scholarly journals MAPK10 Expression as a Prognostic Marker of the Immunosuppressive Tumor Microenvironment in Human Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Huahui Li ◽  
Yuting Li ◽  
Ying Zhang ◽  
Binbin Tan ◽  
Tuxiong Huang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Transmembrane Protein ◽  
Cell Receptor ◽  
Receptor Activation ◽  
Mapk Signaling ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Pathway Analyses

Hepatocellular carcinoma (HCC) remains a devastating malignancy worldwide due to lack of effective therapy. The immune-rich contexture of HCC tumor microenvironment (TME) makes this tumor an appealing target for immune-based therapies; however, the immunosuppressive TME is still a major challenge for more efficient immunotherapy in HCC. Using bioinformatics analysis based on the TCGA database, here we found that MAPK10 is frequently down-regulated in HCC tumors and significantly correlates with poor survival of HCC patients. HCC patients with low MAPK10 expression have lower expression scores of tumor infiltration lymphocytes (TILs) and stromal cells in the TME and increased scores of tumor cells than those with high MAPK10 expression. Further transcriptomic analyses revealed that the immune activity in the TME of HCC was markedly reduced in the low-MAPK10 group of HCC patients compared to the high-MAPK10 group. Additionally, we identified 495 differentially expressed immune-associated genes (DIGs), with 482 genes down-regulated and 13 genes up-regulated in parallel with the decrease of MAPK10 expression. GO enrichment and KEGG pathway analyses indicated that the biological functions of these DIGs included cell chemotaxis, leukocyte migration and positive regulation of the response to cytokine–cytokine receptor interaction, T cell receptor activation and MAPK signaling pathway. Protein–protein interaction (PPI) analyses of the 495 DIGs revealed five potential downstream hub genes of MAPK10, including SYK, CBL, VAV1, LCK, and CD3G. Several hub genes such as SYK, LCK, and VAV1 could respond to the immunological costimulatory signaling mediated by the transmembrane protein ICAM1, which was identified as a down-regulated DIG associated with low-MAPK10 expression. Moreover, ectopic overexpression or knock-down of MAPK10 could up-regulate or down-regulate ICAM1 expression via phosphorylation of c-jun at Ser63 in HCC cell lines, respectively. Collectively, our results demonstrated that MAPK10 down-regulation likely contributes to the immunosuppressive TME of HCC, and this gene might serve as a potential immunotherapeutic target and a prognostic factor for HCC patients.

Identification of hub genes specific to pulmonary metastasis in osteosarcoma through integrated bioinformatics analysis

2021 ◽  
pp. 1-11
Author(s):  
Yinan Chai ◽  
Lihan Xu ◽  
Rui He ◽  
Liangjun Zhong ◽  
Yuying Wang
Keyword(s):  
Pulmonary Metastasis ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Experimental Studies ◽  
Genetic Alterations ◽  
Mapk Signaling ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Pathway Analyses ◽  
Geo Database

BACKGROUND: Pulmonary metastasis is the most frequent cause of death in osteosarcoma (OS) patients. Recently, several bioinformatics studies specific to pulmonary metastatic osteosarcoma (PMOS) have been applied to identify genetic alterations. However, the interpretation and reliability of the results obtained were limited for the independent database analysis. OBJECTIVE: The expression profiles and key pathways specific to PMOS remain to be comprehensively explored. Therefore, in our study, three original datasets of GEO database were selected. METHODS: Initially, three microarray datasets (GSE14359, GSE14827, and GSE85537) were downloaded from the GEO database. Differentially expressed genes (DEGs) between PMOS and nonmetastatic osteosarcoma (NMOS) were identified and mined using DAVID. Subsequently, GO and KEGG pathway analyses were carried out for DEGs. Corresponding PPI network of DEGs was constructed based on the data collected from STRING datasets. The network was visualized with Cytoscape software, and ten hub genes were selected from the network. Finally, survival analysis of these hub genes also used the TARGET database. RESULTS: In total, 569 upregulated and 1238 downregulated genes were filtered as DEGs between PMOS and NMOS. Based on the GO analysis result, these DEGs were significantly enriched in the anatomical structure development, extracellular matrix, biological adhesion, and cell adhesion terms. Based on the KEGG pathway analysis result, these DEGs were mainly enriched in the pathways in cancer, PI3K-Akt signaling, MAPK signaling, focal adhesion, cytokine-cytokine receptor interaction, and IL-17 signaling. Hub genes (ANXA1 and CXCL12) were significantly associated with overall survival time in OS patient. CONCLUSION: Our results may provide new insight into pulmonary metastasis of OS. However, experimental studies remain necessary to elucidate the biological function and mechanism underlying PMOS.

scholarly journals Cyclin B1 acts as a tumor microenvironment-related cancer promoter and prognostic biomarker in hepatocellular carcinoma

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110162
Author(s):  
Yangming Hou ◽  
Xin Wang ◽  
Junwei Wang ◽  
Xuemei Sun ◽  
Xinbo Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Proportional Hazards ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Cyclin B1 ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Tumor Promoter ◽  
Protein Protein Interaction

Objectives The present study aimed to develop a gene signature based on the ESTIMATE algorithm in hepatocellular carcinoma (HCC) and explore possible cancer promoters. Methods The ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cells (TICs) in a cohort of HCC patients. The differentially expressed genes (DEGs) were screened by Cox proportional hazards regression analysis and protein–protein interaction (PPI) network construction. Cyclin B1 (CCNB1) function was verified using experiments. Results The stromal and immune scores were associated with clinicopathological factors and recurrence-free survival (RFS) in HCC patients. In total, 546 DEGs were up-regulated in low score groups, 127 of which were associated with RFS. CCNB1 was regarded as the most predictive factor closely related to prognosis of HCC and could be a cancer promoter. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analyses indicated that CCNB1 levels influenced HCC tumor microenvironment (TME) immune activity. Conclusions The ESTIMATE signature can be used as a prognosis tool in HCC. CCNB1 is a tumor promoter and contributes to TME status conversion.

The costimulatory activity of Tim-3 requires Akt and MAPK signaling and its recruitment to the immune synapse

2021 ◽  
Vol 14 (687) ◽  
pp. eaba0717
Author(s):  
Shunsuke Kataoka ◽  
Priyanka Manandhar ◽  
Judong Lee ◽  
Creg J. Workman ◽  
Hridesh Banerjee ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Activation ◽  
Cell Activation ◽  
Transmembrane Domain ◽  
Transmembrane Protein ◽  
Cell Receptor ◽  
Mapk Signaling ◽  
Inhibitory Protein ◽  
Immune Synapse

Expression of the transmembrane protein Tim-3 is increased on dysregulated T cells undergoing chronic activation, including during chronic infection and in solid tumors. Thus, Tim-3 is generally thought of as an inhibitory protein. We and others previously reported that under some circumstances, Tim-3 exerts paradoxical costimulatory activity in T cells (and other cells), including enhancement of the phosphorylation of ribosomal S6 protein. Here, we examined the upstream signaling pathways that control Tim-3–mediated increases in phosphorylated S6 in T cells. We also defined the localization of Tim-3 relative to the T cell immune synapse and its effects on downstream signaling. Recruitment of Tim-3 to the immune synapse was mediated exclusively by the transmembrane domain, replacement of which impaired the ability of Tim-3 to costimulate T cell receptor (TCR)–dependent S6 phosphorylation. Furthermore, enforced localization of the Tim-3 cytoplasmic domain to the immune synapse in a chimeric antigen receptor still enabled T cell activation. Together, our findings are consistent with a model whereby Tim-3 enhances TCR-proximal signaling under acute conditions.

scholarly journals Mining TCGA Database for Tumor Microenvironment-Related Genes of Prognostic Value in Hepatocellular Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Zhenfeng Deng ◽  
Jilong Wang ◽  
Banghao Xu ◽  
Zongrui Jin ◽  
Guolin Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Malignant Tumors ◽  
Public Access ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Protein Protein Interaction ◽  
Potential Association ◽  
Poor Outcomes

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The “Estimation of STromal and Immune cells in MAlignant Tumors using Expression data” algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain FABP3, GALNT5, GPR84, ITGB6, MYEOV, PLEKHS1, and STRA6 and may be candidate biomarkers for HCC prognosis.

scholarly journals Anticancer Effects of Emodin on HepG2 Cell: Evidence from Bioinformatic Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Rui-sheng Zhou ◽  
Xiong-Wen Wang ◽  
Qin-feng Sun ◽  
Zeng Jie Ye ◽  
Jian-wei Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Hepg2 Cells ◽  
Molecular Mechanisms ◽  
Mapk Signaling ◽  
Ion Concentration ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Mrna Levels ◽  
Hub Genes ◽  
Positive Regulation

Hepatocellular carcinoma (HCC) is a primary cause of cancer-related death in the world. Despite the fact that there are many methods to treat HCC, the 5-year survival rate of HCC is still at a low level. Emodin can inhibit the growth of HCC cells invitroand invivo. However, the gene regulation of emodin in HCC has not been well studied. In our research, RNA sequencing technology was used to identify the differentially expressed genes (DEGs) in HepG2 cells induced by emodin. A total of 859 DEGs were identified, including 712 downregulated genes and 147 upregulated genes in HepG2 cells treated with emodin. We used DAVID for function and pathway enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING, and Cytoscape was used for module analysis. The enriched functions and pathways of the DEGs include positive regulation of apoptotic process, structural molecule activity and lipopolysaccharide binding, protein digestion and absorption, ECM-receptor interaction, complement and coagulation cascades, and MAPK signaling pathway. 25 hub genes were identified and pathway analysis revealed that these genes were mainly enriched in neuropeptide signaling pathway, inflammatory response, and positive regulation of cytosolic calcium ion concentration. Survival analysis showed that LPAR6, C5, SSTR5, GPR68, and P2RY4 may be involved in the molecular mechanisms of emodin therapy for HCC. A quantitative real-time PCR (qRT-PCR) assay showed that the mRNA levels of LPAR6, C5, SSTR5, GPR68, and P2RY4 were significantly decreased in HepG2 cells treated with emodin. In conclusion, the identified DEGs and hub genes in the present study provide new clues for further researches on the molecular mechanisms of emodin.

scholarly journals Bioinformatics analysis of different candidate genes involved in hepatocellular carcinoma induced by HepG2 cells or tumor cells of patients

2020 ◽  
Vol 48 (6) ◽  
pp. 030006052093211
Author(s):  
Xiang Zhang ◽  
Songna Yin ◽  
Ke Ma
Keyword(s):  
Hepatocellular Carcinoma ◽  
Hepg2 Cells ◽  
Liver Parenchyma ◽  
Preclinical Study ◽  
Gene Expression Omnibus ◽  
Receptor Interaction ◽  
Peroxisome Proliferator ◽  
Ppi Network ◽  
Peroxisome Proliferator Activated Receptor ◽  
Protein Protein Interaction

Objective Hepatocellular carcinoma (HCC) is a common cancer with a high mortality rate; the molecular mechanism involved in HCC remain unclear. We aimed to provide insight into HCC induced with HepG2 cells and identify genes and pathways associated with HCC, as well as potential therapeutic targets. Methods Dataset GSE72581 was downloaded from the Gene Expression Omnibus, including samples from mice injected in liver parenchyma with HepG2 cells, and from mice injected with cells from patient tumor explants. Differentially expressed genes (DEGs) between the two groups of mice were analyzed. Then, gene ontology and Kyoto Encyclopedia of Gene and Genomes pathway enrichment analyses were performed. The MCODE plug-in in Cytoscape was applied to create a protein–protein interaction (PPI) network of DEGs. Results We identified 1,405 DEGs (479 upregulated and 926 downregulated genes), which were enriched in complement and coagulation cascades, peroxisome proliferator-activated receptor signaling pathway, and extracellular matrix–receptor interaction. The top 4 modules and top 20 hub genes were identified from the PPI network, and associations with overall survival were determined using Kaplan–Meier analysis. Conclusion This preclinical study provided data on molecular targets in HCC that could be useful in the clinical treatment of HCC.

scholarly journals Gender Differences in Rheumatoid Arthritis: Interleukin-4 Plays an Important Role

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Chaojie Yu ◽  
Chong Liu ◽  
Jie Jiang ◽  
Hao Li ◽  
Jiarui Chen ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gender Differences ◽  
Cell Differentiation ◽  
Clinical Manifestations ◽  
Cell Receptor ◽  
Chronic Inflammatory Disease ◽  
Interleukin 4 ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Kegg Pathways

Introduction. Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by symmetrical peripheral polyarthritis. A large number of studies have shown that RA is characterized by gender differences in clinical manifestations. The purpose of this study is to identify the key molecules of gender differences in patients with RA and to provide new molecular targets for personalized therapy. Material and Methods. The data from GSE55457 were downloaded from the comprehensive gene expression comprehensive database, and two groups (RA vs. No-RA groups, Male-RA vs. Female-RA groups) of differentially expressed genes (EDGs) were obtained by GEO2R. The GO function and KEGG pathway analyses of DEGs were carried out through the plug-in ClueGO in Cytoscape. Based on the STRING online, a protein-protein interaction (PPI) network was constructed. Hub genes were selected from CytoHubba. Through the intersection of the top 10 hub genes in two sets of EDGs, the key genes and related KEGG pathways were found. Quantitative Real-Time PCR and Western blotting analysis were performed for verification. Results. 1230 DEGs were screened between RA and No-RA groups, and 306 DEGs were screened between male and female RA groups. The common key gene of the two groups is IL-4. Between RA group and No-RA group, interleukin-4 (IL-4) participates in cytokine-cytokine receptor interaction, Th1 and Th2 cell differentiation, Th17 cell differentiation, T cell receptor signaling pathway, etc. Conclusion. This study contributes to the molecular biological mechanism of gender differences in RA. IL-4 may have played an important role.

scholarly journals CSF3 Is a Potential Drug Target for the Treatment of COVID-19

2021 ◽  
Vol 11 ◽  
Author(s):  
Chao Fang ◽  
Jie Mei ◽  
Huixiang Tian ◽  
Yu-Ligh Liou ◽  
Dingchao Rong ◽  
...  
Keyword(s):  
Drug Target ◽  
Bronchial Epithelial Cell ◽  
Receptor Interaction ◽  
Epithelial Cell Line ◽  
Cumulative Number ◽  
Potential Drug Target ◽  
Potential Drug ◽  
Hub Genes ◽  
Therapeutic Vaccines ◽  
Protein Protein Interaction

Coronavirus Disease 2019 (COVID-19) is an acute respiratory infectious disease that appeared at the end of 2019. As of July 2020, the cumulative number of infections and deaths have exceeded 15 million and 630,000, respectively. And new cases are increasing. There are still many difficulties surrounding research on the mechanism and development of therapeutic vaccines. It is urgent to explore the pathogenic mechanism of viruses to help prevent and treat COVID-19. In our study, we downloaded two datasets related to COVID-19 (GSE150819 and GSE147507). By analyzing the high-throughput expression matrix of uninfected human bronchial organoids and infected human bronchial organoids in the GSE150819, 456 differentially expressed genes (DEGs) were identified, which were mainly enriched in the cytokine–cytokine receptor interaction pathway and so on. We also constructed the protein–protein interaction (PPI) network of DEGs to identify the hub genes. Then we analyzed GSE147507, which contained lung adenocarcinoma cell lines (A549 and Calu3) and the primary bronchial epithelial cell line (NHBE), obtaining 799, 460, and 46 DEGs, respectively. The results showed that in human bronchial organoids, A549, Calu3, and NHBE samples infected with SARS-CoV-2, only one upregulated gene CSF3 was identified. Interestingly, CSF3 is one of the hub genes we previously screened in GSE150819, suggesting that CSF3 may be a potential drug target. Further, we screened potential drugs targeting CSF3 by MOE; the top 50 drugs were screened by flexible docking and rigid docking, with 37 intersections. Two antiviral drugs (Elbasvir and Ritonavir) were included; Elbasvir and Ritonavir formed van der Waals (VDW) interactions with surrounding residues to bind with CSF3, and Elbasvir and Ritonavir significantly inhibited CSF3 protein expression.

scholarly journals The Important Role of Perituberal Tissue in Epileptic Patients with Tuberous Sclerosis Complex by the Transcriptome Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shuqiang Li ◽  
Huijie Shao ◽  
Liansheng Chang
Keyword(s):  
Tuberous Sclerosis ◽  
Tuberous Sclerosis Complex ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Genes ◽  
R Language ◽  
Protein Protein Interaction

Epilepsy is most common in patients with tuberous sclerosis complex (TSC). However, in addition to the challenging treatment, the pathogenesis of epilepsy is still controversial. To determine the transcriptome characteristics of perituberal tissue (PT) and clarify its role in the pathogenesis of epilepsy, GSE16969 was downloaded from the GEO database for further study by comprehensive bioinformatics analysis. Identification of differentially expressed genes (DEGs), functional enrichment analysis, construction of protein-protein interaction (PPI) network, and selection of Hub genes were performed using R language, Metascape, STRING, and Cytoscape, respectively. Comparing with cortical tuber (CT), 220 DEGs, including 95 upregulated and 125 downregulated genes, were identified in PT and mainly enriched in collagen-containing extracellular matrix and positive regulation of receptor-mediated endocytosis, as well as the pathways of ECM-receptor interaction and neuroactive ligand-receptor interaction. As for normal cortex (NC), 1549 DEGs, including 30 upregulated and 1519 downregulated genes, were identified and mainly enriched in presynapse, dendrite and axon, and also the pathways of dopaminergic synapse and oxytocin signaling pathway. In the PPI network, 4 hub modules were found between PT and CT, and top 5 hub modules were selected between PT and NC. C3, APLNR, ANXA2, CD44, CLU, CP, MCHR2, HTR1E, CTSG, APP, and GNG2 were identified as Hub genes, of which, C3, CD44, ANXA2, HTR1E, and APP were identified as Hub-BottleNeck genes. In conclusion, PT has the unique characteristics different from CT and NC in transcriptome and makes us further understand its importance in the TSC-associated epilepsy.

scholarly journals Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis

2021 ◽  
Author(s):  
Congcong Wang ◽  
Jianping Guo ◽  
Xiaoyang Zhao ◽  
Jia Jia ◽  
Wenting Xu ◽  
...  
Keyword(s):  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
Receptor Interaction ◽  
Analysis Tool ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Kegg Analysis ◽  
Prognostic Assessment ◽  
Scheme Selection

Background: To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis. Methods: The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation,Visualization and Intergrated Discovery was used to investigate their biological function by Gene Ontology(GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Protein-protein interaction of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized by Cytoscape. Genes calculated by CytoHubba with degree >10 were identified as hub genes. Then, the identified hub genes were verified by UALCAN online analysis tool to evaluate the prognostic value in PDCA. Results: Three expression profiles (GSE15471, GSE16515 and GSE32676) were downloaded from GEO database. The three sets of DEGs exhibited an intersection consisting of 223 genes (214 upregulated DEGs and 9 downregulated DEGs). GO analysis showed that the 223 DEGs were significantly enriched in extracellular exosome, plasma membrane and extracellular space. ECM-receptor interaction, PI3K-Akt signaling pathway and Focal adhesion were the most significantly enriched pathway according to KEGG analysis. By combining the results of Cytohubba, 30 hub genes with a high degree of connectivity were picked out. Finally, we candidated 3 biomarkers by UALCAN online survival analysis, including CEP55, ANLN and PRC1. Conclusion: we identified CEP55, ANLN and PRC1 may be the potential biomarkers and therapeutic targets of PDCA, which used for prognostic assessment and scheme selection.

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