scholarly journals Identification of a Key Glioblastoma Candidate Gene, FUBP3, Based on Weighted Gene Co-expression Network Analysis

2022 ◽  
Author(s):  
Jianmin Li ◽  
Zhao Zhang ◽  
Ke Guo ◽  
Shuhua Wu ◽  
Chong Guo ◽  
...  
Keyword(s):  
T Cells ◽  
Survival Analysis ◽  
Network Analysis ◽  
Candidate Gene ◽  
Differentially Expressed Genes ◽  
Normal Tissue ◽  
Venn Diagram ◽  
Adjacent Normal Tissue ◽  
Immune Infiltration ◽  
Significant Gene

Abstract Background: Glioblastoma multiforme (GBM) is the most common aggressive malignant brain tumor. However, the molecular mechanism of glioblastoma formation is still poorly understood. To identify candidate genes that may be connected to glioma growth and development, weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between gene sets and clinical characteristics. We also explored the function of the key candidate gene.Methods: Two GBM datasets were selected from GEO Datasets. The R language was used to identify differentially expressed genes. WGCNA was used to construct a gene co-expression network in the GEO glioblastoma samples. A custom Venn diagram website was used to find the intersecting genes. The GEPIA website was used for survival analysis to determine the significant gene, FUBP3. OS,DSS, and PFI analyses, based on the UCSC Cancer Genomics Browser, were performed to verify the significance of FUBP3. Immunohistochemistry was performed to evaluate the expression of FUBP3 in glioblastoma and adjacent normal tissue. KEGG and GO enrichment analyses were used to reveal possible functions of FUBP3. Microenvironment analysis was used to explore the relationship between FUBP3 and immune infiltration. Immunohistochemistry was performed to verify the results of the microenvironment analysis.Results: GSE70231 and GSE108474 were selected from GEO Datasets, then 715 and 694 differentially expressed genes (DEGs) from GSE70231 and GSE108474, respectively, were identified. We then performed weighted gene co-expression network analysis (WGCNA) and identified the most downregulated gene modules of GSE70231 and GSE108474, and 659 and 3915 module genes from GSE70231 and GSE108474, respectively, were selected. Five intersection genes (FUBP3, DAD1, CLIC1, ABR, and DNM1) were calculated by Venn diagram. FUBP3 was then identified as the only significant gene by survival analysis using the GEPIA website. OS, DSS, and PFI analyses verified the significance of FUBP3. Immunohistochemical analysis revealed FUBP3 expression in GBM and adjacent normal tissue. KEGG and GO analyses uncovered the possible function of FUBP3 in GBM. Tumor microenvironment analysis showed that FUBP3 may be connected to immune infiltration, and immunohistochemistry identified a positive correlation between immune cells (CD4+ T cells, CD8+ T cells, and macrophages) and FUBP3.Conclusion: FUBP3 is associated with immune surveillance in GBM, indicating that it has a great impact on GBM development and progression. Therefore, interventions involving FUBP3 and its regulatory pathway may be a new approach for GBM treatment.

Co-expression network analysis of placental transcriptome as the basis for searching signal ways and preeclampsia biomarkers

2020 ◽  
pp. 71-72
Author(s):  
А.А. Бабовская ◽  
Е.А. Трифонова ◽  
А.А. Зарубин ◽  
А.В. Марков ◽  
В.А. Степанов
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Early Diagnosis ◽  
Differentially Expressed Genes ◽  
Pathological Process ◽  
Biological Pathways ◽  
Perinatal Morbidity ◽  
Hub Gene ◽  
Significant Gene ◽  
Placental Diseases

Проблема профилактики и ранней диагностики преэклампсии (ПЭ) продолжает оставаться одной из ведущих в акушерстве, поскольку данное осложнение беременности несет большой риск материнской и младенческой смертности. Считается, что основная причина ПЭ - это нарушение этапов формирования плаценты, а регуляции экспрессии генов является значимым механизмом развития плацентарной патологии. Классический подход в транскриптомных исследованиях экспрессии основан на поиске дифференциально-экспрессирующихся генов при заболевании, однако такой подход рассматривает гены изолированно, не учитывая их возможные взаимодействия. Более перспективным подходом является анализ коэкспрессии, который описывает гены, вовлеченные в единые биологические пути патологического процесса, а также позволяет выделять в каждом из кластеров наиболее функционально значимый ген в сети - центральный (hub gene). The problem of prevention and early diagnosis of preeclampsia continues to be one of the leading in obstetrics. It`s a major problem that contributes substantially to maternal and perinatal morbidity and mortality worldwide . Gene expression contributes significantly to the pathogenesis of placental diseases. Traditional methods of studying gene expression are based on the search of differentially expressed genes in a disease, but this approach considers genes in isolation. Coexpression analysis describes the genes involved in the unified biological pathways of the pathological process and also allows you to select in each of the clusters the most functionally significant gene in the network - the hub gene.

ILC2-derived IL-9 inhibit s colorectal cancer progression by activating CD8+ T cells

2020 ◽  
Author(s):  
Jie Wan ◽  
Lan Huang ◽  
Yinqiu Wu ◽  
Xiaoyun Ji ◽  
Shun Yao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Flow Cytometry ◽  
T Cells ◽  
Cancer Progression ◽  
Normal Tissue ◽  
Lymphoid Cells ◽  
Adjacent Normal Tissue

Abstract Background Type 2 innate lymphoid cells (ILC2s), characterized by secreting type 2 cytokines, regulate multiple immune responses. ILC2s are found in different tumor tissues and ILC2-derived interleukin (IL)-4, IL-5, and IL-13 act on the cells in tumor microenvironment to participate in tumor progression. ILC2s are abundant in colorectal cancer (CRC) tissue, but the role of ILC2s in CRC remains unclear. Methods ILC2s were sorted from the spleen using microbeads combined with flow cytometry and tumor infiltrating CD8+ T cells were isolated from tumor tissue by microbeads. Flow cytometry and immunofluorescence were used to detect the percentage of ILC2s and CD8+ T cells in the spleen and CRC tissue. Effects of IL-9 and IL-9-stimulated CD8+ T cells on CT26 cells were measured by proliferation, apoptosis, and migration assays in vitro. GEPIA was used to detect the ILC2s chemokines in CRC tissue and adjacent normal tissue. Results We found that ILC2s were increased in CRC tissue compared with the adjacent normal tissue. In vitro experiments showed that IL-9 could activate CD8+ T cells to promote the death of CT26 cells. ILC2s were the main IL-9-secreting cells in CRC tissue as shown by flow cytometry analysis. In vivo experiments showed that neutralizing ILC2s promoted the tumor growth, while tumor inhibition occurred by intravenous injection of IL-9. Conclusions Our results demonstrated that ILC2-derived IL-9 activated CD8+ T cells to promote anti-tumor effects in CRC.

scholarly journals CXCR3 Expression and Genome-Wide 3′ Splice Site Selection in the TCGA Breast Cancer Cohort

Life ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 746
Author(s):  
Lauren A. Levesque ◽  
Scott Roy ◽  
Nicole Salazar
Keyword(s):  
Breast Cancer ◽  
Splice Site ◽  
Site Selection ◽  
Normal Tissue ◽  
Adjacent Normal Tissue ◽  
Splice Site Selection ◽  
Immune Infiltration ◽  
Cxcr3 Expression ◽  
Genome Wide

CXCR3 is a chemokine receptor with two well-characterized isoforms that have unique, context-dependent roles: CXCR3-A and CXCR3-B, which are produced through alternative 3′ splice site selection (A3SS). RNA-seq data from The Cancer Genome Atlas (TCGA) were used to correlate CXCR3 expression with breast cancer progression. This analysis revealed significant CXCR3 expression patterns associated with survival and differential expression between the tumor and adjacent normal tissue. TCGA data were used to estimate abundance of immune cells in breast cancer, which demonstrated the association of CXCR3 with immune infiltration, particularly in the triple-negative subtype. Given the importance of A3SS in CXCR3, genome-wide analysis of A3SS events was performed to identify events that were differentially spliced between breast cancer tissue and adjacent normal tissue. A total of 481 splicing events in 424 genes were found to be differentially spliced. The parent genes of differentially spliced events were enriched in RNA processing and splicing functions, indicating an underappreciated role of A3SS in the integrated splicing network of breast cancer. These results further validated the role of CXCR3 in immune infiltration of tumors, while raising questions about the role of A3SS splicing.

scholarly journals Identification of Prognostic Biomarkers and Correlation With Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhangya Pu ◽  
Yuanyuan Zhu ◽  
Xiaofang Wang ◽  
Yun Zhong ◽  
Fang Peng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Survival Analysis ◽  
Immune Cell ◽  
Cox Regression ◽  
Quantitative Polymerase Chain Reaction ◽  
Prognostic Biomarkers ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Cerna Network

BackgroundHepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC.MethodsRNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve, TISIDB and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by quantitative polymerase chain reaction, Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds.ResultsThe predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8+ T cells, CD4+ T cells, monocytes, macrophages, neutrophils, and dendritic cells.ConclusionThe findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

scholarly journals SNAP25 Is a Potential Prognostic Biomarker for Prostate Cancer

2021 ◽  
Author(s):  
Longjiang Di ◽  
Maoli Gu ◽  
Yan Wu ◽  
Guoqiang Liu ◽  
Lishuo Zhang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
T Cells ◽  
Gene Ontology ◽  
Differentially Expressed Genes ◽  
Gleason Score ◽  
Immune Cells ◽  
Prognostic Biomarker ◽  
Differentially Expressed ◽  
Normal Prostate ◽  
Immune Infiltration

Abstract Background Prostate cancer is one of the most lethal cancers in male individuals. The Synaptosome associated protein 25 (SNAP25) gene is a key mediator of multiple biological functions in tumours. However, its significant impact on the prognosis in prostate cancer remains to be elucidated.Methods We performed a comprehensive analysis of the Cancer Genome Atlas dataset (TCGA) to identify the differentially expressed genes between prostate cancer and normal prostate tissue. We subjected the differentially expressed genes to gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes functional analysis, and constructed a protein-protein interaction network. We then screened for pivotal genes to identify the hub genes of prognostic significance by performing Cox regression analysis. We identified SNAP25 as one such gene and analysed the relationship between its expression in prostate cancer to poor prognosis using Studio R. Results TCGA database demonstrated that SNAP25 was significantly downregulated in prostate cancer, and that its expression was significantly correlated with the Gleason score and pathological TNM stage of patients. The association between SNAP25 expression and tumour-infiltrating immune cells was evaluated using the Tumour Immune Estimation Resource site. Gene set enrichment and gene ontology analyses were used to analyse the function of SNAP25. We found that SNAP25 expression strongly correlated with overall survival in the Gleason score. In addition, SNAP25 was involved in the activation, differentiation, and migration of immune cells, and its expression was positively correlated with immune infiltration, including of B cells, CD8+ T cells, CD4+ T cells, neutrophils, dendritic cells, macrophages, and natural killer cells. SNAP25 expression was also positively correlated with chemokines/chemokine receptors, suggesting that SNAP25 might regulate the migration of immune cells. These molecular experiment results validate the low expression of SNAP25 seen in prostate cancer cells.Conclusion Our findings indicate a relationship between SNAP25 expression and prostate cancer, demonstrating that SNAP25 is a potential prognostic biomarker due to its vital role in immune infiltration.

scholarly journals P02.04 Tissue-infiltrating Th9 cells in human endometrial cancer

2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A9.1-A9
Author(s):  
H Tong ◽  
H Feng ◽  
X Wan
Keyword(s):  
T Cells ◽  
Endometrial Cancer ◽  
Nk Cells ◽  
Normal Tissue ◽  
High Dimensional ◽  
Adjacent Normal Tissue ◽  
Immune Microenvironment ◽  
Th9 Cells ◽  
Single Cell Profiling ◽  
Shed Light

BackgroundEndometrial cancer (EC) is a hormone-related carcinoma with increased morbidity among female patients of all backgrounds. The immune microenvironment of EC is uncertain.Materials and Methods102 patients were recruited in the present study. 90 postoperative specimens from the patients were analyzed by immunohistochemistry. The leukocyte landscape of endometrial cancer was mapped using high-dimensional single-cell profiling (CyTOF) for 12 patients.ResultsNK cells, MDMs, and neutrophils were enriched in adjacent normal tissue. CCR5+CD38+ PD1+Th9 cells were enriched in the invasive margin. Additionally, PD1+ESRneg T cells and Siglec1+CCR5+CD40+ESRhi macrophage were infiltrated in the tumors.Abstract P02.04 Figure 1ConclusionsImmunological landscape of EC might shed light on new immunotherapuetic approach.Disclosure InformationH. Tong: None. H. Feng: None. X. Wan: None.

scholarly journals Identification of Differentially Expressed Genes Reveals BGN Predicting Overall Survival and Tumor Immune Infiltration of Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Weizhi Chen ◽  
Zhongheng Yang
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Treatment Strategies ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Potential Biomarker ◽  
Positive Correlations ◽  
First Time

Gastric cancer (GC) is one of the most widely occurring malignancies worldwide. Although the diagnosis and treatment strategies of GC have been greatly improved in the past few decades, the morbidity and lethality rates of GC are still rising due to lacking early diagnosis strategies and powerful treatments. In this study, a total of 37 differentially expressed genes were identified in GC by analyzing TCGA, GSE118897, GSE19826, and GSE54129. Using the PPI database, we identified 17 hub genes in GC. By analyzing the expression of hub genes and OS, MFAP2, BGN, and TREM1 were related to the prognosis of GC. In addition, our results showed that higher levels of BGN exhibited a significant correlation with shorter OS time in GC. Nomogram analysis showed that the dysregulation of BGN could predict the prognosis of GC. Moreover, we revealed that BGN had a markedly negative correlation with B cells but had positive correlations with CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells in GC samples. The pan-cancer analysis demonstrated that BGN was differentially expressed and related to tumor-infiltrating immune cells across human cancers. This study for the first time comprehensively revealed that BGN was a potential biomarker for the prediction of GC prognosis and tumor immune infiltration.

scholarly journals Identification of Immune Infiltration, Differentially Expressed Genes, and Signaling Pathways in Fanconi Anemia Based on Bioinformatics Analysis

2022 ◽  
Author(s):  
Biyu Shen ◽  
Songsong Shi ◽  
Haoyang Chen ◽  
Yi Lu ◽  
Hengmei Cui ◽  
...  
Keyword(s):  
T Cells ◽  
Differentially Expressed Genes ◽  
Fanconi Anemia ◽  
Bioinformatics Analysis ◽  
Neutrophil Activation ◽  
Normal Group ◽  
Differentially Expressed ◽  
Expression Levels ◽  
Immune Infiltration ◽  
Kegg Analysis

Abstract Background and Objective: Fanconi anemia (FA) patients have a reduced ability to form blood cells, accompanied by multiple congenital malformations, mental retardation, solid tumors, and other symptoms. However, the molecular mechanism that causes FA is unclear, and few studies have addressed the regulatory mechanism of immune infiltration in FA. Here, we aimed to identify differentially expressed genes (DEGs), pathways, and immune infiltration involved in FA using integrated bioinformatics analysis and molecular mechanisms. Methods: The GEO gene chip database was searched for FA low density bone marrow tissue, and the content and proportion of 22 types of immune cells in the FA group and the normal group were analyzed using CIBERSORT. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of FA differentially expressed genes (DEGs) using R language and related package programs was also performed.Results: The expression levels of T cells regulatory (Tregs), M2 macrophages, T cells CD8, dendritic cells resting, and T cells CD4 naïve in FA were higher than in the normal group. Furthermore, the expression levels of naïve B cells, monocytes, and resting mast cells in FA were lower than in the normal group. GO analysis of FA differential genes showed that “neutrophil degranulation,” “neutrophil activation,” and “neutrophil activation involved in immune response,” were most frequently enriched among biological processes, with “specific granule,” “tertiary granule,” “tertiary granule lumen” among cellular components, and “carbohydrate binding” among molecular functions. For the KEGG analysis, “Asthma” was most often enriched.Conclusion: This study obtained useful data related to immune infiltration, DEGs, and gene pathways of FA, and provides new evidence for immunotherapy and clinical assessment of FA patients. These results are potentially a useful reference for subsequent related scientific research.

scholarly journals Identification of key biomarkers and immune infiltration in the synovial tissue of osteoarthritis by bioinformatics analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8390 ◽  
Author(s):  
Weisong Cai ◽  
Haohuan Li ◽  
Yubiao Zhang ◽  
Guangtao Han
Keyword(s):  
T Cells ◽  
Mast Cells ◽  
Signaling Pathway ◽  
Synovial Tissue ◽  
Differentially Expressed Genes ◽  
Bioinformatics Analysis ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Normal Controls

Background Osteoarthritis (OA) is the most common chronic degenerative joint disease and is mainly characterized by cartilage degeneration, subcartilage bone hyperplasia, osteophyte formation and joint space stenosis. Recent studies showed that synovitis might also be an important pathological change of OA. However, the molecular mechanisms of synovitis in OA are still not well understood. Objective This study was designed to identify key biomarkers and immune infiltration in the synovial tissue of osteoarthritis by bioinformatics analysis. Materials and Methods The gene expression profiles of GSE12021, GSE55235 and GSE55457 were downloaded from the GEO database. The differentially expressed genes (DEGs) were identified by the LIMMA package in Bioconductor, and functional enrichment analyses were performed. A protein-protein interaction network (PPI) was constructed, and module analysis was performed using STRING and Cytoscape. The CIBERSORT algorithm was used to analyze the immune infiltration of synovial tissue between OA and normal controls. Results A total of 106 differentially expressed genes, including 68 downregulated genes and 38 upregulated genes, were detected. The PPI network was assessed, and the most significant module containing 14 hub genes was identified. Gene Ontology analysis revealed that the hub genes were significantly enriched in immune cell chemotaxis and cytokine activity. KEGG pathway analysis showed that the hub genes were significantly enriched in the rheumatoid arthritis signaling pathway, IL-17 signaling pathway and cytokine-cytokine receptor interaction signaling pathway. The immune infiltration profiles varied significantly between osteoarthritis and normal controls. Compared with normal tissue, OA synovial tissue contained a higher proportion of memory B cells, naive CD4+ T cells, regulatory T cells, resting dendritic cells and resting mast cells, while naive CD4+ T cells, activated NK cells, activated mast cells and eosinophils contributed to a relatively lower portion (P > 0.05). Finally, the expression levels of 11 hub genes were confirmed by RT-PCR. Conclusion The hub genes and the difference in immune infiltration in synovial tissue between osteoarthritis and normal controls might provide new insight for understanding OA development.

scholarly journals Identification of Prognostic Biomarkers and Correlation with Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

2020 ◽  
Author(s):  
Zhangya Pu ◽  
Yuanyuan Zhu ◽  
Xiaofang Wang ◽  
Yun Zhong ◽  
Fang Peng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Survival Analysis ◽  
Immune Cell ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Prognostic Biomarkers ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Cerna Network

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC. Methods: RNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds. Results: The predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8 + T cells, CD4 + T cells, monocytes, macrophages, neutrophils, and dendritic cells. Conclusions: The findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

Sign in / Sign up

Export Citation Format

Share Document