scholarly journals Identification of key genes related to macrophage infiltration in gastric cancer based on WGCNA

2020 ◽  
Author(s):  
Haiyan Chen ◽  
Cangang Zhang ◽  
Shuai Cao ◽  
Meng Cao ◽  
Nana Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Immune Cell ◽  
Accurate Diagnosis ◽  
Marker Genes ◽  
Hub Genes ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
New Strategy ◽  
Tumor Environment ◽  
Advanced Stages

Abstract Background: Gastric cancer (GC) is rampant around the world. Most of the GC cases are detected in advanced stages with poor prognosis. The identification of marker genes for early diagnosis is of great significance. Studying the tumor environment is helpful to acknowledge the process of tumorigenesis, development, and metastasis.Methods: In GEO, 22 kinds of immune cell infiltration were calculated by CIBERSORT. Macrophages were discovered remarkably infiltrated higher in GC compared with normal tissues. WGCNA was utilized to construct the network and then identify key modules and genes related to macrophages in TCGA.Results: Finally, 18 hub genes were verified. In the PPI bar chart, the top 3 genes were chosen as hub genes involved in most pathways. On the TIMER and THPA websites, it is verified that the expression levels of CYBB, CD86 and C3AR1 genes in tumor tissues were higher than those in normal tissues.Conclusion: These genes may work as biomarkers or targets for accurate diagnosis and treatment of GC in the future. Our findings may be a new strategy for the treatment of GC.

scholarly journals Identification and Validation of CYBB, CD86, and C3AR1 as the Key Genes Related to Macrophage Infiltration of Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Haiyan Chen ◽  
Qi Sun ◽  
Cangang Zhang ◽  
Junjun She ◽  
Shuai Cao ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Gene Expression Omnibus ◽  
Marker Genes ◽  
Hub Genes ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
New Strategy ◽  
Tumor Environment ◽  
Advanced Stages ◽  
Geo Database

Gastric cancer (GC) is rampant around the world. Most of the GC cases are detected in advanced stages with poor prognosis. The identification of marker genes for early diagnosis is of great significance. Studying the tumor environment is helpful to acknowledge the process of tumorigenesis, development, and metastasis. Twenty-two kinds of immune cells were calculated by CIBERSORT from Gene Expression Omnibus (GEO) database. Subsequently, higher infiltration of macrophages M0 was discovered in GC compared with normal tissues. WGCNA was utilized to construct the network and then identify key modules and genes related to macrophages in TCGA. Finally, 18 hub genes were verified. In the PPI bar chart, the top 3 genes were chosen as hub genes involved in most pathways. On the TIMER and THPA websites, it is verified that the expression levels of CYBB, CD86, and C3AR1 genes in tumor tissues were higher than those in normal tissues. These genes may work as biomarkers or targets for accurate diagnosis and treatment of GC in the future. Our findings may be a new strategy for the treatment of GC.

scholarly journals CDCA3 Is a Novel Prognostic Biomarker Associated with Immune Infiltration in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Zhihuai Wang ◽  
Shuai Chen ◽  
Gaochao Wang ◽  
Sun Li ◽  
Xihu Qin
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Immune Cell ◽  
Disease Free Survival ◽  
In Silico Analysis ◽  
Gene Markers ◽  
Free Survival ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Tumor Tissues

Cell division cycle-associated protein-3 (CDCA3) contributes to the regulation of the cell cycle. CDCA3 plays an important role in the carcinogenesis of various cancers; however, the association between CDCA3 expression, prognosis of patients, and immune infiltration in the tumor microenvironment is still unknown. Here, we demonstrated that CDCA3 was differentially expressed between the tumor tissues and corresponding normal tissues using in silico analysis in the ONCOMINE and Tumor Immune Estimation Resource (TIMER) databases. We analyzed the relationship between the expression of CDCA3 and prognosis of patients with hepatocellular carcinoma (HCC) using the Kaplan–Meier plotter database and Gene Expression Profiling Interactive Analysis (GEPIA). Furthermore, we determined the prognostic value of CDCA3 expression using univariate and multivariate analyses. We observed that CDCA3 expression closely correlated with immune infiltration and gene markers of infiltrating immune cells in the TIMER database. CDCA3 was highly expressed in the tumor tissues than in the adjacent normal tissues in various cancers, including HCC. Increased expression of CDCA3 was accompanied by poorer overall survival (OS), relapse-free survival (RFS), progression-free survival (PFS), and disease-specific survival (DSS). The correlation between CDCA3 expression and OS and disease-free survival (DFS) was also studied using GEPIA. CDCA3 expression was associated with the levels of immune cell infiltration and was positively correlated with tumor purity. Moreover, CDCA3 expression was associated with gene markers such as PD-1, CTLA4, LAG3, and TIM-3 from exhausted T cells, CD3D, CD3E, and CD2 from T cells, and TGFB1 and CCR8 located on the surface of Tregs. Thus, we demonstrated that CDCA3 may be a potential target and biomarker for the management and diagnosis of HCC.

scholarly journals Immune Cell Landscape in Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yang Yang ◽  
Wei He ◽  
Zi-rui Wang ◽  
Yu-jiao Wang ◽  
Lan-lan Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
B Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Univariate Analysis ◽  
Molecular Therapy ◽  
Expression Level ◽  
Regulatory Factors ◽  
Normal Tissues ◽  
The Relationship

Background. The tumor-infiltrating immune cells are closely associated with the prognosis of gastric cancer (GC). This article is aimed at determining the composition change of immune cells and immune regulatory factors in GC and normal tissues, depicting their prognosis value in GC, and revealing the relationship between them and GC clinical parameters. Methods. We used CIBERSORT to calculate the proportion of 22 immune cells in the GC or normal tissues; a t -test was applied to assess the expression difference of immune cells and immune regulatory factors in normal and GC tissues. The relationship of the immune cells, immune regulatory factors, and GC patients’ clinical characteristics was assessed by univariate analysis. Results. In this study, we found that the proportion of macrophages increased, while plasma cells and monocytes decreased in GC tissues. In these immune fractions, Tregs and naïve B cells were found to be correlated with GC patients’ prognosis. Interestingly, the expression of immune regulatory factors was ambiguous with their classical function in GC tissues. For example, TIM-3, FOXP3, and CMTM6 were overexpressed, while CD27 and PD-1 were underexpressed in GC tissues. We also found that IDO1, PD-1, TIGIT, and TIM-3 were highly expressed in high-grade GC tissues, the HERC2 expression level was related to patients’ gender, and the TIGIT expression level was sensitive to targeted therapy. Furthermore, our results suggested that the infiltration of Tregs and naive B cells was strongly correlated with the T stage, radiation therapy, targeted molecular therapy, and the expression levels of TIM-3 and FOXP3 in GC. Conclusion. The expression pattern of tumor-infiltrating immune cells and immune regulatory factors was systematically depicted in the GC tumor microenvironment, indicating that individualized treatment based on the tumor-infiltrating immune cells and immune regulatory factors may be beneficial to GC patients.

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 Follistatin-like 1 (FSTL1) is a Prognostic Biomarker and Correlated with Immune Cell Infiltration in Gastric Cancer

2020 ◽  
Author(s):  
Li Li ◽  
Shanshan Huang ◽  
Yangyang Yao ◽  
Jun Chen ◽  
Junhe Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Tumor Immunity ◽  
Survival Data ◽  
Immune Cell ◽  
Bioinformatic Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Western Blot Assay ◽  
Immune Infiltration ◽  
Normal Tissues

Abstract Background: Follistatin-like 1 (FSTL1) plays a central role in the progression of tumor and tumor immunity. However, the effect of FSTL1 on the prognosis and immune infiltration of gastric cancer (GC) remains to be elucidated.Method: The expression of FSTL1 data was analyzed in Oncomine and TIMER databases. Analyses of clinical parameters and survival data were conducted by Kaplan-Meier plotter and immunohistochemistry. Western blot assay and real‐time quantitative PCR (RT-qPCR) was using to analyzed protein and mRNA expression, respectively. The correlations between FSTL1 and cancer immune infiltrates was analyzed by Tumor Immune Estimation Resource (TIME), Gene Expression Profiling Interactive Analysis (GEPIA) and LinkedOmics database.Results: The expression of FSTL1 was significantly higher in GC tissues than in normal tissues, and bioinformatic analysis and Immunohistochemistry (IHC) indicated that high FSTL1 expression significantly correlated with poor prognosis in GC. Moreover, FSTL1 was predicted as an independent prognostic factor in GC patients. Bioinformatics analysis results suggested that FSTL1 mainly involved in tumor progression and tumor immunity. And significant correlations were found between FSTL1 expression and immune cell infiltration in GC.Conclusion: The study effectively revealed useful information about FSTL1 expression, prognostic values, potential functional networks and impact of tumor immune infiltration in GC. In summary, FSTL1 can be used as a biomarker for prognosis and evaluating immune cell infiltration in GC.

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 Identification of the hub genes and prognostic indicators of gastric cancer and correlation of indicators with tumor-infiltrating immune cell levels

2021 ◽  
Vol 12 (13) ◽  
pp. 4025-4038
Author(s):  
Yun Ji ◽  
Lu Gao ◽  
Can Zhang ◽  
Xu Sun ◽  
Liping Dai ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Immune Cell ◽  
Prognostic Indicators ◽  
Hub Genes

scholarly journals Dissecting the Single-Cell Transcriptome Network in Superficial/Deep Tumor Tissues of Diffuse Gastric Cancer

2021 ◽  
Author(s):  
Yili Ren ◽  
Beibei Zhang ◽  
Chenkai Xu ◽  
Lei Zhang
Keyword(s):  
Gastric Cancer ◽  
Survival Analysis ◽  
Single Cell ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Cell Subpopulation ◽  
Diffuse Gastric Cancer ◽  
Normal Tissues ◽  
Tumor Tissues

Abstract Background and purpose: Gastric cancer is a type of highly heterogeneous malignant tumor and the prognosis of gastric cancer is hard to be improved due to limited knowledge on the molecular mechanism of heterogeneity. Single-cell sequencing technology is recently widely used for the investigation of both inter-tumoral heterogeneity and intra-tumoral heterogeneity. The present study aims to explore the potential oncogene by analyzing the single-cell data in the GSE167297 dataset.Methods: The GSE167297 dataset was downloaded from the GEO database, followed by quality control to remove data with lower quality. The division on cell subtypes was determined by the characteristic marker expressed in each cell subpopulation. Wilcoxon rank-sum test was used to screen out differentially expressed genes. Survival analysis was performed to evaluate the prognostic value of G-protein subunit g 11 (GNG11) gene which was significantly overexpressed in deep tumor tissues of diffuse gastric cancer.Results: In both normal tissues and tumor tissues, subtypes of immune cells and stromal cells were identified, with a higher proportion of infiltrated macrophages observed in deep tumor tissues. EPCAM was found significantly highly expressed in a cell subpopulation from gastric tumor tissues. 515 differentially expressed genes (| log2FC | > 2 and FDR < 1e-5) were screened out between normal tissues and tumor tissues. 86 differentially expressed genes (| log2FC | > 1 and FDR < 0.01) were screened out between superficial and deep tumor tissues, in which GNG11 was most highly expressed in deep tumor tissues (mean expression value: 0.1247, FC value: 52.2109). Disease-specific survival analysis on GNG11 results showed that the HR [95%CI] in the constructed univariate Cox proportional risk model was 4.419 [1.399-13.96] and the P-value in the log-rank test was 0.0056.Conclusion: Differentially expression profiles were provided both extratumorally and intratumorally, indicating a higher infiltration of macrophages in deep tumor tissues. Additionally,GNG11 was screened out to be a significant risk factor in STAD patients.

scholarly journals Identification of Potential Biomarkers and Therapy Targets involved in Gastric Cancer Using Bioinformatics Analysis

2021 ◽  
Author(s):  
YangYang Teng ◽  
Na Shan ◽  
GuangRong Lu ◽  
LeYi Ni ◽  
ZeJun Gao ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Bioinformatics Analysis ◽  
Risk Model ◽  
Malignant Tumors ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Normal Tissues ◽  
Therapy Targets ◽  
Selection Operator ◽  
Cancer Tissues

Abstract Gastric cancer remains one of the five major malignant tumors in the world, posing a great threat to public life and health. As gene sequencing technology develops, it is urgent to find out specific molecular markers for cancer therapy. In this study, datasets of GSE13911, GSE30727, GSE63089 and GSE118916 were investigated by bioinformatics analysis, and differentially expressed genes (DEGs) between GC tissues and normal tissues were screened for potential cancer therapeutic targets. Furthermore, the GSE63089 dataset was analyzed by Weighted Gene Co-expression Network Analysis (WGCNA), and the highly related genes were clustered. Then, the hub genes were searched using co-expression network and Molecular Complex Detection (MCODE) plug-in from Cytoscape software. Finally, ASPM, COL11A1 and CDC20 were obtained by intersection of hub genes and DEGs. The expressions of ASPM, COL11A1 and CDC20 gene in gastric cancer tissues and normal tissues from TCGA database were detected. For these genes, the least absolute shrink and selection operator (LASSO) Cox expression analysis was used to establish the prognostic risk model. COL11A1 and CDC20 genes were identified as candidate prognostic risk markers for GC. Analysis using qRT-PCR has shown that COL11A1 and CDC20 were significant differentially expressed between gastric cancer tissues and normal gastric tissues (P < 0.01). In conclusion, our study identifies specific DEGs involved in ECM process and metabolism by cytochrome P450 process, and these DEGs may be potential targets for GC therapy. The model constructed by COL11A1 and CDC20 genes can predict the prognosis risk of GC patients. Taken together, these findings provide reference for further analyses of key alterations during GC progression.

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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