scholarly journals Systematic Identification of Key Functional Modules and Genes in Gastric Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Rui Wu ◽  
Jin-Yu Sun ◽  
Li-Li Zhao ◽  
Zhi-Ning Fan ◽  
Cheng Yang
Keyword(s):  
Gastric Cancer ◽  
Cancer Metastasis ◽  
Immune Cell ◽  
Human Cancer ◽  
Differentially Expressed Gene ◽  
Hub Gene ◽  
Kaplan Meier ◽  
Incidence And Mortality ◽  
High Incidence ◽  
Systematic Identification

Gastric cancer (GC) is associated with high incidence and mortality rates worldwide. Differentially expressed gene (DEG) analysis and weighted gene coexpression network analysis (WGCNA) are important bioinformatic methods for screening core genes. In our study, DEG analysis and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the DEGs. SBNO2 was identified as the hub gene based on the intersection between the DEGs and the purple module in WGCNA. The expression and prognostic value of SBNO2 were verified in UALCAN, GEPIA2, Human Cancer Metastasis Database, Kaplan–Meier plotter, and TIMER. We identified 1974 DEGs, and 28 modules were uncovered via WGCNA. The purple module was identified as the hub module in WGCNA. SBNO2 was identified as the hub gene, which was upregulated in tumour tissues. Moreover, patients with GC and higher SBNO2 expression had worse prognoses. In addition, SBNO2 was suggested to play an important role in immune cell infiltration. In summary, based on DEGs and key modules related to GC, we identified SBNO2 as a hub gene, thereby offering novel insights into the development and treatment of GC.

scholarly journals Systematic identification of key functional modules and genes in esophageal cancer

2021 ◽  
Author(s):  
Rui Wu ◽  
Hao Zhuang ◽  
Yu-kun Mei ◽  
Jin-yu Sun ◽  
Tao Dong ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Immune Cell ◽  
Hub Gene ◽  
Kaplan Meier ◽  
Incidence And Mortality ◽  
Differential Expression Genes ◽  
High Incidence ◽  
Systematic Identification ◽  
Kaplan Meier Plotter ◽  
Core Genes

Abstract Background Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods.Methods The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan–Meier plotter, and TIMER databases.Results We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 ‘might not play an important role in immune cell infiltration.Conclusion Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer.

scholarly journals Systematic Identification of Key Functional Modules and Genes in Esophageal Cancer

2020 ◽  
Author(s):  
Rui Wu ◽  
Hao Zhuang ◽  
Jin-yu Sun ◽  
Li-li Zhao ◽  
Li Liu ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Immune Cell ◽  
Hub Gene ◽  
Kaplan Meier ◽  
Incidence And Mortality ◽  
Differential Expression Genes ◽  
High Incidence ◽  
Systematic Identification ◽  
Kaplan Meier Plotter ◽  
Core Genes

Abstract Background: Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods.Methods: The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan–Meier plotter, and TIMER databases.Results: We identified 1,044 DEGs form dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed worse prognosis. However, CCNB1 doesn’t play an important role in immune cell infiltration.Conclusion Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer.

scholarly journals Systematic identification of key functional modules and genes in esophageal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rui Wu ◽  
Hao Zhuang ◽  
Yu-Kun Mei ◽  
Jin-Yu Sun ◽  
Tao Dong ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Immune Cell ◽  
Hub Gene ◽  
Kaplan Meier ◽  
Incidence And Mortality ◽  
Differential Expression Genes ◽  
High Incidence ◽  
Systematic Identification ◽  
Kaplan Meier Plotter ◽  
Core Genes

Abstract Background Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods. Methods The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan–Meier plotter, and TIMER databases. Results We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 ‘might not play an important role in immune cell infiltration. Conclusions Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer.

DEPDC1 upregulation promotes cell proliferation and predicts poor prognosis in patients with gastric cancer

2020 ◽  
pp. 1-9
Author(s):  
Zhaohua Gong ◽  
Hongjin Chu ◽  
Jian Chen ◽  
Lixin Jiang ◽  
Benjiao Gong ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Gastric Adenocarcinoma ◽  
Cancer Metastasis ◽  
Human Cancer ◽  
Mrna Level ◽  
Tumor Development ◽  
Kaplan Meier

BACKGROUND: Previous studies revealed that DEP domain containing 1 (DEPDC1) is involved in the carcinogenesis and progression of several types of human cancer. However the role of DEPDC1 in gastric cancer has not been studied. OBJECTIVE: The objective of this study was to study the expression and pathophysiological function of DEPDC1 in gastric cancer. METHODS: DEPDC1 expression in gastric adenocarcinoma cells was examined with Western blot and qRT-PCR. Clinical pathological features of patients were determined by immunohistochemistry. The effect of DEPDC1 expression on cell proliferation was studied by in vitro cell proliferation assay; and cell cycle influence was assessed by ow cytometry. Survival curves were plotted using Kaplan-Meier. RESULTS: DEPDC1 was overexpressed in gastric adenocarcinoma tissues compared with the paired adjacent normal gastric tissues, in accordance with mRNA level downloaded from GEPIA database. DEPDC1 expression level was significantly associated with cancer metastasis and differentiation. DEPDC1 upregulation caused cell cycle accelerating from G1 to S phase, and it was correlated with poorer overall survival. CONCLUSION: Therefore, DEPDC1 upregulation in gastric adenocarcinoma is associated with tumor development and poor clinical outcomes of the patients, implying DEPDC1 might be a potential therapeutic target against gastric cancer.

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 High-Throughput Sequencing of miRNAs Reveals a Tissue Signature in Gastric Cancer and Suggests Novel Potential Biomarkers

2015 ◽  
Vol 9s1 ◽  
pp. BBI.S23773 ◽  
Author(s):  
Sylvain Darnet ◽  
Fabiano C Moreira ◽  
Igor G Hamoy ◽  
Rommel Burbano ◽  
André Khayat ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Gastric Adenocarcinoma ◽  
High Throughput Sequencing ◽  
Therapeutic Targets ◽  
Chain Reaction ◽  
Incidence And Mortality ◽  
High Incidence ◽  
Small Set ◽  
Polymerase Chain ◽  
Mirnas Expression

Gastric cancer has a high incidence and mortality rate worldwide; however, the use of biomarkers for its clinical diagnosis remains limited. The microRNAs (miRNAs) are biomarkers with the potential to identify the risk and prognosis as well as therapeutic targets. We performed the ultradeep miRnomes sequencing of gastric adenocarcinoma and gastric antrum without tumor samples. We observed that a small set of those samples were responsible for approximately 80% of the total miRNAs expression, which might represent a miRNA tissue signature. Additionally, we identified seven miRNAs exhibiting significant differences, and, of these, hsa-miR-135b and hsa-miR-29c were able to discriminate antrum without tumor from gastric cancer regardless of the histological type. These findings were validated by quantitative real-time polymerase chain reaction. The results revealed that hsa-miR-135b and hsa-miR-29c are potential gastric adenocarcinoma occurrence biomarkers with the ability to identify individuals at a higher risk of developing this cancer, and could even be used as therapeutic targets to allow individualized clinical management.

scholarly journals CXCR4 negatively correlates with NKT cell infiltration during gastric precancerous lesions progression to early gastric cancer

2020 ◽  
Author(s):  
Xiaotao Jiang ◽  
Kunhai Zhuang ◽  
Kailin Jiang ◽  
Yi Wen ◽  
Linling Xie ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Precancerous Lesions ◽  
Clinical Information ◽  
Cell Infiltration ◽  
Hub Genes ◽  
Nkt Cell ◽  
Hub Gene ◽  
Correlation Test

Abstract Background: With the coming of immunotherapy era, immunotherapy is gradually playing a vital role in the treatment of gastric cancer (GC). However, immune microenvironment in gastric precancerous lesions (GPL) and early gastric cancer (EGC) still remain largely unknown. Methods: From the Gene Expression Omnibus (GEO), data of three GPL-related gene expression profiles (GSE55696, GSE87666 and GSE130823) and three GC data sets with clinical information (GSE66229, GSE15459 and GSE34942) were downloaded. Three GC data were consolidated as a GC meta-GEO cohort. RNA sequencing data of 375 stomach adenocarcinoma (STAD) samples with clinical information from The Cancer Genome Atlas (TCGA) and 175 stomach normal controls (NC) from Genotype-Tissue Expression (GTEx) datasets were obtained from the UCSC Xena browser, which were merged as a STAD TCGA-GTEx cohort. The abundance of immune cells in above datasets were estimated using Immune Cell Abundance Identifier (ImmuCellAI) algorithm. Firstly, key immune cells associated with GPL progression to EGC were identified using one‐way analysis of variance (ANOVA) test as well as Spearman’s correlation test in two GPL and EGC related datasets (GSE55696 and GSE87666). Then, weighted gene co-expression analysis (WGCNA) and pathway enrichment were adopted to identify hub gene co-expression network. Candidate hub genes were identified based on network parameters. Combining expression comparison and prognosis analysis in STAD TCGA-GTEx and GC meta-GEO cohort, Genes with significant difference between GC and NC and prognostic significance were identified as real hub genes. Correlation between real hub genes and key immune cells was evaluated using Pearson’s correlation test. The pattern of key immune cells infiltration and hub genes expression as well as their correlation during GPL progression to EGC were validated in an independent cohort GSE130823. The correlation was also verified in the GC datasets (STAD TCGA-GTEx and GC meta-GEO cohort).Results: Combining with GSE55696 and GSE87666 cohorts, NKT cell was found gradually decreased with GPL progression and negatively correlated with tumorigenesis significantly. It was identified as the key immune cell associated with GPL progression to EGC based on one-way ANOVA test and Spearman’s correlation test. Further verification indicated that it was significantly downregulated in GC in meta-GEO cohort and STAD TCGA-GTEx cohort. According to the results of WGCNA and KEGG pathway enrichment, green modules in GSE55696 and GSE87666 cohorts were considered as hub modules as they were negatively associated with NKT cell infiltration at a significant level and their overlapping genes were significantly enriched in immune-related pathways. In further screening, CXCR4 was found to be significantly upregulated in GC and had a poor prognosis, which was determined as the real hub gene. CXCR4 expression was found increased with GPL progression, positively correlated with tumorigenesis and negatively correlated with NKT cell infiltration significantly. The pattern of NKT cell infiltration and CXCR4 expression as well as their relationship stay consistent in the independent GPL cohort GSE130823. The negative correlation of CXCR4 with NKT cell infiltration was also confirmed in GC datasets (GC meta-GEO cohort and STAD TCGA-GTEx cohort).Conclusion: CXCR4 and NKT cell are possible to serve as biomarkers in monitoring GPL progression to EGC. Besides, CXCR4 may be involved in regulating NKT cell infiltration during GPL progression to EGC, which may provide a new immunotherapeutic target.

scholarly journals CXCR4 Negatively Correlates with NKT Cell Infiltration During Gastric Precancerous Lesions Progression to Early Gastric Cancer

2020 ◽  
Author(s):  
Xiaotao Jiang ◽  
Kunhai Zhuang ◽  
Kailin Jiang ◽  
Yi Wen ◽  
Linling Xie ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Gastric Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Precancerous Lesions ◽  
Expression Profiles ◽  
Cell Infiltration ◽  
Hub Genes ◽  
Nkt Cell ◽  
Hub Gene

Abstract Background Immune microenvironment in gastric precancerous lesions (GPL) and early gastric cancer (EGC) still remain largely unknown. This study aims to identify key immune cells and hub genes associated with GPL progression to EGC. Methods Immune Cell Abundance Identifier (ImmuCellAI) algorithm was used to quantify the proportions of immune cells of GPL and GC samples based on gene expression profiles. Key immune cells associated with GPL progression to EGC were identified using one‐way analysis of variance (ANOVA) test and Spearman’s correlation test. Weighted gene co-expression analysis (WGCNA) and pathway enrichment were adopted to identify hub gene co-expression network and hub genes associated with the key immune cells infiltration. The pattern of key immune cells infiltration, hub genes expression and their correlation were verified in an independent GPL-EGC cohort and GC datasets.Results NKT cell was found gradually decreased during GPL progression to EGC and negatively correlated with tumorigenesis. According to WGCNA and hub genes screening, CXCR4, having a poor prognosis, increased with GPL progression, positively correlated with tumorigenesis and negatively correlated with NKT cell infiltration significantly, was identified as the real hub gene. The negative correlation between CXCR4 and NKT cell infiltration was successfully verified in an independent GPL-EGC cohort and GC datasets.Conclusion CXCR4 and NKT cell are possible to serve as biomarkers in monitoring GPL progression to EGC. Besides, CXCR4 may be involved in regulating NKT cell infiltration during GPL progression to EGC, which may provide a new immunotherapeutic target.

scholarly journals Evaluation of serum markers for gastric cancer and its precursor diseases among high incidence and mortality rate of gastric cancer area

2018 ◽  
Vol 22 (1) ◽  
pp. 104-112 ◽  
Author(s):  
Boldbaatar Gantuya ◽  
Khasag Oyuntsetseg ◽  
Dashdorj Bolor ◽  
Yansan Erdene-Ochir ◽  
Ruvjir Sanduijav ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Mortality Rate ◽  
Serum Markers ◽  
Incidence And Mortality ◽  
High Incidence

scholarly journals Identification CXCL9 is a Potential Prognostic Biomarker in Ovarian and Gastric Cancer and is Correlated with Immune Infiltrates

2021 ◽  
Author(s):  
Tinghui Wu ◽  
Yongchao Li ◽  
Shujuan Gong ◽  
Ruijun Shi ◽  
Hangzheng Zhou ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Dendritic Cells ◽  
Immune Cell ◽  
Mrna Level ◽  
Progression Free Survival ◽  
Cytotoxic Lymphocytes ◽  
Poor Overall Survival ◽  
Normal Tissues ◽  
Microarray Database ◽  
Kaplan Meier

Abstract Background CXCL9 also known as an interferon gamma-inducible chemokine that belonging to the CXC chemokine family. It plays a role in promoting chemotaxis, inducing leukocyte differentiation and multiplication, and triggering tissue extravasation. Methods The TIMER (Tumor Immune Estimation Resource) and cancer microarray database Oncomine were used to dig at CXCL9 expression. The clinic prognostic level of CXCL9 was evaluated via Kaplan-Meier plotter. Then, Using TIMER and GEPIA, we investigated whether CXCL9 expression impacted cancer immune infiltrates. Results CXCL9 expression has been found to be significantly lower in ovarian and gastric cancers relative to normal tissues. In patients with ovarian cancer (OS HR = 0.78, P = 0.0017; PFS HR = 0.85, R = 0.015) and gastric cancer (OS HR = 0.55, P = 1.1e-08; PFS HR = 0.58, R = 7.6e-07), low CXCL9 expression was correlation to PFS (progression-free survival) and OS (poor overall survival). Furthermore, in OV and GC, CXCL9 was shown to have a close interaction with tumor-infiltrating immunity cells (B cells, CD4 + and CD8 + T cells, macrophages, neutrophils, and dendritic cells). CXCL9 expression, on the other hand, was shown to be closely related to several immune markers. Conclusion In OV and GC, CXCL9 mRNA level is strongly associated with prognosis and levels of penetration tumor-infiltrating immunity cell. The CXCL9 expression may also play a role in controlling TAMs (tumor-associated macrophages), DCs (Dendritic cells), CTLs (cytotoxic lymphocytes), and NK (natural killer) cells in OV and GC. CXCL9 may be seen as an independent marker that assesses the prognosis in OV and GC patients. Besides, CXCL9 expression level also can assess the immune cell subtypes of tumor microenvironment in OV and GC.

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