scholarly journals Identification of core genes and outcome in gastric cancer using bioinformatics analysis

Oncotarget ◽  
2017 ◽  
Vol 8 (41) ◽  
pp. 70271-70280 ◽  
Author(s):  
Chenhua Sun ◽  
Qi Yuan ◽  
Dongdong Wu ◽  
Xiaohu Meng ◽  
Baolin Wang
Keyword(s):  
Gastric Cancer ◽  
Bioinformatics Analysis ◽  
Core Genes

scholarly journals Identification of potential core genes in gastric cancer using bioinformatics analysis

2021 ◽  
Vol 0 (0) ◽  
pp. 2109-2122
Author(s):  
Changjiang Shao ◽  
Rong Wang ◽  
Dandan Kong ◽  
Qian Gao ◽  
Chunfang Xu
Keyword(s):  
Gastric Cancer ◽  
Bioinformatics Analysis ◽  
Potential Core ◽  
Core Genes

scholarly journals Identification of core genes and clinical outcomes in tumors originated from endoderm (gastric cancer and lung carcinoma) via bioinformatics analysis

Medicine ◽  
2021 ◽  
Vol 100 (12) ◽  
pp. e25154
Author(s):  
Yewen Shi ◽  
Dongmin Chang ◽  
Wenhan Li ◽  
FengYu Zhao ◽  
Xiaoyong Ren ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Clinical Outcomes ◽  
Lung Carcinoma ◽  
Bioinformatics Analysis ◽  
Core Genes

Bioinformatics Analysis Identifies CPZ as a Tumor Immunology Biomarker For Gastric Cancer

2020 ◽  
Vol 15 ◽  
Author(s):  
Yuan Gu ◽  
Ying Gao ◽  
Xiaodan Tang ◽  
Huizhong Xia ◽  
Kunhe Shi
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Signaling Pathway ◽  
Tumor Immunology ◽  
Bioinformatics Analysis ◽  
Human Cancer ◽  
Disease Free Survival ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Pathway Regulation

Background: Gastric cancer (GC) is one of the most common malignancies worldwide. However, the biomarkers for the prognosis and diagnosis of Gastric cancer were still need. Objective: The present study aimed to evaluate whether CPZ could be a potential biomarker for GC. Method: Kaplan-Meier plotter (http://kmplot.com/analysis/) was used to determine the correlation between CPZ expression and overall survival (OS) and disease-free survival (DFS) time in GC [9]. We analyzed CPZ expression in different types of cancer and the correlation of CPZ expression with the abundance of immune infiltrates, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells, via gene modules using TIMER Database. Results: The present study identified that CPZ was overexpressed in multiple types of human cancer, including Gastric cancer. We found that overexpression of CPZ correlates to the poor prognosis of patients with STAD. Furthermore, our analyses show that immune infiltration levels and diverse immune marker sets are correlated with levels of CPZ expression in STAD. Bioinformatics analysis revealed that CPZ was involved in regulating multiple pathways, including PI3K-Akt signaling pathway, cGMP-PKG signaling pathway, Rap1 signaling pathway, TGF-beta signaling pathway, regulation of cell adhesion, extracellular matrix organization, collagen fibril organization, collagen catabolic process. Conclusion: This study for the first time provides useful information to understand the potential roles of CPZ in tumor immunology and validate it to be a potential biomarker for GC.

scholarly journals The meta and bioinformatics analysis of GRP78 expression in gastric cancer

Oncotarget ◽  
2017 ◽  
Vol 8 (42) ◽  
pp. 73017-73028 ◽  
Author(s):  
Hua-Chuan Zheng ◽  
Bao-Cheng Gong ◽  
Shuang Zhao
Keyword(s):  
Gastric Cancer ◽  
Bioinformatics Analysis

scholarly journals Bioinformatics analysis of the prognosis and biological significance of VCAN in gastric cancer

2021 ◽  
Author(s):  
Xiao‐yan Huang ◽  
Jin‐jian Liu ◽  
Xiong Liu ◽  
Yao‐hui Wang ◽  
Wei Xiang
Keyword(s):  
Gastric Cancer ◽  
Bioinformatics Analysis ◽  
Biological Significance

scholarly journals Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Gu ◽  
Ying Sun ◽  
Xiong Zheng ◽  
Jin Ma ◽  
Xiao-Ying Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Microarray Analysis ◽  
Cancer Progression ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Circular Rnas ◽  
Target Mrnas

Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar’s home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network.

Identification of core genes and potential molecular mechanisms in breast cancer using bioinformatics analysis

2019 ◽  
Vol 215 (7) ◽  
pp. 152436 ◽  
Author(s):  
Fei Liu ◽  
Yunyan Wu ◽  
Yunzhe Mi ◽  
Lina Gu ◽  
Meixiang Sang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Core Genes

scholarly journals Joint bioinformatics analysis of underlying potential functions of hsa-let-7b-5p and core genes in human glioma

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Xiaonan Xi ◽  
Yahui Chu ◽  
Ning Liu ◽  
Qianqian Wang ◽  
Zheng Yin ◽  
...  
Keyword(s):  
Bioinformatics Analysis ◽  
Potential Functions ◽  
Human Glioma ◽  
Core Genes
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