EBV and HP Infections in Gastric Cancer Tissues and Their Correlation with HER2, P53, Ki-67 Gene Expression

2021 ◽  
Vol 11 (02) ◽  
pp. 48-58
Author(s):  
杨 江
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Ki 67 ◽  
Cancer Tissues

scholarly journals The Antioxidant Alpha-Lipoic Acid Inhibits Proliferation and Invasion of Human Gastric Cancer Cells via Suppression of STAT3-Mediated MUC4 Gene Expression

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yu Yang ◽  
Erhu Fang ◽  
Jiajun Luo ◽  
Hongxue Wu ◽  
Yue Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Cancer Cells ◽  
Human Gastric Cancer ◽  
Alpha Lipoic Acid ◽  
Gastric Cancer Cells ◽  
Muc4 Expression ◽  
Cancer Tissues ◽  
Muc4 Gene ◽  
Proliferation And Invasion

Background. Metastasis and invasion are the main causes of mortality in gastric cancer. To improve the treatment of gastric cancer, the development of effective and innovative antitumor agents toward invasion and proliferation is needed. Alpha-lipoic acid (ALA), a naturally occurring thiol antioxidant, showed antiproliferative and cytotoxic effects on several cancers. So it is feasible to explore whether ALA can be used to inhibit proliferation and invasion in human gastric cancer. Methods. The expression of MUC4 in human gastric cancer tissues was assayed by immunohistochemistry. Then, we performed in vitro cell proliferation and invasion analysis to explore the antitumor effect of ALA using AGS, BGC-823, and MKN-28 cells. To further explore the mechanism of ALA-mediated downregulation of MUC4, we cotransfected human gastric cancer cells with STAT3 siRNA and STAT3 overexpression construct. ChIP assays were carried out to find the relationship between MUC4 and STAT3. Results. We found that the MUC4 gene was strongly expressed in human gastric cancer tissues. Meanwhile, ALA reduced proliferation and invasion of human gastric cancer cells by suppressing MUC4 expression. We also found that STAT3 was involved in the inhibition of MUC4 by ALA. Mechanistically, ALA suppressed MUC4 expression by inhibiting STAT3 binding to the MUC4 promoter region. Conclusion. ALA inhibits both proliferation and invasion of gastric cancer cells by suppression of STAT3-mediated MUC4 gene expression.

scholarly journals The Gene Expression Status of the PI3K/AKT/mTOR Pathway in Gastric Cancer Tissues and Cell Lines

2016 ◽  
Vol 22 (4) ◽  
pp. 797-805 ◽  
Author(s):  
Ismael Riquelme ◽  
Oscar Tapia ◽  
Jaime A. Espinoza ◽  
Pamela Leal ◽  
Kurt Buchegger ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Cell Lines ◽  
Mtor Pathway ◽  
Cancer Tissues ◽  
Expression Status

Ultrastructural Cytochemical Study of Human Gastric Cancer: Observation of AKP ase,ACP ase,G6P ase,TPP ase and CO ase

1990 ◽  
Vol 48 (3) ◽  
pp. 254-255
Author(s):  
Dong Yuming ◽  
Yang Guanglin ◽  
Du Wei Dong ◽  
Xu Ai Liam
Keyword(s):  
Gastric Cancer ◽  
Gastric Epithelium ◽  
Human Gastric Cancer ◽  
Electron Microscopic ◽  
Cytochemical Study ◽  
Electron Microscopic Cytochemistry ◽  
Cytochemical Reaction ◽  
Set Up ◽  
Cancer Tissues ◽  
Cytochemical Technique

The activities and distributions of AKPase ,ACPase,G6Pase,TPPase and COase in human normal gastric mucosa and gastric cancer tissues were studied histochemically at light microscopic level. These enzymes are the marker enzymes of cell membrane lysosome endoplasmic reticulum, Golgi apparatus and mitochondrion objectively. On the basis of the research we set up a special ultrastructural cytochemical technique and first researched into gastric cancer domesticly. Ultrastructural cytochemistry is also called electron microscopic cytochemistry. This new technique possesses both the sensitivity of cytochemical reaction andi the high resolution of electron microscope. It is characterized by direct observation,exact localization and the combination morphology with function.The distributions of AKPase,ACPase,G6Pase,TPPase and COase in 14 cases of gastric cancer and 1 case of gastric Denign lesion were studied ultrastructurally. The results showed: 1. normal gastric epithelium had no AKPase reaction. The reaction of ACPase,G6Pase,TPPase and Coase were found in the corresponding organella, which were consistent with their function.

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 A novel prognostic model based on epithelial-mesenchymal transition-related genes predicts patient survival in gastric cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wanting Song ◽  
Yi Bai ◽  
Jialin Zhu ◽  
Fanxin Zeng ◽  
Chunmeng Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Risk Model ◽  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Critical Function ◽  
Mesenchymal Transition ◽  
Patient Prognosis

Abstract Background Gastric cancer (GC) represents a major malignancy and is the third deathliest cancer globally. Several lines of evidence indicate that the epithelial-mesenchymal transition (EMT) has a critical function in the development of gastric cancer. Although plentiful molecular biomarkers have been identified, a precise risk model is still necessary to help doctors determine patient prognosis in GC. Methods Gene expression data and clinical information for GC were acquired from The Cancer Genome Atlas (TCGA) database and 200 EMT-related genes (ERGs) from the Molecular Signatures Database (MSigDB). Then, ERGs correlated with patient prognosis in GC were assessed by univariable and multivariable Cox regression analyses. Next, a risk score formula was established for evaluating patient outcome in GC and validated by survival and ROC curves. In addition, Kaplan-Meier curves were generated to assess the associations of the clinicopathological data with prognosis. And a cohort from the Gene Expression Omnibus (GEO) database was used for validation. Results Six EMT-related genes, including CDH6, COL5A2, ITGAV, MATN3, PLOD2, and POSTN, were identified. Based on the risk model, GC patients were assigned to the high- and low-risk groups. The results revealed that the model had good performance in predicting patient prognosis in GC. Conclusions We constructed a prognosis risk model for GC. Then, we verified the performance of the model, which may help doctors predict patient prognosis.

scholarly journals Combining gene expression signature with clinical features for survival stratification of gastric cancer

Genomics ◽  
2021 ◽  
Author(s):  
Qiang Sun ◽  
Dongyang Guo ◽  
Shuang Li ◽  
Yanjun Xu ◽  
Mingchun Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Clinical Features ◽  
Gene Expression Signature ◽  
Expression Signature
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