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

Background and Objective: Gastric cancer (GC) is an important health burden and the prognosis of GC is poor. We aimed to explore new diagnostic and prognostic indicators as well as potential therapeutic targets for GC in the current study.Methods: We screened the overlapped differentially expressed genes (DEGs) from GSE54129 and TCGA STAD datasets. Protein-protein interaction network analysis recognized the hub genes among the DEGs. The roles of these genes in diagnosis, prognosis, and their relationship with immune infiltrates and drug sensitivity of GC were analyzed using R studio. Finally, the clinically significant hub genes were verified using single-cell RNA sequencing (scRNA-seq) data.Results: A total of 222 overlapping genes were screened, which were enriched in extracellular matrix-related pathways. Further, 17 hub genes were identified, and our findings demonstrated that BGN, COMP, COL5A2, and SPARC might be important diagnostic and prognostic indicators of GC, which were also correlated with immune cell infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and sensitivity of therapeutic drugs. The scRNA-seq results further confirmed that all four hub genes were highly expressed in GC.Conclusion: Based on transcriptomics and single-cell sequencing, we identified four diagnostic and prognostic biomarkers of GC, including BGN, COMP, COL5A2, and SPARC, which can help predict drug sensitivity for GC as well.

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

10.21203/rs.3.rs-56342/v1 ◽

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.

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

10.21203/rs.3.rs-79316/v1 ◽

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.

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

10.21203/rs.3.rs-88936/v1 ◽

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.

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Comprehensive Analysis of circRNA-associated Competing Endogenous RNA Networks and Immune Infiltration in Gastric Cancer

10.21203/rs.3.rs-805632/v1 ◽

2021 ◽

Author(s):

beibei xu ◽

Endian Zheng ◽

Yi Huang ◽

Liang Zheng ◽

Qiaoli Lan ◽

...

Keyword(s):

Gastric Cancer ◽

T Cells ◽

Immune Cell ◽

Clinical Stage ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Hub Genes ◽

Qrt Pcr ◽

Ppi Networks

Abstract BackgroundCircular RNA (circRNA) has been shown to be an important regulator in gastric cancer (GC). However, functions and regulatory mechanisms of circRNA-related competitive endogenous RNA (ceRNA) in GC have not been established.MethodsCircRNA data and clinical data were downloaded from the GEO and TCGA databases. The ceRNA and Protein-Protein Interaction (PPI) networks were constructed through bioinformatics analysis. Function enrichment analysis was performed. Additionally, correlations between expression levels of the top 10 hub genes and immune cell infiltration levels, histopathological grade and clinical stage were determined to establish their clinical values. The differentially expressed circRNA (DEcircRNA) was validated by quantitative real-time PCR (qRT-PCR).ResultsScreening of the GEO and TCGA databases revealed a total of 1627 DEcircRNAs, 6516 DEmRNAs, and 1451 DEmiRNAs. The ceRNA interaction network contained 2 circRNAs, 3 miRNAs and 55 mRNAs. Meanwhile, Gene Ontology (GO) analysis revealed a total of 323 biological processes (BP) terms, 53 cellular components (CC) terms, 51 molecular functions (MF) terms, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed 4 signaling pathways. Gene Set Enrichment Analysis (GSEA) analysis revealed that EPHA4, NCAM1 and NRXN1 were positively correlated with the axon guidan and adhesion molecules pathways. Most of top 10 hub genes were positively correlated with B cells, CD8+ T cells, CD4+ T cells, Neutrophils and Dendritic Cell infiltration. Correlation analysis between hub genes and clinical phenotypes revealed that elevated expressions of EPHA4 and KCNA1 indicated poor tissue differentiation and were associated with clinically advanced stages of GC. The qRT-PCR results revealed that the expression of has_circ_0002504 was significantly down-regulated in 3 GC cell lines which was consistent with the results of our bioinformatics analysis.ConclusionsHas_circ_0001998 and has_circ_0002504 are potential diagnostic biomarkers for GC, and the high expressions of both EPHA4 and KCNA1 may predict poor prognosis.

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ADAMTS12 acts as a tumor microenvironment related cancer promoter in gastric cancer

Scientific Reports ◽

10.1038/s41598-021-90330-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yangming Hou ◽

Yingjuan Xu ◽

Dequan Wu

Keyword(s):

Gastric Cancer ◽

Tumor Microenvironment ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Tumor Promoter ◽

Protein Protein Interaction ◽

Oxidative Phosphorylation Pathway ◽

Cox Proportional Hazard Regression

AbstractThe infiltration degree of immune and stromal cells has been shown clinically significant in tumor microenvironment (TME). However, the utility of stromal and immune components in Gastric cancer (GC) has not been investigated in detail. In the present study, ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cell (TIC) in GC cohort, including 415 cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were screened by Cox proportional hazard regression analysis and protein–protein interaction (PPI) network construction. Then ADAMTS12 was regarded as one of the most predictive factors. Further analysis showed that ADAMTS12 expression was significantly higher in tumor samples and correlated with poor prognosis. Gene Set Enrichment Analysis (GSEA) indicated that in high ADAMTS12 expression group gene sets were mainly enriched in cancer and immune-related activities. In the low ADAMTS12 expression group, the genes were enriched in the oxidative phosphorylation pathway. CIBERSORT analysis for the proportion of TICs revealed that ADAMTS12 expression was positively correlated with Macrophages M0/M1/M2 and negatively correlated with T cells follicular helper. Therefore, ADAMTS12 might be a tumor promoter and responsible for TME status and tumor energy metabolic conversion.

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Bioinformatics analysis of DNMT1 expression and its role in head and neck squamous cell carcinoma prognosis

Scientific Reports ◽

10.1038/s41598-021-81971-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jili Cui ◽

Lian Zheng ◽

Yuanyuan Zhang ◽

Miaomiao Xue

Keyword(s):

Gene Expression ◽

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Immune Cell ◽

Neck Squamous Cell Carcinoma ◽

Hub Genes ◽

Significant Difference ◽

Dnmt1 Expression

AbstractHead and neck squamous cell carcinoma (HNSCC) is the sixth most common type of malignancy in the world. DNA cytosine-5-methyltransferase 1 (DNMT1) play key roles in carcinogenesis and regulation of the immune micro-environment, but the gene expression and the role of DNMT1 in HNSCC is unknown. In this study, we utilized online tools and databases for pan-cancer and HNSCC analysis of DNMT1 expression and its association with clinical cancer characteristics. We also identified genes that positively and negatively correlated with DNMT1 expression and identified eight hub genes based on protein–protein interaction (PPI) network analysis. Enrichment analyses were performed to explore the biological functions related with of DNMT1. The Tumor Immune Estimation Resource (TIMER) database was performed to explore the relationship between DNMT1 expression and immune-cell infiltration. We demonstrated that DNMT1 gene expression was upregulated in HNSCC and associated with poor prognosis. Based on analysis of the eight hub genes, we determined that DNMT1 may be involved in cell cycle, proliferation and metabolic related pathways. We also found that significant difference of B cells infiltration based on TP 53 mutation. These findings suggest that DNMT1 related epigenetic alterations have close relationship with HNSCC progression, and DNMT1 could be a novel diagnostic biomarker and a promising therapeutic target for HNSCC.

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Comprehensive Analysis of SFRP Family Members Prognostic Value and Immune Infiltration in Gastric Cancer

Life ◽

10.3390/life11060522 ◽

2021 ◽

Vol 11 (6) ◽

pp. 522

Author(s):

Dehua Liu ◽

Chenyu Sun ◽

Nahyun Kim ◽

Chandur Bhan ◽

John Pocholo Whitaker Tuason ◽

...

Keyword(s):

Gastric Cancer ◽

Wnt Signaling ◽

Signaling Pathway ◽

Prognostic Value ◽

Immune Cell ◽

System Development ◽

Wnt Signaling Pathway ◽

Immune System Development ◽

Precision Therapy ◽

Gastric Cancer Patients

Gastric cancer (GC) is the fifth most common cancer globally. Secreted frizzled-related proteins (SFRP) are important elements associated with the Wnt signaling pathway, and its dysregulated expression is found in multiple cancers. However, the function of distinct SFRPs in GC remains poorly understood. We investigated the differential expression, prognostic value, and immune cell infiltration of SFRPs in gastric cancer patients from the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan–Meier plotter, cBioPortal, STRING, Gene-MANIA, DAVID, MethSurv, and TIMER databases. We found that the expression levels of SFRP2 and SFRP4 were significantly increased in GC tissues, whereas the SFRP1 and SFRP5 expressions were reduced. SFRP1, SFRP2, and SFRP5 were significantly correlated with the clinical cancer stage in GC patients. Higher expression of SFRPs was associated with short overall survival (OS) in GC patients. Besides, high SFRPs methylation showed favorable OS in GC patients. The functions of SFRPs were primarily related to the Wnt signaling pathway, immune system development, and basal cell carcinoma. The expression of SFRPs was strongly correlated with immune infiltrating cells, including CD4+ T cells and macrophages in GC. Our study indicated that SFRPs could be potential targets of precision therapy and prognostic biomarkers for the survival of GC patients.

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Identifying of biomarkers associated with gastric cancer based on 11 topological analysis methods of CytoHubba

Scientific Reports ◽

10.1038/s41598-020-79235-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hua Ma ◽

Zhihui He ◽

Jing Chen ◽

Xu Zhang ◽

Pingping Song

Keyword(s):

Gastric Cancer ◽

Protein Interactions ◽

Clustering Algorithm ◽

Cox Model ◽

Topological Analysis ◽

Lasso Regression ◽

Ppi Network ◽

Hub Genes ◽

P53 Signaling ◽

Analysis Methods

AbstractGastric cancer (GC) is one of the most common types of malignancy. Its potential molecular mechanism has not been clarified. In this study, we aimed to explore potential biomarkers and prognosis-related hub genes associated with GC. The gene chip dataset GSE79973 was downloaded from the GEO datasets and limma package was used to identify the differentially expressed genes (DEGs). A total of 1269 up-regulated and 330 down-regulated genes were identified. The protein-protein interactions (PPI) network of DEGs was constructed by STRING V11 database, and 11 hub genes were selected through intersection of 11 topological analysis methods of CytoHubba in Cytoscape plug-in. All the 11 selected hub genes were found in the module with the highest score from PPI network of all DEGs by the molecular complex detection (MCODE) clustering algorithm. In order to explore the role of the 11 hub genes, we performed GO function and KEGG pathway analysis for them and found that the genes were enriched in a variety of functions and pathways among which cellular senescence, cell cycle, viral carcinogenesis and p53 signaling pathway were the most associated with GC. Kaplan-Meier analysis revealed that 10 out of the 11 hub genes were related to the overall survival of GC patients. Further, seven of the 11 selected hub genes were verified significantly correlated with GC by uni- or multivariable Cox model and LASSO regression analysis including C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1. C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1 may serve as potential prognostic biomarkers and therapeutic targets for GC.

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