scholarly journals Methylation Drivers and Prognostic Implications in Sinonasal Poorly Differentiated Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 5030
Author(s):  
Laura Libera ◽  
Giorgia Ottini ◽  
Nora Sahnane ◽  
Fabiana Pettenon ◽  
Mario Turri-Zanoni ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Undifferentiated Carcinoma ◽  
Driver Genes ◽  
Histopathological Classification ◽  
Dna Methylation Profile ◽  
Poorly Differentiated ◽  
Prognostic Implications ◽  
Aberrant Dna Methylation ◽  
Worse Prognosis

Background: Poorly differentiated sinonasal carcinomas (PDSNCs) are rare and aggressive malignancies, which include squamous cell carcinoma (SCC), sinonasal undifferentiated carcinoma (SNUC), and neuroendocrine carcinomas (NEC). Several epigenetic markers have been suggested to support the histopathological classification, predict prognosis, and guide therapeutic decision. Indeed, molecularly distinct subtypes of sinonasal carcinomas, including SMARCB1-INI1 or SMARCA4 deficient sinonasal carcinoma, isocitrate dehydrogenase (IDH)-mutant SNUC, ARID1A mutant PDSNCs, and NUT carcinomas, have recently been proposed as separate entities. Identification of aberrant DNA methylation levels associated with these specific epigenetic driver genes could be useful for prognostic and therapeutic purpose. Methods: Histopathological review and immunohistochemical study was performed on 53 PDSNCs. Molecular analysis included mutational profile by NGS, Sanger sequencing, and MLPA analyses, and global DNA methylation profile using LINE-1 bisulfite-PCR and pyrosequencing analysis. Results: Nine SWI/SNF complex defective cases and five IDH2 p.Arg172x cases were identified. A significant correlation between INI-1 or IDH2 defects and LINE-1 hypermethylation was observed (p = 0.002 and p = 0.032, respectively), which were associated with a worse prognosis (p = 0.007). Conclusions: Genetic and epigenetic characterization of PDSNCs should be performed to identify distinct prognostic entities, which deserved a tailored clinical treatment.

scholarly journals Distinct DNA methylation targets by aging and chronic inflammation: a pilot study using gastric mucosa infected with Helicobacter pylori

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Satoshi Yamashita ◽  
Sohachi Nanjo ◽  
Emil Rehnberg ◽  
Naoko Iida ◽  
Hideyuki Takeshima ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Helicobacter Pylori ◽  
Gastric Mucosa ◽  
Chronic Inflammation ◽  
Cpg Islands ◽  
Human Gastric Mucosa ◽  
Driver Genes ◽  
Age Related ◽  
A Genome ◽  
Aberrant Dna Methylation

Abstract Background Aberrant DNA methylation is induced by aging and chronic inflammation in normal tissues. The induction by inflammation is widely recognized as acceleration of age-related methylation. However, few studies addressed target genomic regions and the responsible factors in a genome-wide manner. Here, we analyzed methylation targets by aging and inflammation, taking advantage of the potent methylation induction in human gastric mucosa by Helicobacter pylori infection-triggered inflammation. Results DNA methylation microarray analysis of 482,421 CpG probes, grouped into 270,249 genomic blocks, revealed that high levels of methylation were induced in 44,461 (16.5%) genomic blocks by inflammation, even after correction of the influence of leukocyte infiltration. A total of 61.8% of the hypermethylation was acceleration of age-related methylation while 21.6% was specific to inflammation. Regions with H3K27me3 were frequently hypermethylated both by aging and inflammation. Basal methylation levels were essential for age-related hypermethylation while even regions with little basal methylation were hypermethylated by inflammation. When limited to promoter CpG islands, being a microRNA gene and high basal methylation levels strongly enhanced hypermethylation while H3K27me3 strongly enhanced inflammation-induced hypermethylation. Inflammation was capable of overriding active transcription. In young gastric mucosae, genes with high expression and frequent mutations in gastric cancers were more frequently methylated than in old ones. Conclusions Methylation by inflammation was not simple acceleration of age-related methylation. Targets of aberrant DNA methylation were different between young and old gastric mucosae, and driver genes were preferentially methylated in young gastric mucosa.

Aberrant DNA methylation profile of hepatitis B virus infection

2018 ◽  
Vol 91 (1) ◽  
pp. 81-92 ◽  
Author(s):  
Jinglan Jin ◽  
Hongqin Xu ◽  
Ruihong Wu ◽  
Junqi Niu ◽  
Shibo Li
Keyword(s):  
Dna Methylation ◽  
Hepatitis B Virus ◽  
Virus Infection ◽  
Hepatitis B ◽  
Methylation Profile ◽  
Hepatitis B Virus Infection ◽  
B Virus ◽  
Dna Methylation Profile ◽  
Aberrant Dna Methylation

scholarly journals Uncovering Driver DNA Methylation Events in Nonsmoking Early Stage Lung Adenocarcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Xindong Zhang ◽  
Lin Gao ◽  
Zhi-Ping Liu ◽  
Songwei Jia ◽  
Luonan Chen
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Methylation Data ◽  
Driver Genes ◽  
Differential Network Analysis ◽  
Differential Network ◽  
Aberrant Dna Methylation ◽  
Never Smokers

As smoking rates decrease, proportionally more cases with lung adenocarcinoma occur in never-smokers, while aberrant DNA methylation has been suggested to contribute to the tumorigenesis of lung adenocarcinoma. It is extremely difficult to distinguish which genes play key roles in tumorigenic processes via DNA methylation-mediated gene silencing from a large number of differentially methylated genes. By integrating gene expression and DNA methylation data, a pipeline combined with the differential network analysis is designed to uncover driver methylation genes and responsive modules, which demonstrate distinctive expressions and network topology in tumors with aberrant DNA methylation. Totally, 135 genes are recognized as candidate driver genes in early stage lung adenocarcinoma and top ranked 30 genes are recognized as driver methylation genes. Functional annotation and the differential network analysis indicate the roles of identified driver genes in tumorigenesis, while literature study reveals significant correlations of the top 30 genes with early stage lung adenocarcinoma in never-smokers. The analysis pipeline can also be employed in identification of driver epigenetic events for other cancers characterized by matched gene expression data and DNA methylation data.

Aberrant DNA methylation profile and frequent methylation ofKLK10andOXGR1genes in hepatocellular carcinoma

2009 ◽  
Vol 48 (12) ◽  
pp. 1057-1068 ◽  
Author(s):  
Chang-Yi Lu ◽  
Sen-Yung Hsieh ◽  
Yen-Jung Lu ◽  
Chi-Sheng Wu ◽  
Lih-Chyang Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Dna Methylation ◽  
Methylation Profile ◽  
Dna Methylation Profile ◽  
Aberrant Dna Methylation

scholarly journals Aberrant DNA methylation profile of hepatocellular carcinoma and surgically resected margin

2009 ◽  
Vol 100 (6) ◽  
pp. 996-1004 ◽  
Author(s):  
Cheng Lou ◽  
Zhi Du ◽  
Bin Yang ◽  
YingTang Gao ◽  
YiJun Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Dna Methylation ◽  
Methylation Profile ◽  
Dna Methylation Profile ◽  
Aberrant Dna Methylation ◽  
Resected Margin
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