Key Genes in the JAZ Signaling Pathway Are Up-Regulated Faster and More Abundantly in Caterpillar-Resistant Maize

Objective: This work aimed to investigate the molecular mechanisms underlying the efficacy of vemurafenib as a treatment for melanoma. Methods: The GSE52882 dataset, which includes A375 and A2058 melanoma cell lines treated with vemurafenib and dimethyl sulfoxide (DMSO), and clinical information associated with melanoma patients, were acquired from the Gene Expression Omnibus (GEO) database and University of California Santa Cruz (UCSC), respectively. Functional enrichment analysis, protein-protein interaction (PPI) network construction, sub-module analysis, and transcriptional regulation analysis were performed on overlapping differentially expressed genes (DEGs) identified in both cell lines. Finally, we performed a survival analysis based on the genes identified. Results: A total of 447 consistently overlapping DEGs (176 up- and 271 down-regulated DEGs) were screened. Upregulated genes were enriched in pathways of neurotrophin signaling, estrogen signaling, and transcriptional misregulation in cancer. Downregulated DEGs played essential roles in melanogenesis, pathways of cancer, PI3K-Akt signaling pathway, and AMPK signaling pathway. Upregulated (MMP2, JUN, KAT28, and PIK3R3) and downregulated genes (CXCL8, CCND1, IGF1R, and ITGB3) were considered as hub genes in the PPI network. Additionally, PIK3R3 and LEF1 served as key genes in the regulatory network. The overexpression of MMP2 and CXCL8 was associated with a poor prognosis in melanoma patients. Results: A total of 447 consistently overlapping DEGs (176 up- and 271 down-regulated DEGs) were screened. Upregulated genes were enriched in pathways of neurotrophin signaling, estrogen signaling, and transcriptional misregulation in cancer. Downregulated DEGs played essential roles in melanogenesis, pathways of cancer, PI3K-Akt signaling pathway, and AMPK signaling pathway. Upregulated (MMP2, JUN, KAT28, and PIK3R3) and downregulated genes (CXCL8, CCND1, IGF1R, and ITGB3) were considered as hub genes in the PPI network. Additionally, PIK3R3 and LEF1 served as key genes in the regulatory network. The overexpression of MMP2 and CXCL8 was associated with a poor prognosis in melanoma patients. Conclusion: MMP2, CXCL8, PIK3R3, ITGB3, and LEF1 may play roles in the efficacy of vemurafenib treatment in melanoma; for example, MMP2 and PIK3R3 are likely associated with vemurafenib resistance. These findings will contribute to the development of novel therapies for melanoma.

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Transgelin interacts with PARP1 and affects Rho signaling pathway in human colon cancer cells

10.21203/rs.3.rs-15780/v1 ◽

2020 ◽

Author(s):

Zhen-xian Lew ◽

Hui-min Zhou ◽

Yuan-yuan Fang ◽

Zhen Ye ◽

Wa Zhong ◽

...

Keyword(s):

Mass Spectrometry ◽

Colon Cancer ◽

Transcription Factor ◽

High Performance Liquid Chromatography ◽

Cancer Cells ◽

Signaling Pathway ◽

High Performance ◽

Colon Cancer Cells ◽

Over Expression ◽

Key Genes

Abstract Background: Transgelin, an actin-binding protein, is associated with the cytoskeleton remodeling. Our previous studies found that transgelin was up-regulated in node-positive colorectal cancer versus in node-negative disease. Over-expression of TAGLN affected the expression of 256 downstream transcripts and increased the metastatic potential of colon cancer cells in vitro and in vivo. This study aims to explore the mechanisms that transgelin participates in the metastasis of colon cancer cells.Methods: Immunofluorescence and immunoblotting analysis were used to determine the cellular localization of the endogenous and exogenous transgelin in colon cancer cells. Co-immunoprecipitation and subsequent high performance liquid chromatography/tandem mass spectrometry were performed to identify the proteins potentially interacting with transgelin. Bioinformatics methods were used to analyze the 256 downstream transcripts regulated by transgelin to discriminate the specific key genes and signaling pathways. By analyzing the promoter region of these key genes, GCBI tools were used to predict the potential transcription factor(s) for these genes. The predicted transcription factors were matching to the proteins that have been identified to potentially interact with transgelin. The interaction between transgelin and these transcription factors was verified by co-immunoprecipitation and immunoblotting.Results: Transgelin was found to localize both in the cytoplasm and the nucleus of colon cancer cells. 297 proteins have been identified to interact with transgelin by co-immunoprecipitation and subsequent high performance liquid chromatography/mass spectrometry. Over-expression of TAGLN could lead to differential expression of 184 downstream genes. By constructing the network of gene-encoded proteins, 7 genes (CALM1, MYO1F, NCKIPSD, PLK4, RAC1, WAS and WIPF1) have been discriminated as key genes using network topology analysis. They are mostly involved in the Rho signaling pathway. Poly ADP-ribose polymerase-1 (PARP1) was predicted as the unique transcription factor for the key genes and concurrently matching to the DNA-binding proteins potentially interacting with transgelin. Immunoprecipitation validated that PARP1 interacted with transgelin in human RKO colon cancer cells.Conclusions: The results of this study suggest that transgelin binds to PARP1 and regulates the expression of the downstream key genes mainly involving Rho signaling pathway, thus participates in the metastasis of colon cancer.

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Integrated bioinformatics approach to understand immune-related key genes and pathways in chronic spontaneous urticaria

10.21203/rs.3.rs-137346/v1 ◽

2020 ◽

Author(s):

wenxing su ◽

biao huang ◽

ying zhao ◽

xiaoyan zhang ◽

lu chen ◽

...

Keyword(s):

Signaling Pathway ◽

Protein Interaction ◽

Chronic Spontaneous Urticaria ◽

Signal Pathways ◽

Radical Cure ◽

Ppi Network ◽

Erythroid Progenitor ◽

Immune Infiltration ◽

Protein Protein Interaction ◽

Key Genes

Abstract Background Chronic spontaneous urticaria (CSU) refers to recurrent urticaria that lasts for more than 6 weeks in the absence of an identifiable trigger. Due to its recurrent wheal and severe itching, CSU seriously affects patients' life quality. There is currently no radical cure for it and its vague pathogenesis limits the development of targeted therapy. With the goal of revealing the underlying mechanism, two data sets with accession numbers GSE57178 and GSE72540 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed genes (DEGs) of CSU skin lesion samples and healthy controls, four kinds of analyses were performed, namely functional annotation, protein-protein interaction (PPI) network and module construction, co-expression and drug-gene interaction prediction analysis, and immune and stromal cells deconvolution analyses. Results 92 up-regulated genes and 7 down-regulated genes were selected for subsequent analyses. Through the enrichment analysis of the core modules, three signal pathways were found to be closely related to the occurrence and development of CSU, including TNF signaling pathway, NF-κB signaling pathway and Jak-STAT signaling pathway. Referring to protein-protein interaction (PPI) network analysis and GeneCards database, we identified four key genes, IL6, TLR4, ICAM1, and PTGS2. In addition, according to the results of immune infiltration analysis, CSU tissue generally contained a higher proportion of dendritic cells, Th2 cells, mast cells, megakaryocyte-erythroid progenitor, preadipocytes, and macrophages M1. Conclusions To conclude, the key genes and pathways identified from CSU lesions and normal controls along with the immune infiltration profile may provide new insights into the development of CSU.

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Identification of Key Biomarkers and Immune Infiltration in Sciatic Nerve of Diabetic Neuropathy BKS-db/db Mice by Bioinformatics Analysis

Frontiers in Pharmacology ◽

10.3389/fphar.2021.682005 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yixuan Lin ◽

Fanjing Wang ◽

Lianzhi Cheng ◽

Zhaohui Fang ◽

Guoming Shen

Keyword(s):

Diabetic Neuropathy ◽

Signaling Pathway ◽

Functional Enrichment ◽

Hub Genes ◽

Data Set ◽

Immune Infiltration ◽

P53 Signaling ◽

Ppi Networks ◽

Key Genes ◽

P53 Signaling Pathway

Diabetic neuropathy (DN) is one of the chronic complications of diabetes which can cause severe harm to patients. In order to determine the key genes and pathways related to the pathogenesis of DN, we downloaded the microarray data set GSE27382 from Gene Expression Omnibus (GEO) and adopted bioinformatics methods for comprehensive analysis, including functional enrichment, construction of PPI networks, central genes screening, TFs-target interaction analysis, and evaluation of immune infiltration characteristics. Finally, we examined quantitative real- time PCR (qPCR) to validate the expression of hub genes. A total of 318 differentially expressed genes (DEGs) were identified, among which 125 upregulated DEGs were enriched in the mitotic nuclear division, extracellular region, immunoglobulin receptor binding, and p53 signaling pathway, while 193 downregulated DEGs were enriched in ion transport, membrane, synapse, sodium channel activity, and retrograde endocannabinoid signaling. GSEA plots showed that condensed nuclear chromosome kinetochore were the most significant enriched gene set positively correlated with the DN group. Importantly, we identified five central genes (Birc5, Bub1, Cdk1, Ccnb2, and Ccnb1), and KEGG pathway analysis showed that the five hub genes were focused on progesterone-mediated oocyte maturation, cell cycle, and p53 signaling pathway. The proportion of immune cells from DN tissue and normal group showed significant individual differences. In DN samples, T cells CD4 memory resting and dendritic cells resting accounted for a higher proportion, and macrophage M2 accounted for a lower proportion. In addition, all five central genes showed consistent correlation with immune cell infiltration levels. qPCR showed the same expression trend of five central genes as in our analysis. Our research identified key genes related to differential genes and immune infiltration related to the pathogenesis of DN and provided new diagnostic and potential therapeutic targets for DN.

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Transcriptomic Analysis Reveals Both Coxsackievirus B3 Woodruff and GD Strain Using Similar Key Genes to Induce FoxO Signaling Pathway Activation in HeLa Cells

10.21203/rs.3.rs-193617/v1 ◽

2021 ◽

Author(s):

Mi Liu ◽

Qian Yang ◽

Jun Han

Keyword(s):

Oxidative Stress ◽

Cell Cycle ◽

Signaling Pathway ◽

Hela Cells ◽

Stress Resistance ◽

Coxsackievirus B3 ◽

Common Mechanism ◽

Oxidative Stress Resistance ◽

Key Genes ◽

Foxo Signaling Pathway

Abstract Coxsackievirus B3 (CVB3) is the major cause of viral myocarditis in human worldwide. Various studies have investigated the viral infection and pathogenic mechanisms. However, the precise disease mechanism is still not clear. In this study, RNA-seq technology was used to compare the transcriptomic profile of virus infected HeLa cells to the controls in order to analysis the key genes of host virus interaction. Two CVB3 strains, CVB3 Woodruff and GD16-69-CVB3 strain were selected to figure out the common disease mechanisms of both experimental and clinical strains respectively. Increased expression of cell cycle genes CCNG2, GADD45B, PIM1, RBM15, KLF10 and RIOK3, down regulation of CYBA were detected. Autophagy genes ATG12 and YOD1 were also upregulated during CVB3 infection. Slightly increase of SOD2 and ATG12 were shown in the expression of infected cells, meanwhile, little change was detected in GABARAP expression. Further, FoxO signaling pathway was enriched by KEGG analysis, shown a close interaction with the DEGs in the PPI network. Genes of related pathways such as cell cycle, autophagy and oxidative stress resistance were confirmed by RT-PCR as well. In conclusion, our results reveal that FoxO signaling pathway is a common mechanism activated during the infection of both CVB3 strains. And this pathway plays a regulatory role in downstream pathways such as cell cycle, autophagy, oxidative stress resistance and antiviral immune responds.

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Exploration of the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology and molecular docking

10.21203/rs.3.rs-39351/v2 ◽

2020 ◽

Author(s):

Rong-Bin Chen ◽

Ying-Dong Yang ◽

Kai Sun ◽

Shan Liu ◽

Wei Guo ◽

...

Keyword(s):

Molecular Docking ◽

Postmenopausal Osteoporosis ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Active Ingredients ◽

Active Compounds ◽

Core Proteins ◽

Key Genes

Abstract Background: Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease, which poses huge challenges to individuals and society. Ziyin Tongluo Formula (ZYTLF) has been proved effective in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP have not been thoroughly elucidated.Methods: Online databases were used to identify the active ingredients of ZYTLF and corresponding putative targets. Genes associated with PMOP were mined, and then mapped with the putative targets to obtain overlapping genes. Multiple networks were constructed and analyzed, from which the key genes were selected. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analysis. Finally, AutoDock Tools and other software were used for molecular docking of core compounds and key proteins. Results: Ninety-two active compounds of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. Network analysis showed the top 5 active ingredients including quercetin, kaempferol, luteolin, scutellarein, and formononetin., and the top 50 key genes such as VEGFA, MAPK8, AKT1, TNF, ESR1. Enrichment analysis uncovered two significant types of KEGG pathways in PMOP, hormone-related signaling pathways (estrogen , prolactin, and thyroid hormone signaling pathway) and inflammation-related pathways (TNF, PI3K-Akt, and MAPK signaling pathway). Moreover, molecular docking analysis verified that the main active compounds were tightly bound to the core proteins, further confirming the anti-PMOP effects. Conclusions: Based on network pharmacology and molecular docking technology, this study initially revealed the mechanisms of ZYTLF on PMOP, which involves multiple targets and multiple pathways.

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Identification of Five Cytotoxicity-Related Genes Involved in the Progression of Triple-Negative Breast Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.723477 ◽

2022 ◽

Vol 12 ◽

Author(s):

Yan Zhang ◽

Gui-hui Tong ◽

Xu-Xuan Wei ◽

Hai-yang Chen ◽

Tian Liang ◽

...

Keyword(s):

Breast Cancer ◽

T Cell ◽

Signaling Pathway ◽

Therapeutic Efficacy ◽

Normal Tissue ◽

R Package ◽

Rna Seq ◽

Matched Normal Tissue ◽

M1 Macrophage ◽

Key Genes

Background: Breast cancer is one of the deadly tumors in women, and its incidence continues to increase. This study aimed to identify novel therapeutic molecules using RNA sequencing (RNA-seq) data of breast cancer from our hospital.Methods: 30 pairs of human breast cancer tissue and matched normal tissue were collected and RNA sequenced in our hospital. Differentially expressed genes (DEGs) were calculated with raw data by the R package “edgeR”, and functionally annotated using R package “clusterProfiler”. Tumor-infiltrating immune cells (TIICs) were estimated using a website tool TIMER 2.0. Effects of key genes on therapeutic efficacy were analyzed using RNA-seq data and drug sensitivity data from two databases: the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Therapeutics Response Portal (CTRP).Results: There were 2,953 DEGs between cancerous and matched normal tissue, as well as 975 DEGs between primary breast cancer and metastatic breast cancer. These genes were primarily enriched in PI3K-Akt signaling pathway, calcium signaling pathway, cAMP signaling pathway, and cell cycle. Notably, CD8+ T cell, M0 macrophage, M1 macrophage, regulatory T cell and follicular helper T cell were significantly elevated in cancerous tissue as compared with matched normal tissue. Eventually, we found five genes (GALNTL5, MLIP, HMCN2, LRRN4CL, and DUOX2) were markedly corelated with CD8+ T cell infiltration and cytotoxicity, and associated with therapeutic response.Conclusion: We found five key genes associated with tumor progression, CD8+ T cell and therapeutic efficacy. The findings would provide potential molecular targets for the treatment of breast cancer.

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Active or Autoclaved Akkermansia muciniphila Relieves TNF-α-Induced Inflammation in Intestinal Epithelial Cells Through Distinct Pathways

Frontiers in Immunology ◽

10.3389/fimmu.2021.788638 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yuheng Luo ◽

Cong Lan ◽

Kunhong Xie ◽

Hua Li ◽

Estelle Devillard ◽

...

Keyword(s):

Epithelial Cells ◽

Signaling Pathway ◽

Intestinal Inflammation ◽

Intestinal Epithelial Cells ◽

Mrna Level ◽

Intestinal Epithelial ◽

Akkermansia Muciniphila ◽

Tnf Α ◽

Key Genes ◽

Cell Cycle Signaling

Intestinal inflammation is a major threat to the health and growth of young animals such as piglets. As a next-generation probiotics, limited studies have shown that Akkermansia muciniphila could alleviate inflammation of intestinal epithelial cells (IECs). In this study, a TNF-α-induced inflammatory model of IPEC-J2 cells, the intestinal porcine enterocytes, was built to evaluate the effects of active or inactive A. muciniphila on the inflammation of IECs. The viability of IPEC-J2 cells was the highest when treated with active (108 copies/mL) or inactive (109 copies/mL) A. muciniphila for 7.5 h (P < 0.01). Treated with 20 ng/mL of TNF-α and followed by a treatment of A. muciniphila, the mRNA level of proinflammatory cytokines (IL-8, IL-1β, IL-6 and TNF-α) was remarkably reduced (P < 0.05) along with the increased mRNA level of tight junction proteins (ZO-1 and Occludin, P < 0.05). Flow cytometry analysis showed that active or inactive A. muciniphila significantly suppressed the rate of the early and total apoptotic of the inflammatory IPEC-J2 cells (P < 0.05). According to results of transcriptome sequencing, active and inactive A. muciniphila may decline cell apoptosis by down-regulating the expression of key genes in calcium signaling pathway, or up-regulating the expression of key genes in cell cycle signaling pathway. And the bacterium may alleviate the inflammation of IECs by down-regulating the expression of PI3K upstream receptor genes. Our results indicate that A. muciniphila may be a promising NGP targeting intestinal inflammation.

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Identification of Key Genes and Pathways Associated with Mast Cells Resting in Meningioma

10.21203/rs.3.rs-80140/v1 ◽

2020 ◽

Author(s):

Hui Xie ◽

Xiao-hui Ding ◽

Ce Yuan ◽

Jin-jiang Li ◽

Zhao-yang Li ◽

...

Keyword(s):

Gene Expression ◽

Mast Cells ◽

Signaling Pathway ◽

Molecular Mechanisms ◽

Immune Cell ◽

Risk Model ◽

Kegg Pathway ◽

Expression Profiles ◽

Receptor Interaction ◽

Key Genes

Abstract Background: To identify candidate key genes and pathways related to mast cells resting in meningioma and the underlying molecular mechanisms of meningioma.Methods: Gene expression profiles of GSE43290 and GSE16581 datasets were obtained from the Gene Expression Omnibus (GEO) database. GO and KEGG pathway enrichments of DEGs were analyzed using the ClusterProfiler package in R. The protein-protein interaction network (PPI), and TF-miRNA- mRNA co-expression networks were constructed. Further, the difference in immune infiltration was investigated using the CIBERSORT algorithm.Results: A total of 1499 DEGs were identified between tumor and normal controls. The analysis of the immune cell infiltration landscape showed that the probability of distribution of memory B cells, regulatory T cells (Tregs), and resting mast cells in tumor samples were significantly higher than those in the controls. Moreover, through WGCNA analysis, the module related to mast cells resting contained 158 DEGs, and KEGG pathway analysis revealed that the DEGs were dominant in the TNF signaling pathway, cytokine-cytokine receptor interaction, and IL-17 signaling pathway. Survival analysis of hub genes related to mast cells resting showed that the risk model was constructed based on 9 key genes. The TF-miRNA- mRNA co-regulation network, including MYC-miR-145-5p, TNFAIP3-miR-29c-3p, and TNFAIP3-hsa-miR-335-3p, were obtained. Further, 36 nodes and 197 interactions in the PPI network were identified. Conclusions: The results of this study revealed candidate key genes, miRNAs, and pathways related to mast cells resting involved in meningioma development, providing potential therapeutic targets for meningioma treatment.

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Integrated Bioinformatics Analysis Reveals Potential Mechanisms Associated with Intestinal Flora Intervention in Non-alcoholic Fatty Liver Disease

10.21203/rs.3.rs-112110/v1 ◽

2020 ◽

Author(s):

Yingying Liu ◽

Xinkui Liu ◽

Wei Zhou ◽

Jingyuan Zhang ◽

Siyu Guo ◽

...

Keyword(s):

Liver Disease ◽

Fatty Liver ◽

Signaling Pathway ◽

Fatty Liver Disease ◽

Molecular Mechanisms ◽

Intestinal Flora ◽

Global Public Health ◽

Alcoholic Fatty Liver ◽

Key Genes ◽

Alcoholic Fatty Liver Disease

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease that imposes a huge economic burden on global public health. And the gut-liver axis theory supports the therapeutic role of intestinal flora in the development and progression of NAFLD. To this end, we designed bioinformatics study on the relationship between intestinal flora disorder and NAFLD, so as to explore the molecular mechanism of intestinal flora interfering with NAFLD. Methods Differentially expressed genes for NAFLD were obtained from GEO database. And the disease genes for NAFLD and intestinal flora disorder were obtained from the disease databases. Using string 11.0 database to establish protein-protein interaction network relationship and cytoscape 3.7.2 software visualization. Cytoscape plug-in MCODE and cytoHubba were used to screen the potential genes of intestinal flora disorder and NAFLD, so as to obtain potential targets for intestinal flora to interfere in the occurrence and process of NAFLD. Enrichment analysis of potential targets was carried out using R 4.0.2 software. Results The results showed that PTGS2, SPINK1 and C5AR1 may be the key genes for intestinal flora to interfere with NAFLD. CCL2, IL6, IL1B and FOS may be key genes for the development and progression of NAFLD. The gene function is mainly reflected in basic biological processes, including the regulation of metabolic process, epithelial development and immune influence. The pathway is mainly related to signal transduction, immune regulation and physiological metabolism. The TNF signaling pathway, AGE-RAGE signaling pathway in the diabetic activity, and NF-Kappa B signaling pathways are important pathways for intestinal flora to interfere with NAFLD. Conclusion According to the analysis results, there is a certain correlation between intestinal flora disorder and NAFLD. It is speculated that the mechanism by which intestinal flora may interfere with the occurrence and development of NAFLD is mainly related to inflammatory response and insulin resistance. Nevertheless, further research is needed to explore the specific molecular mechanisms.

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