0.35, P≤0.001).Conclusions: This study implied that the expression of SOX7 and SOX17 are potential prognosis markers for patients with Lung cancer and the SOXF genes methylation is potential biomarkers for pan-cancer screening. The SOX7 and SOX17 might modulate the Wnt signaling pathway and the expression of SOXF family genes was significantly negatively correlated with tumor hypoxia.

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“…Gene mutation and methylation can regulate gene expression ( 23 , 24 ). The study demonstrated that the incidence of SNV mutations was very low.…”

Section: Discussionmentioning

confidence: 99%

A pan-cancer analysis of the expression of gasdermin genes in tumors and their relationship with the immune microenvironment

Wang¹,

Shi²,

Xu³

et al. 2021

Transl Cancer Res TCR

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Background: Gasdermins (GSDMs) are a class of proteins related to pyrolysis and in humans, consist of GSDMA, GSDMB, GSDMC, GSDMD, DFNA5, and DFNB59. The inflammatory factors and cell contents released during pyrolysis can recruit immune cells and change the microenvironment. However, to date, there is a paucity of studies examining the relationship between GSDMs and the immune microenvironment in tumors. Therefore, this current report analyzed the expression of GSDM genes in tumors and their relationship with the immune microenvironment.Methods: Apply GSCALite and GEPIA2 online analysis tools to analyze the gene expression levels and the Single nucleotide variant (SNV), copy number variation (CNV), and methylation characteristics of GSDM genes respectively. Use R software or TISIDB online analysis tool to carry out the correlation analysis required in the article. Furthermore, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to examine the role of these GSDM genes in various cancers. Results:The results demonstrated that CNV can cause an increase in GSDM gene expression, and methylation can inhibit GSDM gene expression. The elevated expression of GSDMA, GSDMB, GSDMC, GSDMD, and DFNA5 in some or most tumors was often accompanied by elevated immune scores, increased immune cell infiltration, and high expression of major histocompatibility complex (MHC) molecules, chemokines and their receptors, and immune checkpoint-related genes. However, DFNB59 was often negatively correlated with these indicators in tumors. GSDMD was the most highly expressed GSDM protein in various normal tissues and tumors, and showed the strongest correlation with immune microenvironment-related genes. Moreover, the methylation of GSDMD was accompanied by low immune cell infiltration, low expression of MHC molecule-related genes, low expression of chemokines and receptorrelated genes, and low expression of immune checkpoint-related genes.Conclusions: Therefore, the expression of GSDM-related genes is associated with the tumor immune microenvironment. The GSDM genes, especially GSDMD, may be used as therapeutic targets to predict or change the tumor microenvironment and as biomarkers to predict the therapeutic efficacy of immune checkpoint inhibitors.

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Integrated Analysis of Tissue-Specific Promoter Methylation and Gene Expression Profile in Complex Diseases

Cited by 10 publications

References 74 publications

Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review

Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review

Bioinformatics analysis of SOXF family genes reveals potential regulatory mechanism and diagnostic value in cancers

A pan-cancer analysis of the expression of gasdermin genes in tumors and their relationship with the immune microenvironment

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