Comparing the Molecular Biological Characteristics between Gastric Cancer and Atrial Fibrillation Based on mRNA Expression Profiles

2020 ◽  
Vol 10 (01) ◽  
pp. 1-14
Author(s):  
伟 曾
Keyword(s):  
Gastric Cancer ◽  
Atrial Fibrillation ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Biological Characteristics

scholarly journals A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer

2020 ◽  
Vol 10 ◽  
Author(s):  
Zuhua Chen ◽  
Bo Liu ◽  
Minxiao Yi ◽  
Hong Qiu ◽  
Xianglin Yuan
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
Dna Hypomethylation

PurposeThe exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC).MethodsThe mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.Results5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139–0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group.ConclusionWe construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.

scholarly journals Joint analysis of lncRNA m6A methylome and lncRNA/mRNA expression profiles in gastric cancer

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Zhi Lv ◽  
Liping Sun ◽  
Qian Xu ◽  
Chengzhong Xing ◽  
Yuan Yuan
Keyword(s):  
Gastric Cancer ◽  
Mrna Expression ◽  
Expression Analysis ◽  
Target Genes ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Joint Analysis ◽  
Gene Enrichment Analysis ◽  
Gene Enrichment

Abstract Background N6-methyladenosine (m6A) modification might be closely associated with the genesis and development of gastric cancer (GC). Currently, the evidence established by high-throughput assay for GC-related m6A patterns based on long non-coding RNAs (lncRNAs) remains limited. Here, a joint analysis of lncRNA m6A methylome and lncRNA/mRNA expression profiles in GC was performed to explore the regulatory roles of m6A modification in lncRNAs. Methods Three subjects with primary GC were enrolled in our study and paired sample was randomly selected from GC tissue and adjacent normal tissue for each case. Methylated RNA Immunoprecipitation NextGeneration Sequencing (MeRIP-Seq) and Microarray Gene Expression Profiling was subsequently performed. Then co-expression analysis and gene enrichment analysis were successively conducted. Results After data analysis, we identified 191 differentially m6A-methylated lncRNAs, 240 differentially expressed lncRNAs and 229 differentially expressed mRNAs in GC. Furthermore, four differentially m6A-methylated and expressed lncRNAs (dme-lncRNAs) were discovered including RASAL2-AS1, LINC00910, SNHG7 and LINC01105. Their potential target genes were explored by co-expression analysis. And gene enrichment analysis suggested that they might influence the cellular processes and biological behaviors involved in mitosis and cell cycle. The potential impacts of these targets on GC cells were further validated by CCLE database and literature review. Conclusions Four novel dme-lncRNAs were identified in GC, which might exert regulatory roles on GC cell proliferation. The present study would provide clues for the lncRNA m6A methylation-based research on GC epigenetic etiology and pathogenesis.

scholarly journals Significance of aquaporins’ expression in the prognosis of gastric cancer

2018 ◽  
Vol 38 (3) ◽  
Author(s):  
Saroj Thapa ◽  
Mandika Chetry ◽  
Kaiyu Huang ◽  
Yangpei Peng ◽  
Jinsheng Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Cancer Biomarker ◽  
Clinicopathological Features ◽  
Her2 Status ◽  
Aberrant Expression ◽  
Gastric Cancer Patients

Gastric carcinoma is one of the most lethal malignancy at present with leading cause of cancer-related deaths worldwide. Aquaporins (AQPs) are a family of small, integral membrane proteins, which have been evidenced to play a crucial role in cell migration and proliferation of different cancer cells including gastric cancers. However, the aberrant expression of specific AQPs and its correlation to detect predictive and prognostic significance in gastric cancer remains elusive. In the present study, we comprehensively explored immunohistochemistry based map of protein expression profiles in normal tissues, cancer and cell lines from publicly available Human Protein Atlas (HPA) database. Moreover, to improve our understanding of general gastric biology and guide to find novel predictive prognostic gastric cancer biomarker, we also retrieved ‘The Kaplan–Meier plotter’ (KM plotter) online database with specific AQPs mRNA to overall survival (OS) in different clinicopathological features. We revealed that ubiquitous expression of AQPs protein can be effective tools to generate gastric cancer biomarker. Furthermore, high level AQP3, AQP9, and AQP11 mRNA expression were correlated with better OS in all gastric patients, whereas AQP0, AQP1, AQP4, AQP5, AQP6, AQP8, and AQP10 mRNA expression were associated with poor OS. With regard to the clinicopathological features including Laurens classification, clinical stage, human epidermal growth factor receptor 2 (HER2) status, and different treatment strategy, we could illustrate significant role of individual AQP mRNA expression in the prognosis of gastric cancer patients. Thus, our results indicated that AQP’s protein and mRNA expression in gastric cancer patients provide effective role to predict prognosis and act as an essential agent to therapeutic strategy.

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