Identification of Prognostic Biomarkers and Immunotherapeutic Targets with CXC Chemokines in Glioblastoma Multiforme Using Integrated Bioinformatic Analysis

Abstract Background Glioblastoma multiforme (GBM) is the most malignant central nervous system tumour bearing a dismal prognosis. The study aimed to explore the potential biomarkers and therapeutic targets with CXC chemokines in GBM by integrated bioinformatics analysis.Methods Differentially expressed CXC Chemokines were identified in GBM using GEPIA and UALCAN databases,and Kaplan–Meier analyses were performed by GEPIA subsequently. Protein -protein interaction (PPI) network was established in STRING database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were utilized to analyze differentially expressed CXC Chemokines and their similar genes gained from GEPIA. Then, we conducted transcription factors, kinase targets, and immune cells infiltration using TRRUST, LinkedOmics, and TIMER, respectively.Results The mRNA expression levels of CXCL3/5/6/9/10/11/12/13/16 in GMB were significantly elevated compared to normal tissues. GBM patients with higher transcriptional levels of CXCL5/6 were significantly associated with worse disease-free survival, while higher transcriptional levels of CXCL3/5/8 were significantly related to worse overall survival. The functions of CXC chemokines were enriched in Chemokine signaling pathway, Cytokine-cytokine receptor interaction, IL-17 signaling pathway, et.al. RELA and NFKB1were key transcription factors of CXC chemokines. The kinase targets of CXC chemokine contained CDK1, CDK2, PRKCD, MAPK14, ATM, LCK, MTOR, and GRK3, which are involved in oncogenesis, migration, and survival. Moreover, we revealed significant correlations between the expression of CXC chemokines and the infiltration immune cells, especially for dendritic cells.Conclusion The significant CXC chemokines and related pathways may provide a novel possibility for prognostic biomarkers and immunotherapeutic treatment in GMB.Short title: CXC Chemokines with prognosis in GBM

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Expression profile analysis of Differentially Expressed Genes in Human Coronary Artery Endothelial Cells Induced by Serum from Kawasaki Disease: A preliminary study

10.21203/rs.3.rs-54163/v1 ◽

2020 ◽

Author(s):

Xue Fan ◽

Meng Li ◽

Min Xiao ◽

Cong Liu ◽

Mingguo Xu

Keyword(s):

Endothelial Cells ◽

Coronary Artery ◽

Kawasaki Disease ◽

Signaling Pathway ◽

Differentially Expressed Genes ◽

Differentially Expressed ◽

Receptor Interaction ◽

Healthy Children ◽

Rna Seq ◽

Human Coronary Artery

Abstract Background: Kawasaki disease (KD) leads to coronary artery damage and the etiology of KD is unknown. The present study was designed to explore the differentially expressed genes (DEGs) in KD serum-induced human coronary artery endothelial cells (HCAECs) by RNA-sequence (RNA-seq). Methods: HCAECs were stimulated with serum (15% (v/v)), which were collected from 20 healthy children and 20 KD patients, for 24 hours. DEGs were then detected and analyzed by RNA-seq and bioinformatics analysis. Results: The expression of SMAD1, SMAD6, CD34, CXCL1, PITX2, and APLN was validated by qPCR. 102 genes, 59 up-regulated and 43 down-regulated genes, were significantly differentially expressed in KD groups. GO enrichment analysis showed that DEGs were enriched in cellular response to cytokines, cytokine-mediated signaling pathway, and regulation of immune cells migration and chemotaxis. KEGG signaling pathway analysis showed that DEGs were mainly involved in cytokine−cytokine receptor interaction, chemokine signaling pathway, and TGF−β signaling pathway. Besides, the mRNA expression levels of SMAD1, SMAD6, CD34, CXCL1, and APLN in the KD group were signiﬁcantly up-regulated compared with the normal group, whilePITX2 was significantly down-regulated. Conclusion: 102 DEGs in KD serum-induced HCAECs were identified, and six new targets were proposed as potential indicators of KD.

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Mining database for the therapeutic targets and prognostic biomarkers among STAT family in glioblastoma

Cancer Biomarkers ◽

10.3233/cbm-201746 ◽

2020 ◽

pp. 1-13

Author(s):

Chenglin Li ◽

Yanfei Zhou ◽

Hanshun Deng ◽

Yuanshen Ye ◽

Shuizhen Zhao ◽

...

Keyword(s):

Immune Response ◽

Signaling Pathway ◽

Web Applications ◽

Therapeutic Targets ◽

Prognostic Biomarkers ◽

Receptor Interaction ◽

Immune Gene ◽

Nf Kappa B ◽

Signal Transducers ◽

Pathways Analysis

BACKGROUND: Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor with a high mortality rate. Aberrant activation of signal transducers and activators of transcription (STAT) signaling results in tumor pathogenesis and progression by regulating cell cycle, cell survival and immune response. METHODS: Therapeutic targets and prognostic biomarkers within the STAT family in GBM were explored using web applications and databases. RESULTS: High levels of STAT1/3/5A/5B/6 and low levels of STAT4 were observed in GBM patients. GBM patients expressing high STAT1/2/3/5A/6 and low STAT4/5B levels had the worse overall survival. Among the STAT family, STAT4 and STAT6 were the most frequently mutated genes. A low to moderate correlation among members of the STAT family was observed. Additionally, the STATs were involved in activation or inhibition of cancer related pathways. Analysis of immune infiltrates showed STAT5A levels to be significantly correlated with abundance of immune cells and levels of immune gene biomarkers. Gene ontology (GO) functions and KEGG pathway analysis indicated that STAT5A is involved in immune response-regulating signaling pathway, neutrophil and lymphocyte mediated immunity, single-stranded DNA binding, cytokine-cytokine receptor interaction, NOD-like receptor signaling pathway, NF-kappa B signaling pathway and TNF signaling pathway. Moreover, several kinase and transcription factor targets of STAT5A in GBM were identified. CONCLUSION: We report here therapeutic targets, prognostic biomarkers and regulation network of STAT family in GBM. These findings lay a foundation for further studies on the role of STAT family in therapy and prognosis of GBM. Further studies are required to verify our results.

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Identification of hydatidosis-related modules and key regulatory genes

PeerJ ◽

10.7717/peerj.9280 ◽

2020 ◽

Vol 8 ◽

pp. e9280

Author(s):

Jijun Song ◽

Mingxin Song

Keyword(s):

Transcription Factors ◽

Signaling Pathway ◽

Target Genes ◽

Expression Profiles ◽

Differential Expression Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Bmp Signaling ◽

Differentially Expressed ◽

Regulatory Effects

Background Echinococcosis caused by larval of Echinococcus is prevalent all over the world. Although clinical experience showed that the presence of tapeworms could not be found in liver lesions, the repeated infection and aggravation of lesions still occur in the host. Here, this study constructed a multifactor-driven disease-related dysfunction network to explore the potential molecular pathogenesis mechanism in different hosts after E.multilocularis infection. Method First, iTRAQ sequencing was performed on human liver infected with E.multilocularis. Second, obtained microRNAs(miRNAs) expression profiles of humans and canine infected with Echinococcus from the GEO database. In addition, we also performed differential expression analysis, protein interaction network analysis, enrichment analysis, and crosstalk analysis to obtain genes and modules related to E.multilocularis infection. Pivot analysis is used to calculate the potential regulatory effects of multiple factors on the module and identify related non-coding RNAs(ncRNAs) and transcription factors(TFs). Finally, we screened the target genes of miRNAs of Echinococcus to further explore its infection mechanism. Results A total of 267 differentially expressed proteins from humans and 3,635 differentially expressed genes from canine were obtained. They participated in 16 human-related dysfunction modules and five canine-related dysfunction modules, respectively. Both human and canine dysfunction modules are significantly involved in BMP signaling pathway and TGF-beta signaling pathway. In addition, pivot analysis found that 1,129 ncRNAs and 110 TFs significantly regulated human dysfunction modules, 158 ncRNAs and nine TFs significantly regulated canine dysfunction modules. Surprisingly, the Echinococcus miR-184 plays a role in the pathogenicity regulation by targeting nine TFs and one ncRNA in humans. Similarly, miR-184 can also cause physiological dysfunction by regulating two transcription factors in canine. Conclusion The results show that the miRNA-184 of Echinococcus can regulate the pathogenic process through various biological functions and pathways. The results laid a solid theoretical foundation for biologists to further explore the pathogenic mechanism of Echinococcosis.

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INHBB Is a Novel Prognostic Biomarker Associated with Cancer-Promoting Pathways in Colorectal Cancer

BioMed Research International ◽

10.1155/2020/6909672 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Jinpeng Yuan ◽

Aosi Xie ◽

Qiangjian Cao ◽

Xinxin Li ◽

Juntian Chen

Keyword(s):

Colorectal Cancer ◽

Signaling Pathways ◽

Signaling Pathway ◽

Transforming Growth Factor ◽

Cox Regression ◽

Prognostic Biomarker ◽

Disease Free Survival ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Receptor Interaction

Background. Inhibin subunit beta B (INHBB) is a protein-coding gene that participated in the synthesis of the transforming growth factor-β (TGF-β) family members. The study is aimed at exploring the clinical significance of INHBB in patients with colorectal cancer (CRC) by bioinformatics analysis. Methods. Real-time PCR and analyses of Oncomine, Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) databases were utilized to evaluate the INHBB gene transcription level of colorectal cancer (CRC) tissue. We evaluated the INHBB methylation level and the relationship between expression and methylation levels of CpG islands in CRC tissue. The corresponding clinical data were obtained to further explore the association of INHBB with clinical and survival features. In addition, Gene Set Enrichment Analysis (GSEA) was performed to explore the gene ontology and signaling pathways of INHBB involved. Results. INHBB expression was elevated in CRC tissue. Although the promoter of INHBB was hypermethylated in CRC, methylation did not ultimately correlate with the expression of INHBB. Overexpression of INHBB was significantly and positively associated with invasion depth, distant metastasis, and TNM stage. Cox regression analyses and Kaplan-Meier survival analysis indicated that high expression of INHBB was correlated with worse overall survival (OS) and disease-free survival (DFS). GSEA showed that INHBB was closely correlated with 5 cancer-promoting signaling pathways including the Hedgehog signaling pathway, ECM receptor interaction, TGF-β signaling pathway, focal adhesion, and pathway in cancer. INHBB expression significantly promoted macrophage infiltration and inhibited memory T cell, mast cell, and dendritic cell infiltration. INHBB expression was positively correlated with stromal and immune scores of CRC samples. Conclusion. INHBB might be a potential prognostic biomarker and a novel therapeutic target for CRC.

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Identification of key lncRNAs and mRNAs associated with Oral squamous cell carcinoma progression

Current Bioinformatics ◽

10.2174/1573411016999200729125745 ◽

2020 ◽

Vol 15 ◽

Author(s):

Yong Mi ◽

Na Li ◽

Qing Li ◽

Yang Shi ◽

Congcong Zhang ◽

...

Keyword(s):

Immune Response ◽

Squamous Cell Carcinoma ◽

Oral Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Signaling Pathway ◽

Squamous Cell ◽

Differentially Expressed ◽

Receptor Interaction ◽

Type I ◽

Catabolic Process

Background: Oral squamous cell carcinoma (OSCC) had been the sixth most common cancer worldwide. Emerging studies showed long non-coding RNAs played a key role in human cancers. However, the molecular mechanisms underlying the initiation and progression of OSCC remained to be further explored Objective: The present study aimed to identify differentially expressed lncRNAs and mRNAs in OSCC. Methods: GSE30784 was analyzed to identify differentially expressed lncRNAs and mRNAs in OSCC. Protein-protein interaction network and co-expression network analysis were performed to reveal the potential roles of OSCC related mRNAs and lncRNAs Results: In present study, we identified 21 up-regulated lncRNAs and 54 down-regulated lncRNAs in OSCC progression. Next we constructed a lncRNA related co-expression network in OSCC, which included 692 mRNAs and 2193 edges. Bioinformatics analysis showed lncRNAs were widely co-expressing with regulating type I interferon signaling pathway, extracellular matrix organization, collagen catabolic process, immune response, ECM-receptor interaction, Focal adhesion, and PI3K-Akt signaling pathway. A key network, included lncRNA C5orf66-AS1, C21orf15, LOC100506098, PCBP1-AS1, LOC284825, OR7E14P, HCG22, and FLG-AS1, were found to be involved in the regulation of immune response to tumor cell, Golgi calcium ion transport, negative regulation of vitamin D receptor signaling pathway, glycerol-3-phosphate catabolic process. Moreover, we found showed higher expression of CYP4F29P, PCBP1-AS1, HCG22, and C5orf66-AS1were associated with shorter overall survival time in OSCC samples Conclusions: We thought our analysis could provide novel insights to explore the potential mechanisms underlying OSCC progression

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Transcriptome analysis reveals modulation of the STAT family in PEDV-infected IPEC-J2 cells

BMC Genomics ◽

10.1186/s12864-020-07306-2 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Zhengzheng Hu ◽

Yuchen Li ◽

Heng Du ◽

Junxiao Ren ◽

Xianrui Zheng ◽

...

Keyword(s):

Transcription Factors ◽

Differentially Expressed Genes ◽

Influenza A ◽

Molecular Mechanisms ◽

Host Cells ◽

Differentially Expressed ◽

Economic Losses ◽

Receptor Interaction ◽

Epithelial Cell Line ◽

Diarrhea Virus

Abstract Background Porcine epidemic diarrhea virus (PEDV) is a causative agent of serious viral enteric disease in suckling pigs. Such diseases cause considerable economic losses in the global swine industry. Enhancing our knowledge of PEDV-induced transcriptomic responses in host cells is imperative to understanding the molecular mechanisms involved in the immune response. Here, we analyzed the transcriptomic profile of intestinal porcine epithelial cell line J2 (IPEC-J2) after infection with a classical strain of PEDV to explore the host response. Results In total, 854 genes were significantly differentially expressed after PEDV infection, including 716 upregulated and 138 downregulated genes. Functional annotation analysis revealed that the differentially expressed genes were mainly enriched in the influenza A, TNF signaling, inflammatory response, cytokine receptor interaction, and other immune-related pathways. Next, the putative promoter regions of the 854 differentially expressed genes were examined for the presence of transcription factor binding sites using the MEME tool. As a result, 504 sequences (59.02%) were identified as possessing at least one binding site of signal transducer and activator of transcription (STAT), and five STAT transcription factors were significantly induced by PEDV infection. Furthermore, we revealed the regulatory network induced by STAT members in the process of PEDV infection. Conclusion Our transcriptomic analysis described the host genetic response to PEDV infection in detail in IPEC-J2 cells, and suggested that STAT transcription factors may serve as key regulators in the response to PEDV infection. These results further our understanding of the pathogenesis of PEDV.

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Systematic Profiling of Diagnostic and Prognostic Value of Autophagy-Related Genes for Sarcoma Patients

10.21203/rs.3.rs-76971/v1 ◽

2020 ◽

Author(s):

Yuanhe Wang ◽

Jianyi Li ◽

Cheng Shao ◽

Xiaojie Tang ◽

Yukun Du ◽

...

Keyword(s):

Tumor Microenvironment ◽

Immune Cells ◽

Disease Free Survival ◽

Independent Set ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Immune Checkpoints ◽

Systematic Analysis

Abstract Background: Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking.Methods: Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set. Results: In total, 84 DEIRGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between twp clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.636 for the OS and DFS nomograms, respectively.Conclusion: This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

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A Pan-Cancer Analysis of Transcriptome and Survival Reveals Prognostic Differentially Expressed LncRNAs and Predicts Novel Drugs for Glioblastoma Multiforme Therapy

Frontiers in Genetics ◽

10.3389/fgene.2021.723725 ◽

2021 ◽

Vol 12 ◽

Author(s):

Rongchuan Zhao ◽

Xiaohan Sa ◽

Nan Ouyang ◽

Hong Zhang ◽

Jiao Yang ◽

...

Keyword(s):

Glioblastoma Multiforme ◽

Survival Data ◽

Drug Target ◽

Differentially Expressed ◽

Prognostic Biomarkers ◽

Cancer Type ◽

Cancer Pathogenesis ◽

Cancer Types ◽

Novel Drug ◽

Pan Cancer

Numerous studies have identified various prognostic long non-coding RNAs (LncRNAs) in a specific cancer type, but a comprehensive pan-cancer analysis for prediction of LncRNAs that may serve as prognostic biomarkers is of great significance to be performed. Glioblastoma multiforme (GBM) is the most common and aggressive malignant adult primary brain tumor. There is an urgent need to identify novel therapies for GBM due to its poor prognosis and universal recurrence. Using available LncRNA expression data of 12 cancer types and survival data of 30 cancer types from online databases, we identified 48 differentially expressed LncRNAs in cancers as potential pan-cancer prognostic biomarkers. Two candidate LncRNAs were selected for validation in GBM. By the expression detection in GBM cell lines and survival analysis in GBM patients, we demonstrated the reliability of the list of pan-cancer prognostic LncRNAs obtained above. By constructing LncRNA-mRNA-drug network in GBM, we predicted novel drug-target interactions for GBM correlated LncRNA. This analysis has revealed common prognostic LncRNAs among cancers, which may provide insights into cancer pathogenesis and novel drug target in GBM.

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Identification of therapeutic targets and prognostic biomarkers among STAT family in glioblastoma

10.21203/rs.2.23359/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Chenglin Li ◽

Yanfei Zhou ◽

Hanshun Deng ◽

Yuanshen Ye ◽

Shuizhen Zhao ◽

...

Keyword(s):

Immune Response ◽

Signaling Pathway ◽

Web Applications ◽

Therapeutic Targets ◽

Prognostic Biomarkers ◽

Receptor Interaction ◽

Immune Gene ◽

Kegg Pathways ◽

Incidence And Mortality ◽

Regulation Network

Abstract Background: Glioblastoma (GBM) is the most common and aggressive primary brain malignancies with high incidence and mortality. The aberrant activation of STAT signaling was confirmed to result in tumor pathogenesis and progress by regulating cell cycle, cell survival, and immune response. Methods: The clinical significance of and regulation network of STAT family in GBM were explored with several web applications or database. Results: The level of STAT1/3/5A/5B/6 were increased in GBM while STAT4 level was decreased. GBM patients with high expression of STAT1/2/3/5A/6 and low expression of STAT4/5B had a worse overall survival. Among the STAT family, STAT 4 and STAT6 were the top two frequently mutated genes. Correlation suggested a low to moderate correlation among STAT family. STAT family were also involved in the activation or inhibition of the famous cancer related pathways. Immune infiltrates analysis suggested that STAT5A level showed significantly correlated with the abundance of immune cells and the level of immune gene biomarkers. GO functions and KEGG pathways analysis revealed that STAT5A was involved in immune response-regulating signaling pathway, neutrophil and lymphocyte mediated immunity, single-stranded DNA binding, cytokine-cytokine receptor interaction, NOD-like receptor signaling pathway, NF-kappa B signaling pathway, and TNF signaling pathway. Moreover, we also identified several Kinase and transcription factor targets of STAT5A in GBM. Conclusions: Our results revealed the therapeutic targets, prognostic biomarkers and regulation network of STAT family in GBM, laying the foundation for further studies about STAT family in therapy and prognosis of GBM.

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Differential Analysis of Expressed Genes in Diabetic Nephropathy Based on Bioinformatics Technology

10.21203/rs.3.rs-770285/v1 ◽

2021 ◽

Author(s):

Yu Liu ◽

Jundong Wang ◽

wencheng Chi ◽

Jing Xie ◽

LaiKuan Teh ◽

...

Keyword(s):

Gene Expression ◽

Diabetic Nephropathy ◽

Signaling Pathway ◽

Differentially Expressed Genes ◽

Biological Effects ◽

Cytokine Receptor ◽

Differentially Expressed ◽

Receptor Interaction ◽

Differential Analysis ◽

Core Genes

Abstract Objective: Bioinformatics technology was used in this study to analyze the expression data of patients with diabetic nephropathy (DN) and normal subjects from the microarray. The purpose of this study was to screen the differentially expressed genes in DN and to explore the pathogenesis and potential therapeutic targets of DN. Methods: The data of gene expression in the gse142153 gene chip was downloaded from the gene expression database (GEO). The up-regulated and down-regulated expressed genes were analyzed by R language. The core genes of differentially expressed genes were analyzed by string database, Cytoscape software and its plug-in. The differentially expressed genes were analyzed by gene ontology and Kyoto Encyclopedia of genes and genomes. Results: A total of 112 differentially expressed genes were screened, including 50 down-regulated genes and 62 up-regulated genes. There are 10 up-regulated core genes including CXCL8, MMP9, IL1B, IL6, IL10, CXCL2, CCL20, ATF3, CXCL3, F3. Their biological effects are mainly concentrated in the IL-17 signaling pathway, rheumatoid arthritis, viral protein interaction with cytokine and cytokine receptor, Amoebiasis, TNF signaling pathway, Legionellosis, Cytokine-cytokine receptor interaction, Lipid, and atherosclerosis, Malaria, NOD-like receptor signaling pathway, etc. Conclusion: Analysis of differentially expressed genes and core genes enhanced the understanding of the pathogenesis of DN and provided a potential train of thought for the treatment of DN.

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