scholarly journals Accumulation of DNA Methylation Changes in the Progression of Gastritis to Gastric Cancer

10.5772/53147 ◽  
2013 ◽  
Author(s):  
Zheming Lu ◽  
Dajun Deng
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation

Development and Validation of a Prognostic Nomogram for Gastric Cancer Based on DNA Methylation-Driven Genes

2019 ◽  
Author(s):  
Yi Bai ◽  
Chunlian Wei ◽  
Yuxin Zhong ◽  
Junyu Long ◽  
Shan Huang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Development And Validation

Magnesium-dependent Phosphatase (MDP) 1 is a Potential Suppressor of Gastric Cancer

2019 ◽  
Vol 19 (10) ◽  
pp. 817-827
Author(s):  
Jianbo Zhu ◽  
Lijuan Deng ◽  
Baozhen Chen ◽  
Wenqing Huang ◽  
Xiandong Lin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Cell Proliferation ◽  
Protein C ◽  
Biological Function ◽  
Prognostic Markers ◽  
Biological Effects ◽  
Signal Transducer ◽  
Gastric Cancer Cells ◽  
Transcription 3

Background:Recurrence is the leading cause of treatment failure and death in patients with gastric cancer (GC). However, the mechanism underlying GC recurrence remains unclear, and prognostic markers are still lacking.Methods:We analyzed DNA methylation profiles in gastric cancer cases with shorter survival (<1 year) or longer survival (> 3 years), and identified candidate genes associated with GC recurrence. Then, the biological effects of these genes on gastric cancer were studied.Results:A novel gene, magnesium-dependent phosphatase 1 (mdp1), was identified as a candidate gene whose DNA methylation was higher in GC samples from patients with shorter survival and lower in patients with longer survival. MDP1 protein was highly expressed in GC tissues with longer survival time, and also had a tendency to be expressed in highly differentiated GC samples. Forced expression of MDP1 in GC cell line BGC-823 inhibited cell proliferation, whereas the knockdown of MDP1 protein promoted cell growth. Overexpression of MDP1 in BGC-823 cells also enhanced cell senescence and apoptosis. Cytoplasmic kinase protein c-Jun N-terminal kinase (JNK) and signal transducer and activator of transcription 3 (Stat3) were found to mediate the biological function of MDP1.Conclusion:These results suggest that MDP1 protein suppresses the survival of gastric cancer cells and loss of MDP expression may benefit the recurrence of gastric cancer.

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

scholarly journals Differential regulation of LRRC37A2 in gastric cancer by DNA methylation

Epigenetics ◽  
2021 ◽  
pp. 1-7
Author(s):  
Fernanda Wisnieski ◽  
Jaqueline Cruz Geraldis ◽  
Leonardo Caires Santos ◽  
Mariana Ferreira Leal ◽  
Danielle Queiroz Calcagno ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Differential Regulation

scholarly journals Filtering high-dimensional methylation marks with extremely small sample size: an application to gastric cancer data

2021 ◽  
Author(s):  
Xin Chen ◽  
Qingrun Zhang ◽  
Thierry Chekouo
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Sample Size ◽  
Small Sample Size ◽  
Small Sample ◽  
Differential Methylation ◽  
High Dimensional ◽  
Cancer Data ◽  
Cancer Pathogenesis ◽  
A Genome

Abstract Background: DNA methylations in critical regions are highly involved in cancer pathogenesis and drug response. However, to identify causal methylations out of a large number of potential polymorphic DNA methylation sites is challenging. This high-dimensional data brings two obstacles: first, many established statistical models are not scalable to so many features; second, multiple-test and overfitting become serious. To this end, a method to quickly filter candidate sites to narrow down targets for downstream analyses is urgently needed. Methods: BACkPAy is a pre-screening Bayesian approach to detect biological meaningful clusters of potential differential methylation levels with small sample size. BACkPAy prioritizes potentially important biomarkers by the Bayesian false discovery rate (FDR) approach. It filters non-informative sites (i.e. non-differential) with flat methylation pattern levels accross experimental conditions. In this work, we applied BACkPAy to a genome-wide methylation dataset with 3 tissue types and each type contains 3 gastric cancer samples. We also applied LIMMA (Linear Models for Microarray and RNA-Seq Data) to compare its results with what we achieved by BACkPAy. Then, Cox proportional hazards regression models were utilized to visualize prognostics significant markers with The Cancer Genome Atlas (TCGA) data for survival analysis. Results: Using BACkPAy, we identified 8 biological meaningful clusters/groups of differential probes from the DNA methylation dataset. Using TCGA data, we also identified five prognostic genes (i.e. predictive to the progression of gastric cancer) that contain some differential methylation probes, whereas no significant results was identified using the Benjamin-Hochberg FDR in LIMMA. Conclusions: We showed the importance of using BACkPAy for the analysis of DNA methylation data with extremely small sample size in gastric cancer. We revealed that RDH13, CLDN11, TMTC1, UCHL1 and FOXP2 can serve as predictive biomarkers for gastric cancer treatment and the promoter methylation level of these five genes in serum could have prognostic and diagnostic functions in gastric cancer patients.

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